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Journal articles on the topic 'Outdoor scene analysis'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Ruan, Ling, Ling Zhang, Yi Long, and Fei Cheng. "Coordinate references for the indoor/outdoor seamless positioning." Proceedings of the ICA 1 (May 16, 2018): 1–7. http://dx.doi.org/10.5194/ica-proc-1-97-2018.

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Indoor positioning technologies are being developed rapidly, and seamless positioning which connected indoor and outdoor space is a new trend. The indoor and outdoor positioning are not applying the same coordinate system and different indoor positioning scenes uses different indoor local coordinate reference systems. A specific and unified coordinate reference frame is needed as the space basis and premise in seamless positioning application. Trajectory analysis of indoor and outdoor integration also requires a uniform coordinate reference. However, the coordinate reference frame in seamless

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Kilawati, Andi, and Rosmalah Yanti. "Hubungan Outdor Activity dengan Scene Setting dalam Skill Mengajar Pembelajaran IPA Mahasiswa PGSD Universitas Cokroaminoto Palopo." Cokroaminoto Journal of Primary Education 2, no. 1 (2019): 6–10. http://dx.doi.org/10.30605/cjpe.122019.100.

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This study generally aims to determine the relationship of outdoor activity with Scene Settings in Elementary School Science Learning PGSD University Students Cokroaminoto Palopo. This research is a quantitative research. The research model used in this study is the correlational model. This research hypothesis was tested using two-way analysis of variance (ANAVA). The sample of this study was PGSD University Cokroaminoto Palopo University. The results of this study indicate that: (1) there is a positive relationship between outdoor activities and scene settings (2) there is a positive positiv

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Musel, Benoit, Louise Kauffmann, Stephen Ramanoël, et al. "Coarse-to-fine Categorization of Visual Scenes in Scene-selective Cortex." Journal of Cognitive Neuroscience 26, no. 10 (2014): 2287–97. http://dx.doi.org/10.1162/jocn_a_00643.

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Neurophysiological, behavioral, and computational data indicate that visual analysis may start with the parallel extraction of different elementary attributes at different spatial frequencies and follows a predominantly coarse-to-fine (CtF) processing sequence (low spatial frequencies [LSF] are extracted first, followed by high spatial frequencies [HSF]). Evidence for CtF processing within scene-selective cortical regions is, however, still lacking. In the present fMRI study, we tested whether such processing occurs in three scene-selective cortical regions: the parahippocampal place area (PPA

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CHAN, K. L. "VIDEO-BASED GAIT ANALYSIS BY SILHOUETTE CHAMFER DISTANCE AND KALMAN FILTER." International Journal of Image and Graphics 08, no. 03 (2008): 383–418. http://dx.doi.org/10.1142/s0219467808003155.

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A markerless human gait analysis system using uncalibrated monocular video is developed. The background model is trained for extracting the subject silhouette, whether in static scene or dynamic scene, in each video frame. Generic 3D human model is manually fit to the subject silhouette in the first video frame. We propose the silhouette chamfer, which contains the chamfer distance of silhouette and region information, as one matching feature. This, combined dynamically with the model gradient, is used to search for the best fit between subject silhouette and 3D model. Finally, we use the disc

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Tylecek, Radim, and Robert Fisher. "Consistent Semantic Annotation of Outdoor Datasets via 2D/3D Label Transfer." Sensors 18, no. 7 (2018): 2249. http://dx.doi.org/10.3390/s18072249.

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The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data however typically requires much manual annotation of semantic regions in the data, delivered by substantial human labour. To speed up this process, we propose a framework for semantic annotation of scenes captured by moving camera(s), e.g., mounted on a vehicle or robot. It makes use of an available 3D model of the traversed scene to project segmente

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Bielecki, Andrzej, and Piotr Śmigielski. "Three-Dimensional Outdoor Analysis of Single Synthetic Building Structures by an Unmanned Flying Agent Using Monocular Vision." Sensors 21, no. 21 (2021): 7270. http://dx.doi.org/10.3390/s21217270.

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An algorithm designed for analysis and understanding a 3D urban-type environment by an autonomous flying agent, equipped only with a monocular vision, is presented. The algorithm is hierarchical and is based on the structural representation of the analyzed scene. Firstly, the robot observes the scene from a high altitude to build a 2D representation of a single object and a graph representation of the 2D scene. The 3D representation of each object arises as a consequence of the robot’s actions, as a result of which it projects the object’s solid on different planes. The robot assigns the obtai

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Kuhnert, Lars, and Klaus-Dieter Kuhnert. "Sensor-Fusion Based Real-Time 3D Outdoor Scene Reconstruction and Analysis on a Moving Mobile Outdoor Robot." KI - Künstliche Intelligenz 25, no. 2 (2011): 117–23. http://dx.doi.org/10.1007/s13218-011-0093-z.

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SAKODA, Keishi, and Yamada ICHIRO. "Acoustic scene analysis of spatial and temporal distribution of sound arrival direction and frequency spectra." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 270, no. 1 (2024): 10075–79. http://dx.doi.org/10.3397/in_2024_4386.

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In the outdoor monitoring of aircraft noise, not only the target aircraft sounds to be monitored arrive, but also various environmental sounds also arrive at the monitoring site, and the sound situation changes from moment to moment. The authors have studied and reported on a method to classify environmental sound sources and to evaluate the influence of environmental sounds on aircraft sound monitoring by analyzing the spatial-temporal distribution of sound arrival direction and sound level of various environmental sounds at the monitoring site as a sound scene. This paper will make a report

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Shi, Lei. "Unveiling the Impact of Air Pollution on Outdoor Training for Endurance and Explosive Power." International Journal of Ambient Computing and Intelligence 15, no. 1 (2025): 1–19. https://doi.org/10.4018/ijaci.386085.

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In recent years, air pollution impacts athletes during outdoor training, especially in endurance and explosive-power training. This paper uses the boundary image inverse optimization algorithm and dynamic scene three-dimensional analysis model to study this impact. First, it briefly introduces the algorithms' application in sports training and existing research. Then, by combining dynamic scene classification technology, it quantifies the training process and proposes an improved boundary image inverse optimization algorithm. Finally, it uses the 3D analysis model to classify the training proc

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He, Wei. "Research on Outdoor Garden Scene Reconstruction Based on PMVS Algorithm." Scientific Programming 2021 (November 24, 2021): 1–10. http://dx.doi.org/10.1155/2021/4491382.

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The three-dimensional reconstruction of outdoor landscape is of great significance for the construction of digital city. With the rapid development of big data and Internet of things technology, when using the traditional image-based 3D reconstruction method to restore the 3D information of objects in the image, there will be a large number of redundant points in the point cloud and the density of the point cloud is insufficient. Based on the analysis of the existing three-dimensional reconstruction technology, combined with the characteristics of outdoor garden scene, this paper gives the det

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Oo, Thanda, Hiroshi Kawasaki, Yutaka Ohsawa, and Katsushi Ikeuchi. "Separation of Reflection and Transparency Based on Spatiotemporal Analysis for Outdoor Scene." IPSJ Digital Courier 2 (2006): 428–40. http://dx.doi.org/10.2197/ipsjdc.2.428.

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Angsuwatanakul, Thanate, Jamie O’Reilly, Kajornvut Ounjai, Boonserm Kaewkamnerdpong, and Keiji Iramina. "Multiscale Entropy as a New Feature for EEG and fNIRS Analysis." Entropy 22, no. 2 (2020): 189. http://dx.doi.org/10.3390/e22020189.

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The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrate the potential of this multimodality approach since memory is a highly complex neurocognitive process, and the mechanisms governing selective retention of memories are not fully understood by other approaches. In this study, 15 healthy participants with normal colour vision participated in the visu

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Silva, Nelson, Pedro J. S. Cardoso, and João M. F. Rodrigues. "Multimodal Sentiment Classifier Framework for Different Scene Contexts." Applied Sciences 14, no. 16 (2024): 7065. http://dx.doi.org/10.3390/app14167065.

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Sentiment analysis (SA) is an effective method for determining public opinion. Social media posts have been the subject of much research, due to the platforms’ enormous and diversified user bases that regularly share thoughts on nearly any subject. However, on posts composed by a text–image pair, the written description may or may not convey the same sentiment as the image. The present study uses machine learning models for the automatic sentiment evaluation of pairs of text and image(s). The sentiments derived from the image and text are evaluated independently and merged (or not) to form the

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Gupta, Niharika, and Priya Khobragade. "Muti-class Image Classification using Transfer Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 1 (2023): 700–704. http://dx.doi.org/10.22214/ijraset.2023.48665.

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Abstract: Humans are very proficient at perceiving natural scenes and understanding their contents. Everyday image content across the globe is rapidly increasing and there is a need for classifying these images for further research. Scene classification is a challenging task, because in some natural scenes there will be common features in images and some images may contain half indoor and half outdoor scene features. In this project we are going to classify natural scenery in images using Artificial Intelligence. Based on the analysis of the error backpropagation algorithm, we propose an innov

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Wijayathunga, Liyana, Alexander Rassau, and Douglas Chai. "Challengesand Solutions for Autonomous Ground Robot Scene Understanding and Navigation in Unstructured Outdoor Environments: A Review." Applied Sciences 13, no. 17 (2023): 9877. http://dx.doi.org/10.3390/app13179877.

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The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively high levels of autonomy. In more unstructured environments, however, the development of fully autonomous mobile robots remains challenging due to the complexity of understanding these environments. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. More recent learning-based methods may replace the

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Gong, Liang, Xiangyu Yu, and Jingchuan Wang. "Curve-Localizability-SVM Active Localization Research for Mobile Robots in Outdoor Environments." Applied Sciences 11, no. 10 (2021): 4362. http://dx.doi.org/10.3390/app11104362.

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Working environment of mobile robots has gradually expanded from indoor structured scenes to outdoor scenes such as wild areas in recent years. The expansion of application scene, change of sensors and the diversity of working tasks bring greater challenges and higher demands to active localization for mobile robots. The efficiency and stability of traditional localization strategies in wild environments are significantly reduced. On the basis of considering features of the environment and the robot motion curved surface, this paper proposes a curve-localizability-SVM active localization algor

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Rodriguez, Leonardo Barriga, Hugo Jimenez Hernandez, Jorge Alberto Soto Cajiga, et al. "A Linear Criterion to sort Color Components in Images." Ingeniería e Investigación 37, no. 1 (2017): 91. http://dx.doi.org/10.15446/ing.investig.v37n1.55444.

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The color and its representation play a basic role in Image Analysis process. Several methods can be beneficial whenever they have a correct representation of wave-length variations used to represent scenes with a camera. A wide variety of spaces and color representations is founded in specialized literature. Each one is useful in concrete circumstances and others may offer redundant color information (for instance, all RGB components are high correlated). This work deals with the task of identifying and sorting which component from several color representations offers the majority of informat

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Weinmann, M., M. S. Müller, M. Hillemann, N. Reydel, S. Hinz, and B. Jutzi. "POINT CLOUD ANALYSIS FOR UAV-BORNE LASER SCANNING WITH HORIZONTALLY AND VERTICALLY ORIENTED LINE SCANNERS – CONCEPT AND FIRST RESULTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 24, 2017): 399–406. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-399-2017.

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In this paper, we focus on UAV-borne laser scanning with the objective of densely sampling object surfaces in the local surrounding of the UAV. In this regard, using a line scanner which scans along the vertical direction and perpendicular to the flight direction results in a point cloud with low point density if the UAV moves fast. Using a line scanner which scans along the horizontal direction only delivers data corresponding to the altitude of the UAV and thus a low scene coverage. For these reasons, we present a concept and a system for UAV-borne laser scanning using multiple line scanners

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Ning, Xiaojuan, Yishu Ma, Yuanyuan Hou, et al. "Trunk-Constrained and Tree Structure Analysis Method for Individual Tree Extraction from Scanned Outdoor Scenes." Remote Sensing 15, no. 6 (2023): 1567. http://dx.doi.org/10.3390/rs15061567.

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The automatic extraction of individual tree from mobile laser scanning (MLS) scenes has important applications in tree growth monitoring, tree parameter calculation and tree modeling. However, trees often grow in rows and tree crowns overlap with varying shapes, and there is also incompleteness caused by occlusion, which makes individual tree extraction a challenging problem. In this paper, we propose a trunk-constrained and tree structure analysis method to extract trees from scanned urban scenes. Firstly, multi-feature enhancement is performed via PointNet to segment the tree points from raw

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Huo, Xin, Hong Chen, YuHao Ma, and Qing Wang. "Design and realization of relic augmented reality system of integration positioning and posture sensing technology." MATEC Web of Conferences 246 (2018): 03014. http://dx.doi.org/10.1051/matecconf/201824603014.

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On the purpose of presenting the old appearance of the relics through digitalization, and overlapping the virtual scenes with the actual scenes at the relic site, in this paper, we introduced the positioning technology, posture sensing technology and system development technology, put forward constructing cultural relic tourism platform based on integration positioning and posture sensing technology, we conducted detailed research and analysis on the users’ experienced process of cultural tourism, designed a relic augmented reality system of integration positioning and posture sensing technolo

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Okutani, Keita, Takami Yoshida, Keisuke Nakamura, and Kazuhiro Nakadai. "Incremental Noise Estimation in Outdoor Auditory Scene Analysis using a Quadrocopter with a Microphone Array." Journal of the Robotics Society of Japan 31, no. 7 (2013): 676–83. http://dx.doi.org/10.7210/jrsj.31.676.

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Cheng, Yayun, Fei Hu, Hongfei Wu, Peng Fu, and Yan Hu. "Multi-polarization passive millimeter-wave imager and outdoor scene imaging analysis for remote sensing applications." Optics Express 26, no. 16 (2018): 20145. http://dx.doi.org/10.1364/oe.26.020145.

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Liu, Wei, Yue Yang, and Longsheng Wei. "Weather Recognition of Street Scene Based on Sparse Deep Neural Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 3 (2017): 403–8. http://dx.doi.org/10.20965/jaciii.2017.p0403.

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Recognizing different weather conditions is a core component of many different applications of outdoor video analysis and computer vision. Street analysis performance, including detecting street objects, detecting road lines, recognizing street sign and etc., varies greatly with weather, so modeling based on weather recognition is the key resolution in this field. Features derived from intrinsic properties of different weather conditions contribute to successful classification. We first propose using deep learning features from convolutional neural networks (CNN) for fine recognition. In order

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Reina, Giulio, Mauro Bellone, Luigi Spedicato, and Nicola Ivan Giannoccaro. "3D traversability awareness for rough terrain mobile robots." Sensor Review 34, no. 2 (2014): 220–32. http://dx.doi.org/10.1108/sr-03-2013-644.

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Purpose – This research aims to address the issue of safe navigation for autonomous vehicles in highly challenging outdoor environments. Indeed, robust navigation of autonomous mobile robots over long distances requires advanced perception means for terrain traversability assessment. Design/methodology/approach – The use of visual systems may represent an efficient solution. This paper discusses recent findings in terrain traversability analysis from RGB-D images. In this context, the concept of point as described only by its Cartesian coordinates is reinterpreted in terms of local description

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Weinmann, M., J. Leitloff, L. Hoegner, B. Jutzi, U. Stilla, and S. Hinz. "Thermal 3D mapping for object detection in dynamic scenes." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-1 (November 7, 2014): 53–60. http://dx.doi.org/10.5194/isprsannals-ii-1-53-2014.

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The automatic analysis of 3D point clouds has become a crucial task in photogrammetry, remote sensing and computer vision. Whereas modern range cameras simultaneously provide both range and intensity images with high frame rates, other devices can be used to obtain further information which could be quite valuable for tasks such as object detection or scene interpretation. In particular thermal information offers many advantages, since people can easily be detected as heat sources in typical indoor or outdoor environments and, furthermore, a variety of concealed objects such as heating pipes a

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Wu, Hui-Yin, Florent Robert, Théo Fafet, et al. "Designing Guided User Tasks in VR Embodied Experiences." Proceedings of the ACM on Human-Computer Interaction 6, EICS (2022): 1–24. http://dx.doi.org/10.1145/3532208.

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Virtual reality (VR) offers extraordinary opportunities in user behavior research to study and observe how people interact in immersive 3D environments. A major challenge of designing these 3D experiences and user tasks, however, lies in bridging the inter-relational gaps of perception between the designer, the user, and the 3D scene. Paul Dourish identified three gaps of perception: ontology between the scene representation and the user and designer interpretation, intersubjectivity of task communication between designer and user, and intentionality between the user's intentions and designer'

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Ning, Xiaojuan, Yishu Ma, Yuanyuan Hou, Zhiyong Lv, Haiyan Jin, and Yinghui Wang. "Semantic Segmentation Guided Coarse-to-Fine Detection of Individual Trees from MLS Point Clouds Based on Treetop Points Extraction and Radius Expansion." Remote Sensing 14, no. 19 (2022): 4926. http://dx.doi.org/10.3390/rs14194926.

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Urban trees are vital elements of outdoor scenes via mobile laser scanning (MLS), accurate individual trees detection from disordered, discrete, and high-density MLS is an important basis for the subsequent analysis of city management and planning. However, trees cannot be easily extracted because of the occlusion with other objects in urban scenes. In this work, we propose a coarse-to-fine individual trees detection method from MLS point cloud data (PCD) based on treetop points extraction and radius expansion. Firstly, an improved semantic segmentation deep network based on PointNet is applie

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B Suba Shri and Keerthi S. "A Study About Blood in Soil and Its Interactions." World Journal of Biology Pharmacy and Health Sciences 22, no. 1 (2025): 477–81. https://doi.org/10.30574/wjbphs.2025.22.1.0407.

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This study investigates the interaction of blood with three soil types roadside soil, construction soil, and red soil under varying environmental conditions: cold, indoor (room temperature), and outdoor exposure. Using phenolphthalein reagent for blood decomposition and pH paper for chemical analysis, observations were made over ten days. Results show significant variations in pH levels and blood decomposition rates depending on soil type and environment. This research offers valuable insights for forensic science, particularly in crime scene reconstruction and estimation of bloodstain age.

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Ramya, C., S. Subha Rani, and G. Kayalvizhi. "Image Inpainting Based on Fast Inpainting and Sparse Representation Method." Advanced Materials Research 984-985 (July 2014): 1350–56. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.1350.

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Especially there is a wide interest in handling the outdoor surveillance images in autonomous navigation, remote surveillance, automatic incident detection, vision based driver assistant system and law enforcement services. In each case, there is an underlying object or scene which is wished to be captured, processed, analyzed and interpreted. Live recording and transmission of outdoor surveillance images are often one of a forensic tool but while transmission it may introduce some variations in the pixels and it may visible as missing blocks. Thus it is significant to improve the visual quali

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Kim, Myeong-Hun, Su-Mi Han, and Hwan Kim. "A Phenomenological Study on the Exposing Experience and Overcoming of Repeated Fatal Accidents of Fire-fighting Officers on Outdoor Service." Fire Science and Engineering 35, no. 4 (2021): 97–106. http://dx.doi.org/10.7731/kifse.b7253918.

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The core purpose of this study is to provide useful information for educational and psychological programs for outdoor fire-fighters by comprehensive analysis of their repeated experience in exposure to fatal accidents and overcoming them. To this end, eight outdoor fire officials in charge of rescue and emergency affairs were selected as subjects of the study at a fire Station in Cheonan and conducted in-depth interviews. Subsequently, interview data were analyzed through Giorgi's phenomenological analysis method and 10 essential themes were derived as followings; the sorriness and regret of

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Wang, Fei, Yan Zhuang, Hong Gu, and Huosheng Hu. "OctreeNet: A Novel Sparse 3-D Convolutional Neural Network for Real-Time 3-D Outdoor Scene Analysis." IEEE Transactions on Automation Science and Engineering 17, no. 2 (2020): 735–47. http://dx.doi.org/10.1109/tase.2019.2942068.

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SZABO, Mihaela, Adelina DUMITRAS, Diana-Maria MIRCEA, Adriana F. SESTRAS, and Robert F. BRZUSZEK. "Analysis of compositional lines in natural landscapes." Nova Geodesia 2, no. 2 (2022): 29. http://dx.doi.org/10.55779/ng2229.

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Nature was and remains an eternal companion of man, but at the same time, it is also a constant enigma. Man’s connection with nature is ancestral, and the need for this connection is constantly proven. Landscape design is the field where art (human creation) and nature meet, creating a field of endless possibilities in the development of outdoor spaces, but while the artistic side of the field is constantly improved and developed, sometimes the exploration of the natural side is left behind. The present study aims to identify and analyse the types of compositional lines that can be found in na

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Huang, Yuanyuan, Guyue Lu, Wei Zhao, Xinyao Zhang, Jiawen Jiang, and Qiang Xing. "FlyDetector—Automated Monitoring Platform for the Visual–Motor Coordination of Honeybees in a Dynamic Obstacle Scene Using Digital Paradigm." Sensors 23, no. 16 (2023): 7073. http://dx.doi.org/10.3390/s23167073.

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Vision plays a crucial role in the ability of compound-eyed insects to perceive the characteristics of their surroundings. Compound-eyed insects (such as the honeybee) can change the optical flow input of the visual system by autonomously controlling their behavior, and this is referred to as visual–motor coordination (VMC). To analyze an insect’s VMC mechanism in dynamic scenes, we developed a platform for studying insects that actively shape the optic flow of visual stimuli by adapting their flight behavior. Image-processing technology was applied to detect the posture and direction of insec

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Bhadoria, Ajeeta Singh, and Vandana Vikas Thakre. "Improved Single Haze Removal using Weighted Filter and Gaussian-Laplacian." International Journal of Electrical and Electronics Research 8, no. 2 (2020): 26–31. http://dx.doi.org/10.37391/ijeer.080201.

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Generally computer applications use digital images. Digital image plays a vital role in the analysis and explanation of data, which is in the digital form. Images and videos of outside scenes are generally affected by the bad weather environment such as haze, fog, mist etc. It will result in bad visibility of the scene caused by the lack of quality. This paper exhibits a study about various image defogging techniques to eject the haze from the fog images caught in true world to recuperate a fast and enhanced nature of fog free images. In this paper, we propose a simple but effective the weight

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Chebi, Hocine, Hind Tabet-Derraz, Rafik Sayah, et al. "Intelligence and Adaptive Global Algorithm Detection of Crowd Behavior." International Journal of Computer Vision and Image Processing 10, no. 1 (2020): 24–41. http://dx.doi.org/10.4018/ijcvip.2020010102.

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The recognition and prediction of people's activities from videos are major concerns in the field of computer vision. The main objective of this article is to propose an adaptive global algorithm that analyzes human behavior from video. This problem is also called video content analysis or VCA. This analysis is performed in outdoor or indoor environments. The video scene can be depending on the number of people present, is characterized by the presence of only one person at a time in the video. We are interested in scenes containing a large number of people. This is called crowd scenes where w

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Manfredi, Giovanni, Israel D. Sáenz Hinostroza, Michel Menelle, Stéphane Saillant, Jean-Philippe Ovarlez, and Laetitia Thirion-Lefevre. "Measurements and Analysis of the Doppler Signature of a Human Moving within the Forest in UHF-Band." Remote Sensing 13, no. 3 (2021): 423. http://dx.doi.org/10.3390/rs13030423.

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Measurements of the Doppler signature in UHF-band of a human moving in outdoor sites are presented in this paper. A radar campaign has been carried out, observing a subject walking and running outside, near and within a forest. A bistatic radar has been employed working in continuous wave (CW) at 1 GHz and 435 MHz. The spectrograms acquired in VV polarization are shown and discussed. This study aims to prove the feasibility of detecting people moving in forested areas at low frequencies. Besides, we highlight the impact of the frequencies and the different sites on the Doppler spectrum of the

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Park, Byeongseon, Heekwon Lee, Yong-Kab Kim, and Sungkwan Youm. "Progressive Pruning of Light Dehaze Networks for Static Scenes." Applied Sciences 14, no. 23 (2024): 10820. http://dx.doi.org/10.3390/app142310820.

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This paper introduces an progressive pruning method for Light DeHaze Networks, focusing on a static scene captured by a fixed camera environments. We develop a progressive pruning algorithm that aims to reduce computational complexity while maintaining dehazing quality within a specified threshold. Our key contributions include a fine-tuning strategy for specific scenes, channel importance analysis, and an progressive pruning approach considering layer-wise sensitivity. Our experiments demonstrate the effectiveness of our progressive pruning method. Our progressive pruning algorithm, targeting

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Valme, Daniil, Anton Rassõlkin, and Dhanushka C. Liyanage. "From ADAS to Material-Informed Inspection: Review of Hyperspectral Imaging Applications on Mobile Ground Robots." Sensors 25, no. 8 (2025): 2346. https://doi.org/10.3390/s25082346.

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Hyperspectral imaging (HSI) has evolved from its origins in space missions to become a promising sensing technology for mobile ground robots, offering unique capabilities in material identification and scene understanding. This review examines the integration and applications of HSI systems in ground-based mobile platforms, with emphasis on outdoor implementations. The analysis covers recent developments in two main application domains: autonomous navigation and inspection tasks. In navigation, the review explores HSI applications in Advanced Driver Assistance Systems (ADAS) and off-road scena

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Fan, Lei, and Yuanzhi Cai. "An Efficient Filtering Approach for Removing Outdoor Point Cloud Data of Manhattan-World Buildings." Remote Sensing 13, no. 19 (2021): 3796. http://dx.doi.org/10.3390/rs13193796.

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Laser scanning is a popular means of acquiring the indoor scene data of buildings for a wide range of applications concerning indoor environment. During data acquisition, unwanted data points beyond the indoor space of interest can also be recorded due to the presence of openings, such as windows and doors on walls. For better visualization and further modeling, it is beneficial to filter out those data, which is often achieved manually in practice. To automate this process, an efficient image-based filtering approach was explored in this research. In this approach, a binary mask image was cre

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Emek Soylu, Busra, Mehmet Serdar Guzel, Gazi Erkan Bostanci, Fatih Ekinci, Tunc Asuroglu, and Koray Acici. "Deep-Learning-Based Approaches for Semantic Segmentation of Natural Scene Images: A Review." Electronics 12, no. 12 (2023): 2730. http://dx.doi.org/10.3390/electronics12122730.

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The task of semantic segmentation holds a fundamental position in the field of computer vision. Assigning a semantic label to each pixel in an image is a challenging task. In recent times, significant advancements have been achieved in the field of semantic segmentation through the application of Convolutional Neural Networks (CNN) techniques based on deep learning. This paper presents a comprehensive and structured analysis of approximately 150 methods of semantic segmentation based on CNN within the last decade. Moreover, it examines 15 well-known datasets in the semantic segmentation field.

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Che, E., and M. J. Olsen. "FAST EDGE DETECTION AND SEGMENTATION OF TERRESTRIAL LASER SCANS THROUGH NORMAL VARIATION ANALYSIS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W4 (September 12, 2017): 51–57. http://dx.doi.org/10.5194/isprs-annals-iv-2-w4-51-2017.

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Terrestrial Laser Scanning (TLS) utilizes light detection and ranging (lidar) to effectively and efficiently acquire point cloud data for a wide variety of applications. Segmentation is a common procedure of post-processing to group the point cloud into a number of clusters to simplify the data for the sequential modelling and analysis needed for most applications. This paper presents a novel method to rapidly segment TLS data based on edge detection and region growing. First, by computing the projected incidence angles and performing the normal variation analysis, the silhouette edges and int

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Chow, Tsz-Yeung, King-Hung Lee, and Kwok-Leung Chan. "Detection of Targets in Road Scene Images Enhanced Using Conditional GAN-Based Dehazing Model." Applied Sciences 13, no. 9 (2023): 5326. http://dx.doi.org/10.3390/app13095326.

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Object detection is a classic image processing problem. For instance, in autonomous driving applications, targets such as cars and pedestrians are detected in the road scene video. Many image-based object detection methods utilizing hand-crafted features have been proposed. Recently, more research has adopted a deep learning approach. Object detectors rely on useful features, such as the object’s boundary, which are extracted via analyzing the image pixels. However, the images captured, for instance, in an outdoor environment, may be degraded due to bad weather such as haze and fog. One possib

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Liu, Jiping, Yong Wang, Mengmeng Liu, Shenghua Xu, Tao Jiang, and Yang Gu. "The Integrated Disaster Reduction Intelligent Service System and its Application." Proceedings of the ICA 2 (July 10, 2019): 1–7. http://dx.doi.org/10.5194/ica-proc-2-76-2019.

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<p><strong>Abstract.</strong> Geo-spatial information technology can provide data resources, positioning benchmarks, basic framework and key technologies for disaster prevention and reduction. At present, there are some problems in China’s disaster reduction services. Too much focus is placed on decision-making but not on early warning. In addition, the integration of technology, system and application of disaster reduction services is not enough. There is still a lack of a unified understanding an integrated disaster reduction intelligent service system. In order to provide

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Nicholls, Victoria I., Benjamin Alsbury-Nealy, Alexandra Krugliak, and Alex Clarke. "Context effects on object recognition in real-world environments: A study protocol." Wellcome Open Research 7 (May 26, 2022): 165. http://dx.doi.org/10.12688/wellcomeopenres.17856.1.

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Background: The environments that we live in impact on our ability to recognise objects, with recognition being facilitated when objects appear in expected locations (congruent) compared to unexpected locations (incongruent). However, these findings are based on experiments where the object is isolated from its environment. Moreover, it is not clear which components of the recognition process are impacted by the environment. In this experiment, we seek to examine the impact real world environments have on object recognition. Specifically, we will use mobile electroencephalography (mEEG) and au

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Nicholls, Victoria I., Benjamin Alsbury-Nealy, Alexandra Krugliak, and Alex Clarke. "Context effects on object recognition in real-world environments: A study protocol." Wellcome Open Research 7 (November 30, 2022): 165. http://dx.doi.org/10.12688/wellcomeopenres.17856.2.

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Background: The environments that we live in impact on our ability to recognise objects, with recognition being facilitated when objects appear in expected locations (congruent) compared to unexpected locations (incongruent). However, these findings are based on experiments where the object is isolated from its environment. Moreover, it is not clear which components of the recognition process are impacted by the environment. In this experiment, we seek to examine the impact real world environments have on object recognition. Specifically, we will use mobile electroencephalography (mEEG) and au

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Nicholls, Victoria I., Benjamin Alsbury-Nealy, Alexandra Krugliak, and Alex Clarke. "Context effects on object recognition in real-world environments: A study protocol." Wellcome Open Research 7 (July 14, 2023): 165. http://dx.doi.org/10.12688/wellcomeopenres.17856.3.

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Background: The environments that we live in impact on our ability to recognise objects, with recognition being facilitated when objects appear in expected locations (congruent) compared to unexpected locations (incongruent). However, these findings are based on experiments where the object is isolated from its environment. Moreover, it is not clear which components of the recognition process are impacted by the environment. In this experiment, we seek to examine the impact real world environments have on object recognition. Specifically, we will use mobile electroencephalography (mEEG) and au

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Cao, Minghe, Jianzhong Wang, and Li Ming. "Multi-Templates Based Robust Tracking for Robot Person-Following Tasks." Applied Sciences 11, no. 18 (2021): 8698. http://dx.doi.org/10.3390/app11188698.

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While the robotics techniques have not developed to full automation, robot following is common and crucial in robotic applications to reduce the need for dedicated teleoperation. To achieve this task, the target must first be robustly and consistently perceived. In this paper, a robust visual tracking approach is proposed. The approach adopts a scene analysis module (SAM) to identify the real target and similar distractors, leveraging statistical characteristics of cross-correlation responses. Positive templates are collected based on the tracking confidence constructed by the SAM, and negativ

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Liu, Long, Huihui Wang, Haorui Li, et al. "Ambulatory Human Gait Phase Detection Using Wearable Inertial Sensors and Hidden Markov Model." Sensors 21, no. 4 (2021): 1347. http://dx.doi.org/10.3390/s21041347.

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Gait analysis, as a common inspection method for human gait, can provide a series of kinematics, dynamics and other parameters through instrumental measurement. In recent years, gait analysis has been gradually applied to the diagnosis of diseases, the evaluation of orthopedic surgery and rehabilitation progress, especially, gait phase abnormality can be used as a clinical diagnostic indicator of Alzheimer Disease and Parkinson Disease, which usually show varying degrees of gait phase abnormality. This research proposed an inertial sensor based gait analysis method. Smoothed and filtered angul

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Reddy, Etikala Raja Vikram, and Sushil Thale. "A Novel Efficient Dual-Gate Mixed Dilated Convolution Network for Multi-Scale Pedestrian Detection." Engineering, Technology & Applied Science Research 13, no. 6 (2023): 11973–79. http://dx.doi.org/10.48084/etasr.6340.

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With the increasing use of onboard high-speed computing systems, vehicle manufacturers are offering significant advanced features of driver assistance systems. Pedestrian detection is one of the major requirements of such systems, which commonly use cameras, radar, and ultrasonic sensors. Image recognition based on captured image streams is one of the powerful tools used for the detection of pedestrians, which exhibits similarities and distinguishing features compared to general object detection. Although pedestrian detection has advanced significantly along with deep learning, some issues sti

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Zhuchkov, Vitaly V., Dmitry A. Peterburgsky, and Evgeny N. Boldyrev. "Analytical assessment of fire tank and fire reservoir operating range." Fire and Emergencies: prevention, elimination 3 (2023): 39–47. http://dx.doi.org/10.25257/fe.2023.3.39-47.

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PURPOSE. Draft amendments and addendums to code 8.13130.2020 “Fire protection systems. Outdoor fire-fighting water supply. Fire safety requirements”, according to which it is proposed to increase working radius of fire tanks and fire reservoirs to 400 m are analyzed. Regulatory documents regarding outdoor fire-fighting water supply for the period from 1947 to the present are examined. The authors analyzed aspects related to determining operating range of a fire tank and an artificial fire reservoir, depending on the capabilities of fire departments and fire-fighting equipment. Such aspects inc

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