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1
Zhong, Xu, Yu Zhou, and Hanyu Liu. "Design and recognition of artificial landmarks for reliable indoor self-localization of mobile robots." International Journal of Advanced Robotic Systems 14, no. 1 (January 1, 2017): 172988141769348. http://dx.doi.org/10.1177/1729881417693489.
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This article presents a self-localization scheme for indoor mobile robot navigation based on reliable design and recognition of artificial visual landmarks. Each landmark is patterned with a set of concentric circular rings in black and white, which reliably encodes the landmark’s identity under environmental illumination. A mobile robot in navigation uses an onboard camera to capture landmarks in the environment. The landmarks in an image are detected and identified using a bilayer recognition algorithm: A global recognition process initially extracts candidate landmark regions across the whole image and tries to identify enough landmarks; if necessary, a local recognition process locally enhances those unidentified regions of interest influenced by illumination and incompleteness and reidentifies them. The recognized landmarks are used to estimate the position and orientation of the onboard camera in the environment, based on the geometric relationship between the image and environmental frames. The experiments carried out in a real indoor environment show high robustness of the proposed landmark design and recognition scheme to the illumination condition, which leads to reliable and accurate mobile robot localization.
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Gerard, Ian J., Jeffery A. Hall, Kelvin Mok, and D. Louis Collins. "New Protocol for Skin Landmark Registration in Image-Guided Neurosurgery: Technical Note." Operative Neurosurgery 11, no. 3 (June 26, 2015): 376–81. http://dx.doi.org/10.1227/neu.0000000000000868.
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Abstract BACKGROUND Newer versions of the commercial Medtronic StealthStation allow the use of only 8 landmark pairs for patient-to-image registration as opposed to 9 landmarks in older systems. The choice of which landmark pair to drop in these newer systems can have an effect on the quality of the patient-to-image registration. OBJECTIVE To investigate 4 landmark registration protocols based on 8 landmark pairs and compare the resulting registration accuracy with a 9-landmark protocol. METHODS Four different protocols were tested on both phantoms and patients. Two of the protocols involved using 4 ear landmarks and 4 facial landmarks and the other 2 involved using 3 ear landmarks and 5 facial landmarks. Both the fiducial registration error and target registration error were evaluated for each of the different protocols to determine any difference between them and the 9-landmark protocol. RESULTS No difference in fiducial registration error was found between any of the 8-landmark protocols and the 9-landmark protocol. A significant decrease (P < .05) in target registration error was found when using a protocol based on 4 ear landmarks and 4 facial landmarks compared with the other protocols based on 3 ear landmarks. CONCLUSION When using 8 landmarks to perform the patient-to-image registration, the protocol using 4 ear landmarks and 4 facial landmarks greatly outperformed the other 8-landmark protocols and 9-landmark protocol, resulting in the lowest target registration error.
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Yu, Seung-Eun, Changmin Lee, and DaeEun Kim. "Analyzing the effect of landmark vectors in homing navigation." Adaptive Behavior 20, no. 5 (June 19, 2012): 337–59. http://dx.doi.org/10.1177/1059712312449543.
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The development of an autonomous navigating robot is a challenging task. Motivated by the performance of insects successfully returning to the nest, researchers have studied bio-inspired navigation algorithms for their potential use in mobile robots. In this paper, we analyze landmark-based approaches, especially Distance Estimated Landmark Vector (DELV), Average Correctional Vector and Average Landmark Vector methods, that use landmark vectors for visible environmental landmarks. We evaluated the homing performance of various landmark vector methods with surrounding landmarks under occlusion and found that the occluded or missing landmarks have a significant influence on the performance. We also developed a landmark vector algorithm with a visual compass that uses only retinal images without a reference compass. From our experimental results, we conclude that the DELV shows robust homing navigation performance with missing or occluded landmarks among landmark vector methods.
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Nguyen, Xuan-Ha, Van-Huy Nguyen, and Thanh-Tung Ngo. "A New Landmark Detection Approach for Slam Algorithm Applied in Mobile Robot." Journal of Science and Technology - Technical Universities 30.7, no. 146 (November 2020): 31–36. http://dx.doi.org/10.51316/30.7.6.
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Simultaneous Localization and Mapping is a key technique for mobile robot applications and has received much research effort over the last three decades. A precondition for a robust and life-long landmark-based SLAM algorithm is the stable and reliable landmark detector. However, traditional methods are based on laserbased data which are believed very unstable, especially in dynamic-changing environments. In this work, we introduce a new landmark detection approach using vision-based data. Based on this approach, we exploit a deep neural network for processing images from a stereo camera system installed on mobile robots. Two deep neural network models named YOLOv3 and PSMNet were re-trained and used to perform the landmark detection and landmark localization, respectively. The landmark’s information is associated with the landmark data through tracking and filtering algorithm. The obtained results show that our method can detect and localize landmarks with high stability and accuracy, which are validated by laser-based measurement data. This approach has opened a new research direction toward a robust and life-long SLAM algorithm.
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Yin, Meijuan, Wen Yang, Xiaonan Liu, and Xiangyang Luo. "Evaluator: A Multilevel Decision Approach for Web-Based Landmark Evaluation." Security and Communication Networks 2020 (July 15, 2020): 1–15. http://dx.doi.org/10.1155/2020/8843188.
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Street-level landmarks are an important basis for street-level IP geolocation, and the web-based landmark is one of the main sources of street-level landmarks. Considering the existing street-level landmark evaluation methods having low accuracy and strict constraints, this paper analyses the causes and evaluation idea of invalid web-based candidate landmarks and proposes Evaluator, a web-based landmark evaluation approach. Evaluator adopts the idea of the decision tree to filter invalid landmarks layer by layer and comprehensively estimates the quantitative reliability of candidate landmarks with public data and services to obtain reliable landmarks. This paper proposes the domain name system (DNS) distributed query algorithm to effectively resolve all IP addresses of a domain name, which provides data support for Evaluator to filter candidate landmarks. Meanwhile, this paper also proposes a reverse verification algorithm to obtain all domain names of an IP address, which provides an important reference to calculate the reliability of a reliable landmark. In addition, gradient descent is used to assess the parameters of the reliability estimating model, which effectively improves the robustness of Evaluator. Experiments show that reliable landmarks from Evaluator reduce the geolocation error of 100 targets in Hong Kong from 7.30 km to 3.91 km, compared with the landmark verifying method (LVM), one of the latest web-based landmark evaluation methods. Moreover, Evaluator significantly improves the evaluation coverage based on the same geolocation accuracy with street-level landmark evaluation (SLE), one of the latest landmark evaluation methods.
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Suriyampola, Piyumika S., and Perri K. Eason. "A field study investigating effects of landmarks on territory size and shape." Biology Letters 10, no. 4 (April 2014): 20140009. http://dx.doi.org/10.1098/rsbl.2014.0009.
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Few studies have examined how landmarks affect territories' fundamental characteristics. In this field study, we investigated effects of landmarks on territory size, shape and location in a cichlid fish ( Amatitlania siquia ). We provided cans as breeding sites and used plastic plants as landmarks. During 10 min trials, we recorded locations where residents chased intruders and used those locations to outline and measure the territory. In two experiments, we observed pairs without landmarks and with either a point landmark (one plant) or linear landmark (four plants) placed near the nest can. We alternated which trial occurred first and performed the second trial 24 h after the first. Territories were approximately round without landmarks or with a point landmark but were significantly more elongated when we added a linear landmark. Without landmarks, nests were centrally located; however, with any landmark, pairs set territory boundaries closer to the landmark and thus the nest. Territory size was significantly reduced in the presence of any landmark. This reduction suggests that a smaller territory with well-defined boundaries has greater benefits than a larger territory with less well-defined borders.
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Chimlek, Sutasinee, and Punpiti Piamsa-nga. "Incremental Tag Suggestion for Landmark Image Collections." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (February 1, 2016): 139. http://dx.doi.org/10.11591/ijece.v6i1.8540.
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In recent social media applications, descriptive information is collected through user tagging, such as face recognition, and automatic environment sensing, such as GPS. There are many applications that recognize landmarks using information gathered from GPS data. However, GPS is dependent on the location of the camera, not the landmark. In this research, we propose an automatic landmark tagging scheme using secondary regions to distinguish between similar landmarks. We propose two algorithms: 1) landmark tagging by secondary objects and 2) automatic new landmark recognition. Images of 30 famous landmarks from various public databases were used in our experiment. Results show increments of tagged areas and the improvement of landmark tagging accuracy.
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Chimlek, Sutasinee, and Punpiti Piamsa-nga. "Incremental Tag Suggestion for Landmark Image Collections." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (February 1, 2016): 139. http://dx.doi.org/10.11591/ijece.v6i1.pp139-150.
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In recent social media applications, descriptive information is collected through user tagging, such as face recognition, and automatic environment sensing, such as GPS. There are many applications that recognize landmarks using information gathered from GPS data. However, GPS is dependent on the location of the camera, not the landmark. In this research, we propose an automatic landmark tagging scheme using secondary regions to distinguish between similar landmarks. We propose two algorithms: 1) landmark tagging by secondary objects and 2) automatic new landmark recognition. Images of 30 famous landmarks from various public databases were used in our experiment. Results show increments of tagged areas and the improvement of landmark tagging accuracy.
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Song, Min Sun, Seong-Oh Kim, Ik-Hwan Kim, Chung-min Kang, and Je Seon Song. "Accuracy of Automatic Cephalometric Analysis Programs on Lateral Cephalograms of Preadolescent Children." JOURNAL OF THE KOREAN ACADEMY OF PEDTATRIC DENTISTRY 48, no. 3 (August 31, 2021): 245–54. http://dx.doi.org/10.5933/jkapd.2021.48.3.245.
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The aim of this study was to evaluate the accuracy of 3 different automatic landmark identification programs on lateral cephalgrams and the clinical acceptability in pediatric dentistry. Sixty digital cephalometric radiographs of 7 to 12 years old healthy children were randomly selected. Fourteen landmarks were chosen for assessment and the mean of 3 measurements of each landmark by a single examiner was defined as the baseline landmarks. The mean difference between an automatically identified landmark and the baseline landmark was measured for each landmark on each image. The total mean difference of 3 automatic programs compared to the baseline landmarks were 2.53 ± 1.63 mm. Errors among 3 programs were not significantly different for 12 of 14 landmarks except Orbitale and Gonion. The automatic landmark identification programs showed significant higher mean detection errors than the manual method. The programs couldn’t be used as the 1st tool to replace human examiners. But considering short consuming time, these results indicate that all 3 programs have sufficient validity to be used in pediatric dental clinic.
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Li, X,, X. Q. Wu, Z. H. Yin, and J. Shen. "THE INFLUENCE OF SPATIAL FAMILIARITY ON THE LANDMARK SALIENCE SENSIBILITY IN PEDESTRIAN NAVIGATION ENVIRONMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 12, 2017): 83–89. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-83-2017.
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To contribute to a more effective design of landmark navigation guidance, this paper is concerned with the relationship between the spatial familiarity and landmark salience, which includes visual, semantic and structural attributes. The link of those two is the subjective judgment of users, which is called landmark salience sensibility. In order to explore the influence of spatial familiarity on the landmark salience sensibility, we selected two types of experimental area including campus and commercial district and four groups of experimental subject with different spatial familiarity degree. After the whole walking process, subjects are asked to draw a navigation sketch for themselves. Depending on the landmarks remaining in the sketch, we calculated the three attributes of the mean landmark salience to represent the landmark salience sensibility of each group for both paths. The result shows that with the increase of spatial familiarity, the landmark salience sensitivity is gradually reduced and the ascending order of attention degree to the attributes of the landmark salience is visual, semantic and structural salience. This conclusion is supportive to the study of landmark extraction and pedestrian guidance. Because the outdoor landmarks are analysed, we propose that in the future indoor landmarks are needed to be concerned.
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Li, Ruixiang, Yuchen Sun, Jianwei Hu, Te Ma, and Xiangyang Luo. "Street-Level Landmark Evaluation Based on Nearest Routers." Security and Communication Networks 2018 (July 18, 2018): 1–12. http://dx.doi.org/10.1155/2018/2507293.
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High reliable street-level landmarks are the basis of IP geolocation, but landmark evaluation methods having been proposed cannot evaluate the street-level landmarks. Therefore, in this paper, a street-level landmark evaluation method based on nearest router is proposed. The location organization declared is regarded as an area not a point. Firstly, the declared location of preevaluated landmark is verified by IP location databases. Secondly, the preevaluated landmarks are grouped according to their nearest router. Then, the distance constraint is obtained using delay value between landmark and its nearest router by delay-distance correlation. And relation model is established among distance constraint, organization’s region radius, and distance between two landmarks. Finally, the reliability value of landmarks is calculated in each group based on relational model and binomial distribution. Landmarks evaluation experiment is taken based on 7082 preevaluated landmarks, and the results show that geolocation errors decrease obviously using evaluated landmarks. The mean error of 100 targets in Shanghai is reduced from 7.832km to 2.185km.
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TIAN, Zhaoxu, Yongmei CHENG, Xiaodong ZHANG, Su YANG, and Shun YAO. "Usability evaluation algorithm of sea area landmark." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 40, no. 1 (February 2022): 69–75. http://dx.doi.org/10.1051/jnwpu/20224010069.
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The landmarks encountered by a flight vehicle in its scene matching navigation are insufficient and distributed unevenly, thus being unable to effectively assist in its inertial navigation system (INS). Therefore, this paper proposes a novel algorithm for sea area landmark usability evaluation based on the probability model. The algorithm defines three types of sea area landmarks and gives their matching method and strategy. The visible range of each sea area landmark is determined according to its relative relations between each position and all landmarks in flight area, flight altitude, flight speed, camera field of view angle and INS drift error. The matching probability of different types of landmarks at different flight altitudes is calculated. Then the observable probability of each landmark is reckoned to give the probability cloud of the sea area landmark usability. The simulation results verify the effectiveness of the algorithm. The sea area landmark usability evaluation results can provide bases for INS to effectively utilize landmarks to perform route planning and realize long-time flight and high-precision navigation.
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Su, Kai, and Xin Geng. "Soft Facial Landmark Detection by Label Distribution Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5008–15. http://dx.doi.org/10.1609/aaai.v33i01.33015008.
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Most existing facial landmark detection algorithms regard the manually annotated landmarks as precise hard labels, therefore, the accurate annotated landmarks are essential to the training of these algorithms. However, in many cases, there exist deviations in manual annotations, and the landmarks marked for facial parts with occlusion and large poses are not always accurate, which means that the “ground truth” landmarks are usually not annotated precisely. In such case, it is more reasonable to use soft labels rather than explicit hard labels. Therefore, this paper proposes to associate a bivariate label distribution (BLD) to each landmark of an image. A BLD covers the neighboring pixels around the original manually annotated point, alleviating the problem of inaccurate landmarks. After generating a BLD for each landmark, the proposed method firstly learns the mappings from an image patch to the BLD of each landmark, and then the predicted BLDs are used in a deformable model fitting process to obtain the final facial shape for the image. Experimental results show that the proposed method performs better than the compared state-of-the-art facial landmark detection algorithms. Furthermore, the proposed method appears to be much more robust against the landmark noise in the training set than other compared baselines.
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Zhang, Lei, Chong-Jun Wang, Jun Wu, Meilin Liu, and Jun-Yuan Xie. "Planning with Multi-Valued Landmarks." Proceedings of the AAAI Conference on Artificial Intelligence 27, no. 1 (June 29, 2013): 1653–54. http://dx.doi.org/10.1609/aaai.v27i1.8520.
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Landmark heuristics are perhaps the most accurate current known admissible heuristics for optimal planning. A disjunctive action landmark can be seen a form of at-least-one constraint on the actions it contains. In many domains, some critical propositions have to be established for a number of times.Propositional landmarks are too weak to express this kind of constraints.In this paper, we propose to generalize landmarks to multi-valued landmarks to represent the more general cardinality constraints. We present a class of local multi-valued landmarks that can be efficiently extracted from propositional landmarks.By encoding multi-valued landmarks into CNF formulas, we can also use SAT solvers to systematically extract multi-valued landmarks.Experiment evaluations show that multi-valued landmark based heuristics are more close to $h^*$ andcompete favorably with the state-of-the-art of admissible landmark heuristics on benchmark domains.
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Liu, Shengli, Xiaowen Zhu, Zewei Cao, and Gang Wang. "Deep 1D Landmark Representation Learning for Space Target Pose Estimation." Remote Sensing 14, no. 16 (August 18, 2022): 4035. http://dx.doi.org/10.3390/rs14164035.
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Monocular vision-based pose estimation for known uncooperative space targets plays an increasingly important role in on-orbit operations. The existing state-of-the-art methods of space target pose estimation build the 2D-3D correspondences to recover the space target pose, where space target landmark regression is a key component of the methods. The 2D heatmap representation is the dominant descriptor in landmark regression. However, its quantization error grows dramatically under low-resolution input conditions, and extra post-processing is usually needed to compute the accurate 2D pixel coordinates of landmarks from heatmaps. To overcome the aforementioned problems, we propose a novel 1D landmark representation that encodes the horizontal and vertical pixel coordinates of a landmark as two independent 1D vectors. Furthermore, we also propose a space target landmark regression network to regress the locations of landmarks in the image using 1D landmark representations. Comprehensive experiments conducted on the SPEED dataset show that the proposed 1D landmark representation helps the proposed space target landmark regression network outperform existing state-of-the-art methods at various input resolutions, especially at low resolutions. Based on the 2D landmarks predicted by the proposed space target landmark regression network, the error of space target pose estimation is also smaller than existing state-of-the-art methods under all input resolution conditions.
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Cain, Peter, and Sapna Malwal. "Landmark use and development of navigation behaviour in the weakly electric fishGnathonemus petersii(Mormyridae; Teleostei)." Journal of Experimental Biology 205, no. 24 (December 15, 2002): 3915–23. http://dx.doi.org/10.1242/jeb.205.24.3915.
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SUMMARYAfrican mormyrids, such as Gnathonemus petersii, migrate:nocturnally, from daytime shelters to find food and return by morning, and seasonally, spawning in swamps flooded during the rainy season. The present study examined whether the fish use landmarks detected viaelectrolocation to locate an aperture, whether they detect changes in landmark size and respond appropriately, whether landmarks or hydrostatic pressure are the primary cues for navigation and whether fish of different developmental stages behave differently with respect to landmarks and navigation. The fish's task was to locate and swim through a circular aperture in a wall dividing an aquarium into two compartments. Two groups of fish were trained to find the aperture with a landmark present, while a control group had no such landmark. The water level remained constant throughout training. At the end of training,the fish's task was to locate the aperture after the landmark size had changed or the water level had increased. The results show that G. petersiiuse landmarks to orient and navigate. They can detect changes in landmark size and will modify their locomotor behaviour to integrate the change into an internal representation. If the water level changes, increasing hydrostatic pressure, the fish orient to a landmark, if present. If no landmark is present, the fish rely on an internal representation oriented to hydrostatic pressure. Larger, early-adult G. petersii located the aperture faster than smaller, sub-adult fish.
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TODT, EDUARDO, and CARME TORRAS. "OUTDOOR VIEW RECOGNITION BASED ON LANDMARK GROUPING AND LOGISTIC REGRESSION." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 03 (May 2013): 1355004. http://dx.doi.org/10.1142/s0218001413550045.
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Vision-based robot localization outdoors has remained more elusive than its indoors counterpart. Drastic illumination changes and the scarceness of suitable landmarks are the main difficulties. This paper attempts to surmount them by deviating from the main trend of using local features. Instead, a global descriptor called landmark-view is defined, which aggregates the most visually-salient landmarks present in each scene. Thus, landmark co-occurrence and spatial and saliency relationships between them are added to the single landmark characterization, based on saliency and color distribution. A suitable framework to compare landmark-views is developed, and it is shown how this remarkably enhances the recognition performance, compared against single landmark recognition. A view-matching model is constructed using logistic regression. Experimentation using 45 views, acquired outdoors, containing 273 landmarks, yielded good recognition results. The overall percentage of correct view classification obtained was 80.6%, indicating the adequacy of the approach.
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Deshmane, Prof Priyanka. "Continent Based Geo-Landmark Detection and Recognition Using CNN." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 2, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem32987.
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In the modern world, we need the development of an automated system that can accurately detect landmarks and provide essential services is important. The 'Continent-based Geo-Landmark Detection and Recognition using CNN" project develop the Continent-based Landmark Detection system using deep learning, specifically Convolutional neural network (CNNs). The system will be capable of identifying landmarks from uploaded images. It will provide a short summary about the identified landmarks, and extract geographic data such as landmark address, latitude and longitude and display them on the map. Additionally, the system will utilize location information (i.e. Latitude and Longitude) to locate 17 essential services such as Road Network, Hospitals, Bus Stops, Railway Station, ATM's, Religious Institutions (Temple, Masjid, Church and more) etc. around the identified landmark within a specified radius, such as 1000 meters (i.e. 1 kilometer). Keywords: CNN; Continents; Geo-landmark; Detection and Recognition; Convolution neural network; Deep Learning; Python.
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Sakai, Atsushi, Teppei Saitoh, and Yoji Kuroda. "Robust Landmark Estimation and Unscented Particle Sampling for SLAM in Dynamic Outdoor Environment." Journal of Robotics and Mechatronics 22, no. 2 (April 20, 2010): 140–49. http://dx.doi.org/10.20965/jrm.2010.p0140.
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In this paper, we propose a set of techniques for accurate and practical Simultaneous Localization And Mapping (SLAM) in dynamic outdoor environments. The techniques are categorized into Landmark estimation and Unscented particle sampling. Landmark estimation features stable feature detection and data management for estimating landmarks accurately, robustly, and at a low-calculation cost. The stable feature detection removes dynamic objects and sensor noise with scan subtraction, detects feature points sparsely and evenly, and sets data association parameters with landmark density. The data management calculates landmark existence probability and spurious landmarks are removed, utilizes landmark exclusivity for data association, and predicts importance weights using the observation range. Unscented particle sampling is based on Unscented Transformation for accurate SLAM. Simulation results of SLAM using our landmark estimation and experimental results of our SLAM in dynamic outdoor environments are presented and discussed. The results show that our landmark estimation decrease SLAM calculation time and maximum position error by 80% compared to conventional landmark estimation, and position estimation of SLAM with Unscented particle sampling ismore accurate than FastSLAM2.0 in dynamic outdoor environments.
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Collett, Matthew, Duane Harland, and Thomas S. Collett. "The use of landmarks and panoramic context in the performance of local vectors by navigating honeybees." Journal of Experimental Biology 205, no. 6 (March 15, 2002): 807–14. http://dx.doi.org/10.1242/jeb.205.6.807.
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SUMMARY Bees seem to use landmarks to segment familiar routes. They can associate, with a landmark, a memory that encodes the direction and distance of the path segment between that landmark and the next. The expression of the memory results in the performance of a local vector matching the distance and direction of the path segment. The memories of path segments appear to be ‘chained’ together, so that the performance of one local vector is sometimes sufficient to elicit the subsequent local vector, even in the absence of the associated landmark. We have investigated the effect of visual panoramic context on the expression of local vectors. Bees were trained to fly along a narrow channel to collect sucrose from a feeder positioned partway along it. Panoramic context was provided by various types of patterning on the walls. The channel was partitioned into different segments using landmarks of two kinds: a boundary landmark that marked a change in the pattern on one or both side-walls of the channel, and an isolated landmark, consisting of a baffle through which the bee passed, for which the wall pattern was the same before as after. In tests, we removed the feeder and analysed the search distribution of the bees for various arrangements of landmarks. Altering the spatial relationship between landmarks has different consequences for the two types of landmark. If the final boundary landmark is shifted, the centre of the search distribution shifts by approximately the same amount. Changes in the position of an isolated landmark have a weaker effect. In the absence of the final context, the search is disrupted. We suggest that for local vectors to be expressed the surrounding panoramic context needs to be appropriate. A comparison of search patterns from two different training configurations of landmarks supports the hypothesis that local vector memories merely encode route segments and that global positional coordinates are not linked to landmark memories.
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Yi, Yingmin, and Ying Huang. "Landmark Sequence Data Association for Simultaneous Localization and Mapping of Robots." Cybernetics and Information Technologies 14, no. 3 (September 1, 2014): 86–95. http://dx.doi.org/10.2478/cait-2014-0035.
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Abstract The paper proposes landmark sequence data association for Simultaneous Localization and Mapping (SLAM) for data association problem under conditions of noise uncertainty increase. According to the space geometric information of the environment landmarks, the information correlations between the landmarks are constructed based on the graph theory. By observing the variations of the innovation covariance using the landmarks of the adjacent two steps, the problem is converted to solve the landmark TSP problem and the maximum correlation function of the landmark sequences, thus the data association of the observation landmarks is established. Finally, the experiments prove that our approach ensures the consistency of SLAM under conditions of noise uncertainty increase.
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Chen, Min, and Hao Wu. "Landmark Dataset Development and Recognition." International Journal of Multimedia Data Engineering and Management 12, no. 4 (October 2021): 38–51. http://dx.doi.org/10.4018/ijmdem.2021100103.
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Landmark recognition aims to detect popular natural and manmade structures within an image. It is challenging with one of the reasons being the lack of large annotated datasets. Existing work mainly focuses on landmarks located in Europe and North America due to regional and language bias. In this study, the authors build a comprehensive Chinese landmark dataset to complement the current data and to benefit research for landmark recognition. It is done by leveraging the vast amount of multimedia data on the web and utilizing image clustering and retrieval techniques in data preparation and analysis. This results in a Chinese landmark dataset with a total of 42,548 images for 987 unique landmarks. In addition, a landmark recognition model is developed based on advanced deep learning techniques and integrated into a mobile application that allows users to do landmark prediction without the need of internet access or cellular data coverage.
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Wang, Yuan, Min Cao, Zhenfeng Fan, and Silong Peng. "Learning to Detect 3D Facial Landmarks via Heatmap Regression with Graph Convolutional Network." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (June 28, 2022): 2595–603. http://dx.doi.org/10.1609/aaai.v36i3.20161.
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3D facial landmark detection is extensively used in many research fields such as face registration, facial shape analysis, and face recognition. Most existing methods involve traditional features and 3D face models for the detection of landmarks, and their performances are limited by the hand-crafted intermediate process. In this paper, we propose a novel 3D facial landmark detection method, which directly locates the coordinates of landmarks from 3D point cloud with a well-customized graph convolutional network. The graph convolutional network learns geometric features adaptively for 3D facial landmark detection with the assistance of constructed 3D heatmaps, which are Gaussian functions of distances to each landmark on a 3D face. On this basis, we further develop a local surface unfolding and registration module to predict 3D landmarks from the heatmaps. The proposed method forms the first baseline of deep point cloud learning method for 3D facial landmark detection. We demonstrate experimentally that the proposed method exceeds the existing approaches by a clear margin on BU-3DFE and FRGC datasets for landmark localization accuracy and stability, and also achieves high-precision results on a recent large-scale dataset.
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Kim, Taehyung, Jiwon Mok, and Euichul Lee. "Detecting Facial Region and Landmarks at Once via Deep Network." Sensors 21, no. 16 (August 9, 2021): 5360. http://dx.doi.org/10.3390/s21165360.
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For accurate and fast detection of facial landmarks, we propose a new facial landmark detection method. Previous facial landmark detection models generally perform a face detection step before landmark detection. This greatly affects landmark detection performance depending on which face detection model is used. Therefore, we propose a model that can simultaneously detect a face region and a landmark without performing the face detection step before landmark detection. The proposed single-shot detection model is based on the framework of YOLOv3, a one-stage object detection method, and the loss function and structure are altered to learn faces and landmarks at the same time. In addition, EfficientNet-B0 was utilized as the backbone network to increase processing speed and accuracy. The learned database used 300W-LP with 64 facial landmarks. The average normalized error of the proposed model was 2.32 pixels. The processing time per frame was about 15 milliseconds, and the average precision of face detection was about 99%. As a result of the evaluation, it was confirmed that the single-shot detection model has better performance and speed than the previous methods. In addition, as a result of using the COFW database, which has 29 landmarks instead of 64 to verify the proposed method, the average normalization error was 2.56 pixels, which was also confirmed to show promising performance.
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Gwinn, Heather M., Shona Fernando, Sufiy James, and Josephine F. Wilson. "Do Landmarks Help or Hinder Women in Route Learning?" Perceptual and Motor Skills 95, no. 3 (December 2002): 713–18. http://dx.doi.org/10.2466/pms.2002.95.3.713.
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Previous research on route learning has demonstrated that men learn routes faster and with fewer errors than women, whereas women are able to recall more landmarks along the route. The present study was aimed at investigating whether landmarks help of hinder women when they learn a route. 47 female and 37 male undergraduate students were randomly assigned to one of two conditions, in which they learned a route on a map with landmarks (the Landmark condition) or with no landmarks (the No-Landmark condition). Men outperformed women in the Landmark condition, learning the route in less time, with fewer errors, and in fewer trials than women did. In contrast, in the No-Landmark condition, no significant differences were found between men and women on the route-learning measures. Men learned the route faster and more accurately when landmarks were present than when they were not, but the performance of women was not affected by the presence or absence of landmarks. These results surest that men and women may employ landmarks differently when learning a route Men may use the positions of landmarks to make distance and direction judgments, whereas women may label the landmarks and memorize these labels, which interferes with learning the route.
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Biegler, R., and R. Morris. "Landmark stability: studies exploring whether the perceived stability of the environment influences spatial representation." Journal of Experimental Biology 199, no. 1 (January 1, 1996): 187–93. http://dx.doi.org/10.1242/jeb.199.1.187.
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To investigate whether spatial learning complies with associative learning theories or with theories of cognitive mapping, rats were trained in three experiments exploring the effect of variations in spatial predictive relationships. In experiment 1, it was found that making one of two landmarks the sole spatial predictor of reward, by varying the spatial relationship between reward and other cues, reduced the control over search exerted by that landmark compared with that observed when the landmark and context cues were both reliable predictors of reward location. This requirement for landmark stability rather than predictive power appears to contradict results obtained in conventional conditioning paradigms. Discrimination learning was unaffected, suggesting a dissociation between discrimination and spatial learning with respect to the influence of geometric stability. Further experiments used arrays of both single and multiple landmarks. Experiment 2 revealed that the stability of a single landmark improved accuracy of search, but also showed that local stability between a pair of landmarks that moved around the arena together was sufficient to support spatial learning. Experiment 3 examined landmark stability using fixed directional cues in the absence of vestibular disorientation. This also revealed a relative advantage of stable landmarks, but animals presented with a landmark that moved from trial to trial did show some evidence of learning. Parametric manipulation of landmark stability offers an intriguing way of influencing the process of spatial representation and thus understanding better the processes through which egocentric representations of perceived space are transformed into allocentric representations of the real world.
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Raeisiyan, Razieh, Behrouz Abdoli, Alireza Farsi, and Hamidollah Hassanlouei. "The Effect of Landmarks With Their Color on Learning Basketball Lay-Up in Beginners." Journal of Motor Learning and Development 9, no. 2 (August 1, 2021): 286–95. http://dx.doi.org/10.1123/jmld.2020-0034.
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The purpose of this study was to determine the effect of landmarks on learning basketball lay-up in beginners. Twenty-seven females (age = 20.30 ± 0.24 years, height = 164.37 ± 0.53 cm) participated in this study. They were assigned to three groups: no landmark group, colored landmark group, and black and white landmark group. All participants performed basketball lay-up for six sessions. The colored group and black and white group trained with the landmarks on the ground while the no landmark group trained without any landmarks based on a trainer instruction. Posttest was performed at the end of the last session of training and also in the retention test following 72 hr. All trials were assessed through 5-point Likert scales, ranging from 1 (very poor) to 5 (very good). The results showed that using landmarks significantly changed the lay-up pattern; however, these changes were not significant for color and lay-up shot accuracy.
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Wolf, I., H. P. Meinzer, and T. Heimann. "Automatic Generation of 3D Statistical Shape Models with Optimal Landmark Distributions." Methods of Information in Medicine 46, no. 03 (2007): 275–81. http://dx.doi.org/10.1160/me9043.
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Summary Objectives: To point out the problem of non-uniform landmark placement in statistical shape modeling, to present an improved method for generating landmarks in the 3D case and to propose an unbiased evaluation metric to determine model quality. Methods: Our approach minimizes a cost function based on the minimum description length (MDL) of the shape model to optimize landmark correspondences over the training set. In addition to the standard technique, we employ an extended remeshing method to change the landmark distribution without losing correspondences, thus ensuring a uniform distribution over all training samples. To breakthe dependency of the established evaluation measures generalization and specificity from the landmark distribution, we change the internal metric from landmark distance to volumetric overlap. Results: Redistributing landmarks to an equally spaced distribution during the model construction phase improves the quality of the resulting models significantly if the shapes feature prominent bulges or other complex geometry. Conclusions: The distribution of landmarks on the training shapes is – beyond the correspondence issue – a crucial point in model construction.
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Rühaak, J., R. Werner, H. Handels, J. Modersitzki, and T. Polzin. "Lung Registration Using Automatically Detected Landmarks." Methods of Information in Medicine 53, no. 04 (2014): 250–56. http://dx.doi.org/10.3414/me13-01-0125.
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SummaryObjectives: Accurate registration of lung CT images is inevitable for numerous clinical applications. Usually, nonlinear intensity-based methods are used. Their accuracy is typically evaluated using corresponding anatomical points (landmarks; e.g. bifurcations of bronchial and vessel trees) annotated by medical experts in the images to register. As image registration can be interpreted as correspond ence finding problem, these corresponding landmarks can also be used in feature-based registration techniques. Recently, approaches for automated identification of such landmark correspondences in lung CT images have been presented. In this work, a novel combination of variational nonlinear intensity-based registration with an approach for automated landmark correspond ence detection in lung CT pairs is presented and evaluated.Methods: The main blocks of the proposed hybrid intensity- and feature-based registration scheme are a two-step landmark correspondence detection and the so-called CoLD (Combining Landmarks and Distance Measures) framework. The landmark correspondence identification starts with feature detection in one image followed by a blockmatching-based transfer of the features to the other image. The established correspond ences are used to compute a thin-plate spline (TPS) transformation. Within CoLD, the TPS transformation is improved by minimization of an objective function consisting of a Normalized Gradient Field distance measure and a curvature regularizer; the landmark correspondences are guaranteed to be preserved by optimization on the kernel of the discretized landmark constraints.Results: Based on ten publicly available end-inspiration/expiration CT scan pairs with anatomical landmark sets annotated by medical experts from the DIR-Lab database, it is shown that the hybrid registration approach is superior in terms of accuracy: The mean distance of expert landmarks is decreased from 8.46 mm before to 1.15 mm after registration, outperforming both the TPS transformation (1.68 mm) and a nonlinear registration without usage of automatically detected landmarks (2.44 mm). The improvement is statistically significant in eight of ten datasets in comparison to TPS and in nine of ten datasets in comparison to the intensity-based registration. Furthermore, CoLD globally estimates the breathing-induced lung volume change well and results in smooth and physiologically plausible motion fields of the lungs.Conclusions: We demonstrated that our novel landmark-based registration pipeline outperforms both TPS and the underlying nonlinear intensity-based registration without landmark usage. This highlights the potential of automatic landmark correspondence detection for improvement of lung CT registration accuracy.
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Zhao, Zikang, Yujia Zhang, Tianjun Wu, Hao Guo, and Yao Li. "Emotionally Controllable Talking Face Generation from an Arbitrary Emotional Portrait." Applied Sciences 12, no. 24 (December 14, 2022): 12852. http://dx.doi.org/10.3390/app122412852.
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With the continuous development of cross-modality generation, audio-driven talking face generation has made substantial advances in terms of speech content and mouth shape, but existing research on talking face emotion generation is still relatively unsophisticated. In this work, we present Emotionally Controllable Talking Face Generation from an Arbitrary Emotional Portrait to synthesize lip-sync and an emotionally controllable high-quality talking face. Specifically, we take a facial reenactment perspective, using facial landmarks as an intermediate representation driving the expression generation of talking faces through the landmark features of an arbitrary emotional portrait. Meanwhile, decoupled design ideas are used to divide the model into three sub-networks to improve emotion control. They are the lip-sync landmark animation generation network, the emotional landmark animation generation network, and the landmark-to-animation translation network. The two landmark animation generation networks are responsible for generating content-related lip area landmarks and facial expression landmarks to correct the landmark sequences of the target portrait. Following this, the corrected landmark sequences and the target portrait are fed into the translation network to generate an emotionally controllable talking face. Our method controls the expressions of talking faces by driving the emotional portrait images while ensuring the generation of animated lip-sync, and can handle new audio and portraits not seen during training. A multi-perspective user study and extensive quantitative and qualitative evaluations demonstrate the superiority of the system in terms of visual emotion representation and video authenticity.
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Büchner, Clemens, Thomas Keller, and Malte Helmert. "Exploiting Cyclic Dependencies in Landmark Heuristics." Proceedings of the International Conference on Automated Planning and Scheduling 31 (May 17, 2021): 65–73. http://dx.doi.org/10.1609/icaps.v31i1.15948.
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Landmarks of a planning task denote properties that must be satisfied by all plans. Existing landmark heuristics exploit that each landmark must be achieved at least once. However, if the orderings between the landmarks induce cyclic dependencies, one of the landmarks in each cycle must be achieved an additional time. We propose two novel heuristics for cost-optimal planning that consider cyclic dependencies between landmarks in addition to the cost for achieving all landmarks once. We show that our heuristics dominate the minimum hitting set solution over any set of landmarks as well as h+ if all delete-relaxation landmarks are considered. An experimental evaluation on benchmarks from the International Planning Competition shows that exploiting cyclic dependencies can lead to improved heuristics.
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Steck, Sibylle D., and Hanspeter A. Mallot. "The Role of Global and Local Landmarks in Virtual Environment Navigation." Presence: Teleoperators and Virtual Environments 9, no. 1 (February 2000): 69–83. http://dx.doi.org/10.1162/105474600566628.
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In visual navigation, landmarks can be used in a number of different ways. In this paper, we investigate the role of global and local landmarks in virtual environment navigation. We performed an experiment in a virtual environment called “Hexatown”, consisting of a regular hexagonal grid of streets and junctions. Each junction was identified by the presence of distinct local landmarks (buildings, phone box, and so on). Additionally, compass information or a global frame of reference was provided by global landmarks (hilltop, television tower, and city skyline). According to participants' movement decisions, egomotion was simulated, and displayed on a 180 deg. projection screen. Participants learned the route back and forth between two local landmarks. In the test phase, individual junctions were approached and the participant's movement decision was recorded. We performed two experiments involving landmark changes after learning. In the first, we used conflicting cues by transposing landmarks. In the second experiment, we reduced either local or global landmark information. Results show that both local and global landmarks are used in wayfinding decisions. However, different participants rely on different strategies. In the first experiment (cue conflict) for example, some of the participants used only local landmarks while others relied exclusively on global landmarks. Other participants used local landmarks at one location and global landmarks at the other. When removing one landmark type in the second experiment, the other type could be used by almost all participants, indicating that information about the neglected landmark type was present in memory.
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Yang, Bo, Xiaosu Xu, Jun Li, and Hong Zhang. "Landmark Generation in Visual Place Recognition Using Multi-Scale Sliding Window for Robotics." Applied Sciences 9, no. 15 (August 2, 2019): 3146. http://dx.doi.org/10.3390/app9153146.
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Landmark generation is an essential component in landmark-based visual place recognition. In this paper, we present a simple yet effective method, called multi-scale sliding window (MSW), for landmark generation in order to improve the performance of place recognition. In our method, we generate landmarks that form a uniform distribution in multiple landmark scales (sizes) within an appropriate range by a process that samples an image with a sliding window. This is in contrast to conventional methods of landmark generation that typically depend on detecting objects whose size distributions are uneven and, as a result, may not be effective in achieving shift invariance and viewpoint invariance, two important properties in visual place recognition. We conducted experiments on four challenging datasets to demonstrate that the recognition performance can be significantly improved by our method in a standard landmark-based visual place recognition system. Our method is simple with a single input parameter, the scales of landmarks required, and it is efficient as it does not involve detecting objects.
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Zhu, Litao, Milan Konečný, Jie Shen, Zdeněk Stachoň, and Hana Švedová. "The Influence of Spatial Familiarity on Landmark Salience Sensibility Based on Eye Tracking." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-438-2019.
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<p><strong>Abstract.</strong> Landmarks play an important role in navigation especially when people in the familiar and unfamiliar environment. These landmarks are usually used for expressing their spatial knowledge. This prior knowledge is related to the spatial familiarity that the spatial knowledge is acquired by individuals as a function of their experience in the environment (Gale et al., 1990). Individuals prefers to take into highly account their familiar route within the environment. Furthermore, the route descriptions include the differed types of landmarks in familiar/unfamiliar routes (Lovelace et al., 1999). The user’s level of spatial familiarity for people is a key factor of how they navigate in the environment (Savage et al., 2012). In human navigation or wayfinding, the dependency on familiar landmarks is the highest priority (Golledge, 2003).</p><p>Landmarks are more distinguishably salient and prominent than the another spatial features (Sorrows and Hirtle, 1999). Therefore, the landmark salience refers to how easily this prominent spatial feature can be regarded as a landmark (Raubal and Winter, 2002). The landmark salience mainly divided into visual, structural (important location), and cognitive (semantic). Visual salience refers to the visual characteristics of spatial features such as color contrast with surroundings. Some visual characteristics include facade areas, shapes, colors and other properties. Semantic salience refers to the spatial knowledge related features such as a cultural importance of building. Structural salience refers to the spatial features play an important role in the structure of the spatial environment.</p><p>The level of spatial knowledge of the individual also an important factor in landmark selection (Nuhn and Timpf, 2018). Hamburger and Röser (2014) investigated landmark semantics and showed that famous buildings were better recognized than unfamiliar ones. Quesnot and Roche (2015) found that the familiar individuals prefer the semantic landmarks in environment while the unfamiliar individuals prefer the landmark with the prominent visual and structural. In contrast, people unfamiliar with an environment prefer landmarks with outstanding visual and structural characteristics.</p><p>The existing literature studies the method that landmark indicators to be considered are not comprehensive while can’t reflect on the landmark characteristics. The reason is that the method of calculation and extraction for landmarks can’t conform the individual preference needs of navigation. Compared with the traditional subjective evaluation method, the eye-tracking method provide objectivity and reliability. For example, a mobile eye tracking system was used by Kiefer et al. (2014) to investigate the process of self-localization. They discovered that test persons directed their attention longer on landmarks on the map and aligned them with objects in the surroundings during successful localization of their own position. Schwarzkopf et al. (2013) used fixed and mobile eye tracking devices to study that participates selected the navigation landmarks in the virtual environment and the real-world of the airport. In general, there are an only limited number of works related to the influence of spatial familiarity on landmark by using eye tracking method.</p><p>At present, many navigation systems are providing users with route directions under different travel modes. These navigation systems have the "distance-to-turn" method in route directions, however the landmark knowledge has not been conformed to user's habits and spatial cognitive in wayfinding. In order to solve these problems, this paper aims to study the characteristics of the user’s spatial familiarity and landmark salience evaluation method in navigation. The following questions are addressed in this study: 1) What’s the relationship between the spatial familiarity with the landmark selection in navigation for individuals? 2) What is the quantitative evaluation model to connect between the spatial familiarity with the landmark salience by using the eye-tracking data?</p><p>In our experiments, we will use eye tracking to explore the influence of spatial familiarity on landmark salience. The experimental path is part of the campus area of Nanjing Normal University. The subjects are divided into novice students and senior students from Nanjing Normal University as unfamiliar and familiar groups respectively. The procedures are divided into two parts, namely, the subjects should walk the experimental path within the fixation time and then they are asked to wear VR eye tracking module a Glass DK II special for HTC view (China; https://www.7invensun.com/) to do three types of tasks about landmark picture with the characteristics of visual, semantic and structural. With this research, we expect to establish a landmark salience evaluation method through eye movement data and analyse the landmark selection rules of groups with different spatial familiarity. It is helpful to design the pedestrian navigation system based on landmarks, improve the pertinence and reliability of navigation services and reduce the cognitive load for users.</p>
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Lin, Guo Yu, and Xu Chen. "Robot Indoor Navigation Method Based on 2D Barcode Landmark." Applied Mechanics and Materials 44-47 (December 2010): 1279–84. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.1279.
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A method for robot indoor navigation based on two-dimensional (2D) barcode landmark is proposed. The scheme constructed on the 2D barcode principle is convenient to operate and easy to recognize landmarks and the barcode have coordinates for their positions and some ability to automatically correct errors. Landmarks are placed over the “ceiling” and photographed by a camera on the robot with its optical axis vertical to the ceiling. Through image segmentation, contour extracting, characteristic curves matching and landmark features identifying, the landmark is located, followed by analyzing the pieces of information about coordinates of the landmark and the deflective angle, with which to compute the robot’s current absolute position and heading angle. This scheme has experimentally demonstrated its effectiveness for robot indoor navigation.
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Hamburger, Kai, and Florian Röser. "The Role of Landmark Modality and Familiarity in Human Wayfinding." Swiss Journal of Psychology 73, no. 4 (January 2014): 205–13. http://dx.doi.org/10.1024/1421-0185/a000139.
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What characteristics constitute a “helpful” landmark for wayfinding and how are they represented in the human brain? Experiment 1 compared recognition and wayfinding performance for visual, verbal, and acoustic landmarks (animals) learned in our virtual environment SQUARELAND. Experiment 2 investigated landmark semantics, namely, famous versus unfamiliar buildings. The results showed that, first, the best recognition performance was observed for words (verbal condition) followed by sounds. Performance was worst for the pictorial landmark information. In the wayfinding phase, a similar level of performance was observed for all three modalities. Second, famous buildings were better recognized than unfamiliar ones, indicating a semantic influence. We conclude that nonvisual information may successfully constitute a landmark and discuss this within the context of current research on landmarks and human wayfinding.
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Kostaki, Maria, Argiro Vatakis, and Stavroula Samartzi. "Assisted spatial navigation: new directions." Homo Virtualis 2, no. 1 (March 27, 2019): 21. http://dx.doi.org/10.12681/homvir.20190.
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Blockchain technology brings new possibilities in assisted spatial navigation. Decentralized map building enables collaboration between users around the world, while providing researchers with a common reference map for extending the capabilities of navigational systems towards more intuitive and accurate landmark navigation assistance. Research on landmark navigation has been mainly focused on the visual characteristics of landmarks. Human behavior, however, has systematically been shown to be enhanced in the presence of multisensory unified events. We propose, therefore, the enhancement of spatial assisted navigation by utilizing landmarks that are multisensory and semantically congruent. Further, our research will provide insights in terms of the auditory parameters that could be combined with a given visual landmark, so as to facilitate landmark retrieval algorithms and user satisfaction during assisted spatial navigation.
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Zhu, Jiasong, Qing Li, Rui Cao, Ke Sun, Tao Liu, Jonathan M. Garibaldi, Qingquan Li, Bozhi Liu, and Guoping Qiu. "Indoor Topological Localization Using a Visual Landmark Sequence." Remote Sensing 11, no. 1 (January 3, 2019): 73. http://dx.doi.org/10.3390/rs11010073.
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This paper presents a novel indoor topological localization method based on mobile phone videos. Conventional methods suffer from indoor dynamic environmental changes and scene ambiguity. The proposed Visual Landmark Sequence-based Indoor Localization (VLSIL) method is capable of addressing problems by taking steady indoor objects as landmarks. Unlike many feature or appearance matching-based localization methods, our method utilizes highly abstracted landmark sematic information to represent locations and thus is invariant to illumination changes, temporal variations, and occlusions. We match consistently detected landmarks against the topological map based on the occurrence order in the videos. The proposed approach contains two components: a convolutional neural network (CNN)-based landmark detector and a topological matching algorithm. The proposed detector is capable of reliably and accurately detecting landmarks. The other part is the matching algorithm built on the second order hidden Markov model and it can successfully handle the environmental ambiguity by fusing sematic and connectivity information of landmarks. To evaluate the method, we conduct extensive experiments on the real world dataset collected in two indoor environments, and the results show that our deep neural network-based indoor landmark detector accurately detects all landmarks and is expected to be utilized in similar environments without retraining and that VLSIL can effectively localize indoor landmarks.
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Floreskul, Volodymyr, Konstantin Tretyakov, and Marlon Dumas. "Memory-Efficient Fast Shortest Path Estimation in Large Social Networks." Proceedings of the International AAAI Conference on Web and Social Media 8, no. 1 (May 16, 2014): 91–100. http://dx.doi.org/10.1609/icwsm.v8i1.14532.
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As the sizes of contemporary social networks surpass billions of users, so grows the need for fast graph algorithms to analyze them. A particularly important basic operation is the computation of shortest paths between nodes. Classical exact algorithms for this problem are prohibitively slow on large graphs, which motivates the development of approximate methods. Of those, landmark-based methods have been actively studied in recent years. Landmark-based estimation methods start by picking a fixed set of landmark nodes, precomputing the distance from each node in the graph to each landmark, and storing the precomputed distances in a data structure. Prior work has shown that the number of landmarks required to achieve a given level of precision grows with the size of the graph. Simultaneously, the size of the data structure is proportional to the product of the size of the graph and the number of landmarks. In this work we propose an alternative landmark-based distance estimation approach that substantially reduces space requirements by means of pruning: computing distances from each node to only a small subset of the closest landmarks. We evaluate our method on the DBLP, Orkut, Twitter and Skype social networks and demonstrate that the resulting estimation algorithms are comparable in query time and potentially superior in approximation quality to equivalent non-pruned landmark-based methods, while requiring less memory or disk space.
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Scioletti, Massimo, Dino Scioletti, Andrea Ferrara, Salvatore Dettori, Dario Stefani, Roberto Carboni, Rosalba Floris, Ruggero D’Anastasio, and Joan Viciano. "Correlations Among New Dental and Cranial Measurements." Dental Anthropology Journal 29, no. 1 (August 25, 2018): 3–15. http://dx.doi.org/10.26575/daj.v29i1.31.
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Cranial and dental anthropometry is commonly used in many areas of research, e.g., in forensicanthropology and paleoanthropology. We propose new craniometric and dental landmarks and distancesthat may have important applications in physical anthropology. Furthermore, a classical anthropometricalapproach was applied to quantify the correlation between dental and cranial measurements,which were taken on 30 Middle Ages adult crania from Sardinia (Italy).Principal components analysis was performed to explore the correlations among inter-landmark distances.The first component showed correlations between the cranial base and maxillary inter-landmarkdistances (the ‘cranial base’ system). The second component exclusively demonstrated correlationsamong maxillary and dental inter-landmark distances (the ‘oral cavity’ system). The third componentshowed positive correlations between the zygomatic and midline maxillary inter-landmark distances,and high negative loadings that include the bilateral styloid process and midline maxillary landmarks(the ‘upper cranium’ system).The inter-landmark dental distances correlate with inter-landmark cranial distances that have notbeen described previously. These data can be applied in other research and clinical areas.
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Xu, Shuqing, Haiyin Zhou, Jiongqi Wang, Zhangming He, and Dayi Wang. "SINS/Landmark Integrated Navigation Based on Landmark Attitude Determination." Sensors 19, no. 13 (July 1, 2019): 2917. http://dx.doi.org/10.3390/s19132917.
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Based on the situation that the traditional SINS (strapdown inertial navigation system)/CNS (celestial navigation system) integrated navigation system fails to realize all-day and all-weather navigation, this paper proposes a SINS/Landmark integrated navigation method based on landmark attitude determination to solve this problem. This integrated navigation system takes SINS as the basic scheme and uses landmark navigation to correct the error of SINS. The way of the attitude determination is to use the landmark information photographed by the landmark camera to complete feature matching. The principle of the landmark navigation and the process of attitude determination are discussed, and the feasibility of landmark attitude determination is analyzed, including the orthogonality of the attitude transform matrix, as well as the influences of the factors such as quantity and geometric position of landmarks. On this basis, the paper constructs the equations of the SINS/Landmark integrated navigation system, testifies the effectiveness of landmark attitude determination on the integrated navigation by Kalman filter, and improves the navigation precision of the system.
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Vallespin, Glenn, Renalyn Torralba, Daniljun Sanchez, Jashin Rosal, and Chennie Solania. "Chiropteran Composition and Morphometric Analysis of Ptenochirus Jagori in Caraga State University, Caraga Region, Philippines." Southeastern Philippines Journal of Research and Development 26, no. 1 (March 31, 2021): 49–62. http://dx.doi.org/10.53899/spjrd.v26i1.124.
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Due to potential and present ecological alteration in roosting sites and food source areas in neighboring vicinity of Caraga State University in Caraga Region, Philippines, unsettled progression of bats are documented through wing variation analysis and fluctuating asymmetry (FA). Twenty-one (21) collected samples of Ptenochirus jagori (Greater Musky Fruit Bat) yields asymmetry of 90.6396%, affecting landmarks of the elbow (landmark 1), carpals (landmark 2), metacarpals (landmark 3, 4, and 10), and phalanges’ fingers (landmarks 5, 6, 11, and 12). Wing variation (landmark-based) analysis suggested significant skewness on both elbows and metacarpals of wings. Wider shape deformation is on the rightwing, and a narrower one was analyzed on the left. Nonetheless, even though similar alteration is present between both wings, Canonical Variation Analysis (CVA) suggests no significant difference in the deformations of histogram analysis.
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Lee, Dong-Hyuk, Hyungpil Moon, and Hyouk Ryeol Choi. "Landmark detection methods for in-pipe robot traveling in urban gas pipelines." Robotica 34, no. 3 (July 9, 2014): 601–18. http://dx.doi.org/10.1017/s0263574714001726.
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SUMMARYElbows and branches in pipelines produce unique image patterns, which can be used as landmarks for autonomous navigation inside the pipelines. This paper presents two landmark detection methods, known as shadow-based method and laser projection method. The first method uses the landmark's unique patterns of shadow produced by the robot's illuminator. The other method exploits special line features generated by its own line-laser beam projector. The basic algorithms for extracting the landmarks are given and special sensor mechanisms are addressed respectively. Finally, the detection performances of each method are validated in various pipeline conditions by using an in-pipe robot, called MRINSPECT-V.
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Gupta, S., G. H. Smith, E. A. Wakelin, T. Van Der Veen, C. Plaskos, and J. W. Pierrepont. "AUTOMATED LANDMARK DETECTION IN FUNCTIONAL LATERAL RADIOGRAPHS USING DEEP LEARNING." Orthopaedic Proceedings 105-B, SUPP_3 (February 2023): 70. http://dx.doi.org/10.1302/1358-992x.2023.3.070.
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Evaluation of patient specific spinopelvic mobility requires the detection of bony landmarks in lateral functional radiographs. Current manual landmarking methods are inefficient, and subjective. This study proposes a deep learning model to automate landmark detection and derivation of spinopelvic measurements (SPM).A deep learning model was developed using an international multicenter imaging database of 26,109 landmarked preoperative, and postoperative, lateral functional radiographs (HREC: Bellberry: 2020-08-764-A-2). Three functional positions were analysed: 1) standing, 2) contralateral step-up and 3) flexed seated. Landmarks were manually captured and independently verified by qualified engineers during pre-operative planning with additional assistance of 3D computed tomography derived landmarks. Pelvic tilt (PT), sacral slope (SS), and lumbar lordotic angle (LLA) were derived from the predicted landmark coordinates. Interobserver variability was explored in a pilot study, consisting of 9 qualified engineers, annotating three functional images, while blinded to additional 3D information. The dataset was subdivided into 70:20:10 for training, validation, and testing.The model produced a mean absolute error (MAE), for PT, SS, and LLA of 1.7°±3.1°, 3.4°±3.8°, 4.9°±4.5°, respectively. PT MAE values were dependent on functional position: standing 1.2°±1.3°, step 1.7°±4.0°, and seated 2.4°±3.3°, p< 0.001. The mean model prediction time was 0.7 seconds per image. The interobserver 95% confidence interval (CI) for engineer measured PT, SS and LLA (1.9°, 1.9°, 3.1°, respectively) was comparable to the MAE values generated by the model.The model MAE reported comparable performance to the gold standard when blinded to additional 3D information. LLA prediction produced the lowest SPM accuracy potentially due to error propagation from the SS and L1 landmarks. Reduced PT accuracy in step and seated functional positions may be attributed to an increased occlusion of the pubic-symphysis landmark. Our model shows excellent performance when compared against the current gold standard manual annotation process.
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Mohd Shah, Hairol Nizam, Zalina Kamis, Azhar Ahmad, Mohd Rizuan Baharon, Muhd Akmal Noor Rajikon, and Kang Hui Hwa. "Vision Based Position Control for Vertical Take-off and Landing (VTOL) Using One Singular Landmark." Modern Applied Science 13, no. 9 (August 22, 2019): 33. http://dx.doi.org/10.5539/mas.v13n9p33.
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This project presents a vision based position control for Vertical Take-off and Landing (VTOL) to recognise a singular landmark for landing and take-off. Position control can provide safe flight and an accurate navigation. The circle landmark which used is an artificial landmark at known locations in an environment. Initially, a camera mounted on VTOL facing downward detecting landmarks in environments. A single circle used as landmark and VTOL will be control the position to reach the landmark. The images from the down-looking camera provided vision data to estimates position of VTOL from landmark. A mathematical method based on projective geometry using to locate VTOL on desired landmark from projected point in capture image. By compute the x-y coordinates of the VTOL with respect to landmark, height of camera above landmark will be obtained. VTOL can localize itself in known environment with pose estimation from landmark. The graphic user interface system (GUI) generate by MATLAB software is used to communicate with VTOL to control the VTOL position
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Tanikawa, Chihiro, Masakazu Yagi, and Kenji Takada. "Automated Cephalometry: System Performance Reliability Using Landmark-Dependent Criteria." Angle Orthodontist 79, no. 6 (November 1, 2009): 1037–46. http://dx.doi.org/10.2319/092908-508r.1.
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Abstract Objective: The purpose of the present study was to evaluate reliability of a system that performs automatic recognition of anatomic landmarks and adjacent structures on lateral cephalograms using landmark-dependent criteria unique to each landmark. Materials and Methods: To evaluate the reliability of the system, the system was used to examine 65 lateral cephalograms. The area of each system-identified anatomic structure surrounding the landmark and the position of each system-identified landmark were compared with norms using confidence ellipses with α = .01, which were derived from the scattergrams of 100 estimates obtained according to the method reported by Baumrind and Frantz. When the system-identified area overlapped with the norm area, anatomic structure recognition was considered successful. In addition, when the system-identified point was located within the norm area, landmark identification was considered successful. Based on these judgment criteria, success rates were calculated for all landmarks. Results: The system successfully identified all specified anatomic structures in all the images and determined the positions of the landmarks with a mean success rate of 88% (range, 77%– 100%). Conclusion: With the incorporation of the rational assessment criteria provided by confidence ellipses, the proposed system was confirmed to be reliable.
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Park, Joorok, Sheldon Baumrind, Sean Curry, Sean K. Carlson, Robert L. Boyd, and Heesoo Oh. "Reliability of 3D dental and skeletal landmarks on CBCT images." Angle Orthodontist 89, no. 5 (March 18, 2019): 758–67. http://dx.doi.org/10.2319/082018-612.1.
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ABSTRACT Objectives: To quantify reliability of three-dimensional skeletal landmarks and a comprehensive set of dental landmarks in cone-beam computed tomography (CBCT) and to determine the shapes of envelope of error. Materials and Methods: Three judges located 31 skeletal landmarks and 60 dental landmarks on the pre- and posttreatment CBCT images of 22 patients. Landmark error was determined by calculating the distance of deviation of landmark locations around their average. Standard deviation and mean radial spherical error were calculated. Scatterplots were constructed to characterize envelope of error. Results: The midline landmarks of the cranial base were highly reliable. Bilateral skeletal landmarks tended to have larger error than midline landmarks. Among the nonconventional landmarks, fronto-zygomatic suture, condyle, and mental foramen showed relatively high reliability. However, foramen spinosum and temporal fossa showed larger errors. Gonion was the least reliable landmark. Most dental landmarks were located more reliably than skeletal landmarks. The highest reliability was found at incisal edges. Mesiobuccal cusp of first molars also showed high reliability. Conclusions: There were differences in the size and shape of the distributions of errors of different landmarks. Most landmarks showed elongated envelopes. Bilateral structures tended to show greater errors than midline structures. Most dental landmarks were more reliable than skeletal landmarks.
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Shi, Yue, Pavel Serdyukov, Alan Hanjalic, and Martha Larson. "Personalized Landmark Recommendation Based on Geotags from Photo Sharing Sites." Proceedings of the International AAAI Conference on Web and Social Media 5, no. 1 (August 3, 2021): 622–25. http://dx.doi.org/10.1609/icwsm.v5i1.14152.
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Geotagged photos of users on social media sites provide abundant location-based data, which can be exploited for various location-based services, such as travel recommendation. In this paper, we propose a novel approach to a new application, i.e., personalized landmark recommendation based on users’ geotagged photos. We formulate the landmark recommendation task as a collaborative filtering problem, for which we propose a category-regularized matrix factorization approach that integrates both user-landmark preference and category-based landmark similarity. We collected geotagged photos from Flickr and landmark categories from Wikipedia for our experiments. Our experimental results demonstrate that the proposed approach outperforms popularity-based landmark recommendation and a basic matrix factorization approach in recommending personalized landmarks that are less visited by the population as a whole.
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Kim, Hyeon-Woo, Hyung-Joon Kim, Seungmin Rho, and Eenjun Hwang. "Augmented EMTCNN: A Fast and Accurate Facial Landmark Detection Network." Applied Sciences 10, no. 7 (March 26, 2020): 2253. http://dx.doi.org/10.3390/app10072253.
Full textAbstract:
Facial landmarks represent prominent feature points on the face that can be used as anchor points in many face-related tasks. So far, a lot of research has been done with the aim of achieving efficient extraction of landmarks from facial images. Employing a large number of feature points for landmark detection and tracking usually requires excessive processing time. On the contrary, relying on too few feature points cannot accurately represent diverse landmark properties, such as shape. To extract the 68 most popular facial landmark points efficiently, in our previous study, we proposed a model called EMTCNN that extended the multi-task cascaded convolutional neural network for real-time face landmark detection. To improve the detection accuracy, in this study, we augment the EMTCNN model by using two convolution techniques—dilated convolution and CoordConv. The former makes it possible to increase the filter size without a significant increase in computation time. The latter enables the spatial coordinate information of landmarks to be reflected in the model. We demonstrate that our model can improve the detection accuracy while maintaining the processing speed.
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Brief, Jakob, Jan H. Behle, Angelika Stellzig-Eisenhauer, and Stefan Hassfeld. "Precision of Landmark Positioning on Digitized Models from Patients with Cleft Lip and Palate." Cleft Palate-Craniofacial Journal 43, no. 2 (March 2006): 168–73. http://dx.doi.org/10.1597/04-106.1.
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Objective To quantify the precision of landmark positioning on digitized casts of patients with unilateral cleft lip and palate. Patients Forty plaster models of newborns up to 8 months of age were selected from the archive of the Department of Orthodontics of the University of Heidelberg. Material and Method The plaster-cast models were digitized with a Micromeasure 70 three-dimensional laser scanner (Micromeasure, Bischoffen, Germany). The laser scanner used in this study operates with a precision of 0.15 mm on the x- and y-axes and 0.06 mm on the z-axis. In the intraobserver study, a single observer placed anatomical landmarks in four rounds, with at least 4 weeks between each round. In the interobserver study, four different observers each placed the same landmarks once. For the two different studies, an ideal location for each landmark was calculated by averaging the landmark positions of the four rounds or observers. The distance between each of the four landmark positions and the ideal landmark was measured. Results A 95% confidence interval for the landmark positioning error was calculated. For the intraobserver investigation, this error was 0.34 to 1.30 mm, and for the interobserver investigation it was 0.7 to 2.00 mm. Conclusion Because both investigations displayed comparable error intervals, it was concluded that different observers could perform landmark positioning for the same studies.