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Journal articles on the topic 'Pose variations'

Author: Grafiati

Published: 4 May 2024

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1

Du, Shan, and Rabab Ward. "Face recognition under pose variations." Journal of the Franklin Institute 343, no. 6 (2006): 596–613. http://dx.doi.org/10.1016/j.jfranklin.2006.08.006.

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Benjamin Dias, M., and Bernard F. Buxton. "Separating shape and pose variations." Image and Vision Computing 22, no. 10 (2004): 851–61. http://dx.doi.org/10.1016/j.imavis.2004.02.002.

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Palese, Marcella. "Variations by generalized symmetries of local Noether strong currents equivalent to global canonical Noether currents." Communications in Mathematics 24, no. 2 (2016): 125–35. http://dx.doi.org/10.1515/cm-2016-0009.

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Abstract We will pose the inverse problem question within the Krupka variational sequence framework. In particular, the interplay of inverse problems with symmetry and invariance properties will be exploited considering that the cohomology class of the variational Lie derivative of an equivalence class of forms, closed in the variational sequence, is trivial. We will focalize on the case of symmetries of globally defined field equations which are only locally variational and prove that variations of local Noether strong currents are variationally equivalent to global canonical Noether currents

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CHEN, SHAOKANG, BRIAN C. LOVELL, and TING SHAN. "ROBUST ADAPTED PRINCIPAL COMPONENT ANALYSIS FOR FACE RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 23, no. 03 (2009): 491–520. http://dx.doi.org/10.1142/s0218001409007284.

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Recognizing faces with uncontrolled pose, illumination, and expression is a challenging task due to the fact that features insensitive to one variation may be highly sensitive to the other variations. Existing techniques dealing with just one of these variations are very often unable to cope with the other variations. The problem is even more difficult in applications where only one gallery image per person is available. In this paper, we describe a recognition method, Adapted Principal Component Analysis (APCA), that can simultaneously deal with large variations in both illumination and facia

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Osuna, Isaac Aaron Rodriguez, Pablo Cobelli, and Nahuel Olaiz. "Bubble Formation in Pulsed Electric Field Technology May Pose Limitations." Micromachines 13, no. 8 (2022): 1234. http://dx.doi.org/10.3390/mi13081234.

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Currently, increasing amounts of pulsed electric fields (PEF) are employed to improve a person’s life quality. This technology is based on the application of the shortest high voltage electrical pulse, which generates an increment over the cell membrane permeability. When applying these pulses, an unwanted effect is electrolysis, which could alter the treatment. This work focused on the study of the local variations of the electric field and current density around the bubbles formed by the electrolysis of water by PEF technology and how these variations alter the electroporation protocol. The

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Shanmuganathan, M., and T. Nalini. "Face Recognition using Nearest Neighbour and Nearest Mean Classification Framework : Empirical Analysis, Conclusions and Future Directions." Journal of Physics: Conference Series 2251, no. 1 (2022): 012010. http://dx.doi.org/10.1088/1742-6596/2251/1/012010.

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Abstract Human Face recognition algorithms have made huge progress in the last decade. In this manuscript, we have presented an approach for the implementation of a face recognition system in a successful manner by varying pose, scale, lighting, and age variation. The different empirical analysis was performed with various datasets for face detection and face identification. Face identification system detects efficiently segments and recognizes face in a cluttered sequence under varying pose, lighting and age variations. From this experimental analysis morphological model outperformed k-NNC, N

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Et. al., K. Suma,. "Dense Feature Based Face Recognition from Surveillance Video using Convolutional Neural Network." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 1436–49. http://dx.doi.org/10.17762/turcomat.v12i5.2040.

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Face Recognition is a field of identifying the person from the facial features and has wide application range in security, human computer interactions, finance etc. In recent years, many researchers have developed different algorithms to identify the Faces from various illumination variations and Pose variation, but these two problems remain unsolved in Face Recognition (FR) field. The Local Binary Pattern (LBP) has already proved its robustness in illumination variation. This paper proposes a four-patch Local Binary Pattern based FR utilizing Convolutional Neural Network (CNN) for ident

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HU, Yuan, Jingqi YAN, Wei LI, and Pengfei SHI. "3D Face Landmarking Method under Pose and Expression Variations." IEICE Transactions on Information and Systems E94-D, no. 3 (2011): 729–33. http://dx.doi.org/10.1587/transinf.e94.d.729.

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Drira, Hassen, Boulbaba Ben Amor, A. Srivastava, M. Daoudi, and R. Slama. "3D Face Recognition under Expressions, Occlusions, and Pose Variations." IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 9 (2013): 2270–83. http://dx.doi.org/10.1109/tpami.2013.48.

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Zhou, Shaohua Kevin, and Rama Chellappa. "Image-based face recognition under illumination and pose variations." Journal of the Optical Society of America A 22, no. 2 (2005): 217. http://dx.doi.org/10.1364/josaa.22.000217.

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Baddar, Wissam J., and Yong Man Ro. "Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3215–23. http://dx.doi.org/10.1609/aaai.v33i01.33013215.

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Spatio-temporal feature encoding is essential for encoding the dynamics in video sequences. Recurrent neural networks, particularly long short-term memory (LSTM) units, have been popular as an efficient tool for encoding spatio-temporal features in sequences. In this work, we investigate the effect of mode variations on the encoded spatio-temporal features using LSTMs. We show that the LSTM retains information related to the mode variation in the sequence, which is irrelevant to the task at hand (e.g. classification facial expressions). Actually, the LSTM forget mechanism is not robust enough

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Ye, Yingsheng, Xingming Zhang, and Wing W. Y. Ng. "Color Distribution Pattern Metric for Person Reidentification." Wireless Communications and Mobile Computing 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4089505.

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Accompanying the growth of surveillance infrastructures, surveillance IP cameras mount up rapidly, crowding Internet of Things (IoT) with countless surveillance frames and increasing the need of person reidentification (Re-ID) in video searching for surveillance and forensic fields. In real scenarios, performance of current proposed Re-ID methods suffers from pose and viewpoint variations due to feature extraction containing background pixels and fixed feature selection strategy for pose and viewpoint variations. To deal with pose and viewpoint variations, we propose the color distribution pat

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Li, Deshi, and Xiaoliang Wang. "An Analytical Measuring Rectification Algorithm of Monocular Systems in Dynamic Environment." Journal of Sensors 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/4132721.

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Range estimation is crucial for maintaining a safe distance, in particular for vision navigation and localization. Monocular autonomous vehicles are appropriate for outdoor environment due to their mobility and operability. However, accurate range estimation using vision system is challenging because of the nonholonomic dynamics and susceptibility of vehicles. In this paper, a measuring rectification algorithm for range estimation under shaking conditions is designed. The proposed method focuses on how to estimate range using monocular vision when a shake occurs and the algorithm only requires

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Gunawan, Alexander Agung Santoso, and Reza A. Prasetyo. "Face Recognition Performance in Facing Pose Variation." CommIT (Communication and Information Technology) Journal 11, no. 1 (2017): 1. http://dx.doi.org/10.21512/commit.v11i1.1847.

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There are many real world applications of face recognition which require good performance in uncontrolled environments such as social networking, and environment surveillance. However, many researches of face recognition are done in controlled situations. Compared to the controlled environments, face recognition in uncontrolled environments comprise more variation, for example in the pose, light intensity, and expression. Therefore, face recognition in uncontrolled conditions is more challenging than in controlled settings. In thisresearch, we would like to discuss handling pose variations in

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Zhang, Zhenduo, Yongru Chen, Wenming Yang, Guijin Wang, and Qingmin Liao. "Pose-Invariant Face Recognition via Adaptive Angular Distillation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 3 (2022): 3390–98. http://dx.doi.org/10.1609/aaai.v36i3.20249.

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Pose-invariant face recognition is a practically useful but challenging task. This paper introduces a novel method to learn pose-invariant feature representation without normalizing profile faces to frontal ones or learning disentangled features. We first design a novel strategy to learn pose-invariant feature embeddings by distilling the angular knowledge of frontal faces extracted by teacher network to student network, which enables the handling of faces with large pose variations. In this way, the features of faces across variant poses can cluster compactly for the same person to create a p

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Prędota, Stanisław. "Over Vlaams-Nederlandse woordenboeken." Werkwinkel 9, no. 1 (2014): 91–105. http://dx.doi.org/10.2478/werk-2014-0006.

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Abstract The contemporary Dutch language belongs to European multi-centered languages and has three variations: Dutch of the Kingdom of the Netherlands, Dutch in Northern Belgium, and Dutch in Surinam. There are differences among the above variations which mainly regard the pronunciation and lexicon. The Flemish and Surinam variations pose a great challenge, especially for the translators of the Flemish and Surinam literature. Similarly, they pose also a significant theoretical and practical problem for the authors of one and two-language dictionaries of the Dutch language. The contemporary le

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ABAYOMI-ALLI, A., E. O. OMIDIORA, S. O. OLABIYISI, J. A. Ojo, and A. Y. AKINGBOYE. "BLACKFACE SURVEILLANCE CAMERA DATABASE FOR EVALUATING FACE RECOGNITION IN LOW QUALITY SCENARIOS." Journal of Natural Sciences Engineering and Technology 15, no. 2 (2017): 13–31. http://dx.doi.org/10.51406/jnset.v15i2.1668.

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Many face recognition algorithms perform poorly in real life surveillance scenarios because they were tested with datasets that are already biased with high quality images and certain ethnic or racial types. In this paper a black face surveillance camera (BFSC) database was described, which was collected from four low quality cameras and a professional camera. There were fifty (50) random volunteers and 2,850 images were collected for the frontal mugshot, surveillance (visible light), surveillance (IR night vision), and pose variations datasets, respectively. Images were taken at distance 3.4,

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Champagne, Zachary M., Robert Schoen, and Claire M. Riddell. "Variations in Both-Addends-Unknown Problems." Teaching Children Mathematics 21, no. 2 (2014): 114–21. http://dx.doi.org/10.5951/teacchilmath.21.2.0114.

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Early elementary school students are expected to solve twelve distinct types of word problems. A math researcher and two teachers pose a structure for thinking about one problem type that has not been studied as closely as the other eleven.

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Wang, Wen-Yao, Hong-Qing Cai, Si-Yuan Qu, et al. "Genomic Variation-Mediating Fluconazole Resistance in Yeast." Biomolecules 12, no. 6 (2022): 845. http://dx.doi.org/10.3390/biom12060845.

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Fungal infections pose a serious and growing threat to public health. These infections can be treated with antifungal drugs by killing hazardous fungi in the body. However, the resistance can develop over time when fungi are exposed to antifungal drugs by generating genomic variations, including mutation, aneuploidy, and loss of heterozygosity. The variations could reduce the binding affinity of a drug to its target or block the pathway through which drugs exert their activity. Here, we review genomic variation-mediating fluconazole resistance in the yeast Candida, with the hope of highlightin

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Mudunuri, Sivaram Prasad, and Soma Biswas. "Low Resolution Face Recognition Across Variations in Pose and Illumination." IEEE Transactions on Pattern Analysis and Machine Intelligence 38, no. 5 (2016): 1034–40. http://dx.doi.org/10.1109/tpami.2015.2469282.

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Wang, Chao, Yongping Li, and Xubo Song. "Video-to-video face authentication system robust to pose variations." Expert Systems with Applications 40, no. 2 (2013): 722–35. http://dx.doi.org/10.1016/j.eswa.2012.08.009.

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22

Ekundayo, Jamiu M., Reza Rezaee, and Chunyan Fan. "Measurement of gas contents in shale reservoirs – impact of gas density and implications for gas resource estimates." APPEA Journal 61, no. 2 (2021): 606. http://dx.doi.org/10.1071/aj20177.

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Gas shale reservoirs pose unique measurement challenges due to their ultra-low petrophysical properties and complicated pore structures. A small variation in an experimental parameter, under high-pressure conditions, may result in huge discrepancies in gas contents and the resource estimates derived from such data. This study illustrates the impact of the equation of state on the gas content determined for a shale sample. The gas content was determined from laboratory-measured high-pressure methane adsorption isotherms and theoretically described by a hybrid type model. The modelling involved

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Zhang, Hua, Li Jia Wang, Zhen Jie Wang, and Wei Yi Yuan. "View-Invariant Face Detection for Colorful Image." Advanced Materials Research 945-949 (June 2014): 1880–84. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.1880.

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To overcome illumination changes and pose variations, a pose-invariant face detection method is presented. First, an illumination compensation method based on reference white is presented to overcome the lighting variations. The reference white is obtained according to the component Y from YCbCr color space. Then, a mixture face model is constructed by the Cb and Cr from YCbCr color space and H from the HSV color space to extract faces from colorful image. At last, an eyes model is designed to locate eyes in the obtained face images, which can distinguish face from neck and arms ultimately. Th

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Wen, Xiaoyu, Juxiang Zhou, Jianhou Gan, and Sen Luo. "A discriminative multiscale feature extraction network for facial expression recognition in the wild." Measurement Science and Technology 35, no. 4 (2024): 045005. http://dx.doi.org/10.1088/1361-6501/ad191c.

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Abstract Driven by advancements in deep learning technologies, substantial progress has been achieved in the field of facial expression recognition over the past decade, while challenges remain brought about by occlusions, pose variations and subtle expression differences in unconstrained (wild) scenarios. Therefore, a novel multiscale feature extraction method is proposed in this paper, that leverages convolutional neural networks to simultaneously extract deep semantic features and shallow geometric features. Through the mechanism of channel-wise self-attention, prominent features are furthe

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Zhao, Gaopeng, Sixiong Xu, and Yuming Bo. "LiDAR-Based Non-Cooperative Tumbling Spacecraft Pose Tracking by Fusing Depth Maps and Point Clouds." Sensors 18, no. 10 (2018): 3432. http://dx.doi.org/10.3390/s18103432.

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How to determine the relative pose between the chaser spacecraft and the high-speed tumbling target spacecraft at close range, which is an essential step in space proximity missions, is very challenging. This paper proposes a LiDAR-based pose tracking method by fusing depth maps and point clouds. The key point is to estimate the roll angle variation in adjacent sensor data by using the line detection and matching in depth maps. The simplification of adaptive voxelized grid point cloud based on the real-time relative position is adapted in order to satisfy the real-time requirement in the appro

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Akhtar, Zahid, Ajita Rattani, and Gian Luca Foresti. "Temporal Analysis Of Adaptive Face Recognition." Journal of Artificial Intelligence and Soft Computing Research 4, no. 4 (2014): 243–55. http://dx.doi.org/10.1515/jaiscr-2015-0012.

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Abstract Aging has profound effects on facial biometrics as it causes change in shape and texture. However, aging remains an under-studied problem in comparison to facial variations due to pose, illumination and expression changes. A commonly adopted solution in the state-of-the-art is the virtual template synthesis for aging and de-aging transformations involving complex 3D modelling techniques. These methods are also prone to estimation errors in the synthesis. Another viable solution is to continuously adapt the template to the temporal variation (ageing) of the query data. Though efficacy

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Yu, Yang, Shaoting Zhang, Fei Yang, and Dimitris Metaxas. "Multi-Pose and Occluded Facial Landmark Localization Via Sparse Shape Representation." International Journal on Artificial Intelligence Tools 24, no. 04 (2015): 1540019. http://dx.doi.org/10.1142/s0218213015400199.

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Automatic facial landmark localization is a challenging problem for real world images because of face pose variations and occlusions. This paper proposes a unified framework to robustly locate facial landmarks under different poses and occlusions. Instead of explicitly modeling the statistical point distribution, we use a sparse linear combination to approximate the observed shape, and hence alleviate the multi-pose problem. In addition, we use the sparsity constraint to handle outliers caused by occlusions. We also model the initial misalignment and use convex optimization techniques to solve

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Liang, Xiao, Masahiro Hirano, and Yuji Yamakawa. "Real-Time Marker-Based Tracking and Pose Estimation for a Rotating Object Using High-Speed Vision." Journal of Robotics and Mechatronics 34, no. 5 (2022): 1063–72. http://dx.doi.org/10.20965/jrm.2022.p1063.

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Object tracking and pose estimation have always been challenging tasks in robotics, particularly for rotating objects. Rotating objects move quickly and with complex pose variations. In this study, we introduce a marker-based tracking and pose estimation method for rotating objects using a high-speed vision system. The method can obtain pose information at frequencies greater than 500 Hz, and can still estimate the pose when parts of the markers are lost during tracking. A robot catching experiment shows that the accuracy and frequency of this system are capable of high-speed tracking tasks.

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Alrjebi, Mustafa M., Wanquan Liu, and ng Li. "Face recognition against pose variations using multi-resolution multiple colour fusion." International Journal of Machine Intelligence and Sensory Signal Processing 1, no. 4 (2016): 304. http://dx.doi.org/10.1504/ijmissp.2016.085269.

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Alrjebi, Mustafa M., Wanquan Liu, and Ling Li. "Face recognition against pose variations using multi-resolution multiple colour fusion." International Journal of Machine Intelligence and Sensory Signal Processing 1, no. 4 (2016): 304. http://dx.doi.org/10.1504/ijmissp.2016.10006096.

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Tai, Ying, Jian Yang, Yigong Zhang, Lei Luo, Jianjun Qian, and Yu Chen. "Face Recognition With Pose Variations and Misalignment via Orthogonal Procrustes Regression." IEEE Transactions on Image Processing 25, no. 6 (2016): 2673–83. http://dx.doi.org/10.1109/tip.2016.2551362.

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Jo, Jaeik, Heeseung Choi, Ig-Jae Kim, and Jaihie Kim. "Single-view-based 3D facial reconstruction method robust against pose variations." Pattern Recognition 48, no. 1 (2015): 73–85. http://dx.doi.org/10.1016/j.patcog.2014.07.013.

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Choi, Sang-Il, Chong-Ho Choi, and Nojun Kwak. "Face recognition based on 2D images under illumination and pose variations." Pattern Recognition Letters 32, no. 4 (2011): 561–71. http://dx.doi.org/10.1016/j.patrec.2010.11.021.

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Naser, Omer Abdulhaleem, Sharifah Mumtazah Syed Ahmad, Khairulmizam Samsudin, and Marsyita Hanafi. "Investigating the Impact of Yaw Pose Variation on Facial Recognition Performance." Advances in Artificial Intelligence and Machine Learning 03, no. 02 (2023): 1039–55. http://dx.doi.org/10.54364/aaiml.2023.1162.

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Facial recognition systems often struggle with detecting faces in poses that deviate from the frontal view. Therefore, this paper investigates the impact of variations in yaw poses on the accuracy of facial recognition systems and presents a robust approach optimized to detect faces with pose variations ranging from 0◦ to ±90◦ . The proposed system integrates MTCNN, FaceNet, and SVC, and is trained and evaluated on the Taiwan dataset, which includes face images with diverse yaw poses. The training dataset consists of 89 subjects, with approximately 70 images per subject, and the testing datase

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Zhang, La, Haiyun Guo, Kuan Zhu, et al. "Hybrid Modality Metric Learning for Visible-Infrared Person Re-Identification." ACM Transactions on Multimedia Computing, Communications, and Applications 18, no. 1s (2022): 1–15. http://dx.doi.org/10.1145/3473341.

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Visible-infrared person re-identification (Re-ID) has received increasing research attention for its great practical value in night-time surveillance scenarios. Due to the large variations in person pose, viewpoint, and occlusion in the same modality, as well as the domain gap brought by heterogeneous modality, this hybrid modality person matching task is quite challenging. Different from the metric learning methods for visible person re-ID, which only pose similarity constraints on class level, an efficient metric learning approach for visible-infrared person Re-ID should take both the class-

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Beham, M. Parisa, S. M. Mansoor Roomi, J. Alageshan, and V. Kapileshwaran. "Performance Analysis of Pose Invariant Face Recognition Approaches in Unconstrained Environments." International Journal of Computer Vision and Image Processing 5, no. 1 (2015): 66–81. http://dx.doi.org/10.4018/ijcvip.2015010104.

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Face recognition and authentication are two significant and dynamic research issues in computer vision applications. There are many factors that should be accounted for face recognition; among them pose variation is a major challenge which severely influence in the performance of face recognition. In order to improve the performance, several research methods have been developed to perform the face recognition process with pose invariant conditions in constrained and unconstrained environments. In this paper, the authors analyzed the performance of a popular texture descriptors viz., Local Bina

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Zulkarnain, Syavira Tiara, and Nanik Suciati. "Selective local binary pattern with convolutional neural network for facial expression recognition." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (2022): 6724. http://dx.doi.org/10.11591/ijece.v12i6.pp6724-6735.

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<span lang="EN-US">Variation in images in terms of head pose and illumination is a challenge in facial expression recognition. This research presents a hybrid approach that combines the conventional and deep learning, to improve facial expression recognition performance and aims to solve the challenge. We propose a selective local binary pattern (SLBP) method to obtain a more stable image representation fed to the learning process in convolutional neural network (CNN). In the preprocessing stage, we use adaptive gamma transformation to reduce illumination variability. The proposed SLBP s

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Lee, Jae-Hyeon, and Chang-Hwan Son. "Trap-Based Pest Counting: Multiscale and Deformable Attention CenterNet Integrating Internal LR and HR Joint Feature Learning." Remote Sensing 15, no. 15 (2023): 3810. http://dx.doi.org/10.3390/rs15153810.

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Pest counting, which predicts the number of pests in the early stage, is very important because it enables rapid pest control, reduces damage to crops, and improves productivity. In recent years, light traps have been increasingly used to lure and photograph pests for pest counting. However, pest images have a wide range of variability in pest appearance owing to severe occlusion, wide pose variation, and even scale variation. This makes pest counting more challenging. To address these issues, this study proposes a new pest counting model referred to as multiscale and deformable attention Cent

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Saghafi, Mohammadali, Aini Hussain, Mohamad Hanif Md. Saad, Mohd Asyraf Zulkifley, Nooritawati Md Tahir, and Mohd Faisal Ibrahim. "Pose and Illumination Invariance of Attribute Detectors in Person Re-identification." International Journal of Engineering & Technology 7, no. 4.11 (2018): 174. http://dx.doi.org/10.14419/ijet.v7i4.11.20796.

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The use of attributes in person re-identification and video surveillance applications has grabbed attentions of many researchers in recent times. Attributes are suitable tools for mid-level representation of a part or a region in an image as it is more similar to human perception as compared to the quantitative nature of the normal visual features description of those parts. Hence, in this paper, the preliminary experimental results to evaluate the robustness of attribute detectors against pose and light variations in contrast to the use of local appearance features is discussed. Results attai

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Chen, Si, Dong Yan, and Yan Yan. "Directional Correlation Filter Bank for Robust Head Pose Estimation and Face Recognition." Mathematical Problems in Engineering 2018 (October 21, 2018): 1–10. http://dx.doi.org/10.1155/2018/1923063.

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During the past few decades, face recognition has been an active research area in pattern recognition and computer vision due to its wide range of applications. However, one of the most challenging problems encountered by face recognition is the difficulty of handling large head pose variations. Therefore, the efficient and effective head pose estimation is a critical step of face recognition. In this paper, a novel feature extraction framework, called Directional Correlation Filter Bank (DCFB), is presented for head pose estimation. Specifically, in the proposed framework, the 1-Dimensional O

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Hajraoui, Abdellatif, and Mohamed Sabri. "Generic and Robust Method for Head Pose Estimation." Indonesian Journal of Electrical Engineering and Computer Science 4, no. 2 (2016): 439. http://dx.doi.org/10.11591/ijeecs.v4.i2.pp439-446.

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Head pose estimation has fascinated the research community due to its application in facial motion capture, human-computer interaction and video conferencing. It is a pre-requisite to gaze tracking, face recognition, and facial expression analysis. In this paper, we present a generic and robust method for model-based global 2D head pose estimation from single RGB Image. In our approach we use of the one part the Gabor filters to conceive a robust pose descriptor to illumination and facial expression variations, and that target the pose information. Moreover, we ensure the classification of the

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Kour, Sukhbir, Ashish Choudhary, Azhar Malik, and Rudra Kaul. "Non surgical retreatment three rooted maxillary premolars: A case report." IP Indian Journal of Conservative and Endodontics 7, no. 2 (2022): 98–102. http://dx.doi.org/10.18231/j.ijce.2022.021.

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Effective and successful endodontic treatment requires dentists to have adequate information on the clinical variations in root canal anatomy. Maxillary premolars exhibit anatomical variations in the numbers of roots and canals, which pose a challenge during root canal therapy these variations must be considered for successful endodontic therapy. Herein, we illustrate the diagnosis and clinical management of previously endodontically treated three rooted maxillary premolars using Cone Beam Computed Tomography (CBCT).

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Clemente, Carolina, Gonçalo Chambel, Diogo C. F. Silva, António Mesquita Montes, Joana F. Pinto, and Hugo Plácido da Silva. "Feasibility of 3D Body Tracking from Monocular 2D Video Feeds in Musculoskeletal Telerehabilitation." Sensors 24, no. 1 (2023): 206. http://dx.doi.org/10.3390/s24010206.

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Musculoskeletal conditions affect millions of people globally; however, conventional treatments pose challenges concerning price, accessibility, and convenience. Many telerehabilitation solutions offer an engaging alternative but rely on complex hardware for body tracking. This work explores the feasibility of a model for 3D Human Pose Estimation (HPE) from monocular 2D videos (MediaPipe Pose) in a physiotherapy context, by comparing its performance to ground truth measurements. MediaPipe Pose was investigated in eight exercises typically performed in musculoskeletal physiotherapy sessions, wh

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Ewaisha, Mahmoud, Marwa El Shawarby, Hazem Abbas, and Ibrahim Sobh. "End-to-End Multitask Learning for Driver Gaze and Head Pose Estimation." Electronic Imaging 2020, no. 16 (2020): 110–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.16.avm-108.

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Modern automobiles accidents occur mostly due to inattentive behavior of drivers, which is why driver’s gaze estimation is becoming a critical component in automotive industry. Gaze estimation has introduced many challenges due to the nature of the surrounding environment like changes in illumination, or driver’s head motion, partial face occlusion, or wearing eye decorations. Previous work conducted in this field includes explicit extraction of hand-crafted features such as eye corners and pupil center to be used to estimate gaze, or appearance-based methods like Convolutional Neural Networks

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Sang, Gaoli, Jing Li, and Qijun Zhao. "Pose-Invariant Face Recognition via RGB-D Images." Computational Intelligence and Neuroscience 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/3563758.

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Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity est

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Tu, Huan, Gesang Duoji, Qijun Zhao, and Shuang Wu. "Improved Single Sample Per Person Face Recognition via Enriching Intra-Variation and Invariant Features." Applied Sciences 10, no. 2 (2020): 601. http://dx.doi.org/10.3390/app10020601.

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Face recognition using a single sample per person is a challenging problem in computer vision. In this scenario, due to the lack of training samples, it is difficult to distinguish between inter-class variations caused by identity and intra-class variations caused by external factors such as illumination, pose, etc. To address this problem, we propose a scheme to improve the recognition rate by both generating additional samples to enrich the intra-variation and eliminating external factors to extract invariant features. Firstly, a 3D face modeling module is proposed to recover the intrinsic p

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Zeng, Junying. "An Improved Sparse Representation Face Recognition Algorithm for Variations of Illumination and Pose." Journal of Information and Computational Science 12, no. 16 (2015): 5987–94. http://dx.doi.org/10.12733/jics20106876.

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Casasent, David. "Face recognition with pose and illumination variations using new SVRDM support-vector machine." Optical Engineering 43, no. 8 (2004): 1804. http://dx.doi.org/10.1117/1.1763935.

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Passalis, G., P. Perakis, T. Theoharis, and I. A. Kakadiaris. "Using Facial Symmetry to Handle Pose Variations in Real-World 3D Face Recognition." IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 10 (2011): 1938–51. http://dx.doi.org/10.1109/tpami.2011.49.

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., Ganapatikrishna P. Hegde. "REAL TIME VOTING SYSTEM USING FACE RECOGNITION FOR DIFFERENT EXPRESSIONS AND POSE VARIATIONS." International Journal of Research in Engineering and Technology 03, no. 07 (2014): 381–84. http://dx.doi.org/10.15623/ijret.2014.0307065.

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