17.1.3.6 Walking, Gait Recognition, Gait Analysis

Human Walking in Virtual Environments: Perception, Technology, and Applications,
Springer2013. ISBN 978-1-4419-8431-9.
WWW Link. 1404
A survey of past and recent developments on human walking in virtual environments with an emphasis on human self-motion perception, the multisensory nature of experiences of walking, conceptual design approaches, current technologies, and applications. BibRef

Guan, Y.[Yu], Sun, Y.L.[Yun-Lian], Li, C.T.[Chang-Tsun], Tistarelli, M.,
Human gait identification from extremely low-quality videos: An enhanced classifier ensemble method,
IET-Bio(3), No. 2, June 2014, pp. 84-93.
DOI Link 1407
BibRef

Iwashita, Y.[Yumi], Ogawara, K.[Koichi], Kurazume, R.[Ryo],
Identification of people walking along curved trajectories,
PRL(48), No. 1, 2014, pp. 60-69.
Elsevier DOI 1410
BibRef
Earlier: A1, A3, A2:
Expanding gait identification methods from straight to curved trajectories,
WACV13(193-199).
IEEE DOI 1303
Gait BibRef

Lai, Z.H.[Zhi-Hui], Xu, Y.[Yong], Jin, Z.[Zhong], Zhang, D.,
Human Gait Recognition via Sparse Discriminant Projection Learning,
CirSysVideo(24), No. 10, October 2014, pp. 1651-1662.
IEEE DOI 1411
feature extraction BibRef

Ngo, T.T.[Trung Thanh], Makihara, Y.S.[Yasu-Shi], Nagahara, H.[Hajime], Mukaigawa, Y.[Yasuhiro], Yagi, Y.S.[Yasu-Shi],
Similar gait action recognition using an inertial sensor,
PR(48), No. 4, 2015, pp. 1289-1301.
Elsevier DOI 1502
BibRef
Earlier:
Inertial-sensor-based walking action recognition using robust step detection and inter-class relationships,
ICPR12(3811-3814).
WWW Link. 1302
Gait action recognition BibRef

Whytock, T.[Tenika], Belyaev, A.[Alexander], Robertson, N.M.[Neil M.],
On covariate factor detection and removal for robust gait recognition,
MVA(26), No. 5, July 2015, pp. 661-674.
WWW Link. 1506
BibRef

Guan, Y., Li, C., Roli, F.,
On Reducing the Effect of Covariate Factors in Gait Recognition: A Classifier Ensemble Method,
PAMI(37), No. 7, July 2015, pp. 1521-1528.
IEEE DOI 1506
Analytical models BibRef

Muramatsu, D., Makihara, Y., Yagi, Y.,
Cross-view gait recognition by fusion of multiple transformation consistency measures,
IET-Bio(4), No. 2, 2015, pp. 62-73.
DOI Link 1507
calibration BibRef

Muramatsu, D., Makihara, Y., Yagi, Y.,
View Transformation Model Incorporating Quality Measures for Cross-View Gait Recognition,
Cyber(46), No. 7, July 2016, pp. 1602-1615.
IEEE DOI 1606
Accuracy BibRef

Chattopadhyay, P.[Pratik], Sural, S.[Shamik], Mukherjee, J.[Jayanta],
Frontal gait recognition from occluded scenes,
PRL(63), No. 1, 2015, pp. 9-15.
Elsevier DOI 1508
BibRef
Earlier:
Exploiting Pose Information for Gait Recognition from Depth Streams,
CDC4CV14(341-355).
Springer DOI 1504
Frontal gait recognition
See also Information fusion from multiple cameras for gait-based re-identification and recognition. BibRef

Zhang, Y.T.[Yu-Ting], Pan, G.[Gang], Jia, K.[Kui], Lu, M.L.[Min-Long], Wang, Y.M.[Yue-Ming], Wu, Z.H.[Zhao-Hui],
Accelerometer-Based Gait Recognition by Sparse Representation of Signature Points With Clusters,
Cyber(45), No. 9, September 2015, pp. 1864-1875.
IEEE DOI 1509
accelerometers BibRef

Marín-Jiménez, M.J.[Manuel J.], Castro, F.M.[Francisco M.], Carmona-Poyato, Á.[Ángel], Guil, N.[Nicolás],
On how to improve tracklet-based gait recognition systems,
PRL(68, Part 1), No. 1, 2015, pp. 103-110.
Elsevier DOI 1512
Gait recognition BibRef

Castro, F.M.[Francisco M.], Delgado-Escaño, R.[Rubén], Hernández-García, R.[Ruber], Marín-Jiménez, M.J.[Manuel J.], Guil, N.[Nicolás],
AttenGait: Gait recognition with attention and rich modalities,
PR(148), 2024, pp. 110171.
Elsevier DOI Code:
WWW Link. 2402
Gait, Optical flow, Deep learning, Attention, Biometrics BibRef

Xing, X.L.[Xiang-Lei], Wang, K.[Kejun], Yan, T.[Tao], Lv, Z.W.[Zhuo-Wen],
Complete canonical correlation analysis with application to multi-view gait recognition,
PR(50), No. 1, 2016, pp. 107-117.
Elsevier DOI 1512
Canonical correlation analysis BibRef

Rida, I., Jiang, X., Marcialis, G.L.,
Human Body Part Selection by Group Lasso of Motion for Model-Free Gait Recognition,
SPLetters(23), No. 1, January 2016, pp. 154-158.
IEEE DOI 1601
Clothing BibRef

Guan, S., Gray, H.A., Keynejad, F., Pandy, M.G.,
Mobile Biplane X-Ray Imaging System for Measuring 3D Dynamic Joint Motion During Overground Gait,
MedImg(35), No. 1, January 2016, pp. 326-336.
IEEE DOI 1601
Bones BibRef

Shi, J.L.[Jin-Long], Sun, Z.X.[Zheng-Xing],
Large-scale three-dimensional measurement based on LED marker tracking,
VC(32), No. 2, February 2016, pp. 179-190.
WWW Link. 1602
BibRef

Nangtin, P.[Prasit], Kumhom, P.[Pinit], Chamnongthai, K.[Kosin],
Gait identification with partial occlusion using six modules and consideration of occluded module exclusion,
JVCIR(36), No. 1, 2016, pp. 107-121.
Elsevier DOI 1603
Gait identification BibRef

Sung, Y., Chung, W.,
Hierarchical Sample-Based Joint Probabilistic Data Association Filter for Following Human Legs Using a Mobile Robot in a Cluttered Environment,
HMS(46), No. 3, June 2016, pp. 340-349.
IEEE DOI 1605
Estimation BibRef

Lao, S.H.[Shi-Hong], Wang, D.[Dong], li, F.[Fu], Zhang, H.H.[Hai-Hong],
Human running detection: Benchmark and baseline,
CVIU(153), No. 1, 2016, pp. 143-150.
Elsevier DOI 1612
Running detection BibRef

Van Nguyen, L., La, H.M.,
Real-Time Human Foot Motion Localization Algorithm With Dynamic Speed,
HMS(46), No. 6, December 2016, pp. 822-833.
IEEE DOI 1612
Kalman filters BibRef

Ortells, J.[Javier], Mollineda, R.A.[Ramón A.], Mederos, B.[Boris], Martín-Félez, R.[Raúl],
Gait recognition from corrupted silhouettes: A robust statistical approach,
MVA(28), No. 1-2, February 2017, pp. 15-33.
Springer DOI 1702
BibRef

Balazia, M.[Michal], Plataniotis, K.N.[Konstantinos N.],
Human gait recognition from motion capture data in signature poses,
IET-Bio(6), No. 2, March 2017, pp. 129-137.
DOI Link 1703
BibRef

Balazia, M.[Michal], Hlavácková-Schindler, K.[Katerina], Sojka, P.[Petr], Plant, C.[Claudia],
Interpretable Gait Recognition by Granger Causality,
ICPR22(1069-1075)
IEEE DOI 2212
Measurement, Analytical models, Neural networks, Video surveillance, Skeleton, Motion capture BibRef

Balazia, M.[Michal], Sojka, P.[Petr],
Walker-Independent Features for Gait Recognition from Motion Capture Data,
SSSPR16(310-321).
Springer DOI 1611
BibRef

Chhatrala, R.[Risil], Jadhav, D.V.[Dattatray V.],
Multilinear Laplacian discriminant analysis for gait recognition,
IET-CV(11), No. 2, March 2017, pp. 153-160.
DOI Link 1703
BibRef

Ryu, J.[Jaehwan], Lee, B.H.[Byeong-Hyeon], Kim, D.H.[Deok-Hwan],
sEMG Signal-Based Lower Limb Human Motion Detection Using a Top and Slope Feature Extraction Algorithm,
SPLetters(24), No. 7, July 2017, pp. 929-932.
IEEE DOI 1706
Feature extraction, Legged locomotion, Motion detection, Muscles, Reactive power, Signal processing algorithms, Timing, Electromyography (EMG), feature extraction, gait recognition, human-computer interaction, locomotion, mode BibRef

Verlekar, T.T.[Tanmay T.], Correia, P.L.[Paulo L.], Soares, L.D.[Luís D.],
View-invariant gait recognition system using a gait energy image decomposition method,
IET-Bio(6), No. 4, July 2017, pp. 299-306.
DOI Link 1707
BibRef

Verlekar, T.T.[Tanmay Tulsidas], Soares, L.D.[Luís Ducla], Correia, P.L.[Paulo Lobato],
Gait recognition in the wild using shadow silhouettes,
IVC(76), 2018, pp. 1-13.
Elsevier DOI 1808
Shadow biometrics, Gait recognition, Biometric recognition, View invariant BibRef

Lishani, A.O.[Ait O.], Boubchir, L.[Larbi], Khalifa, E.[Emad], Bouridane, A.[Ahmed],
Human gait recognition based on Haralick features,
SIViP(11), No. 6, September 2017, pp. 1123-1130.
Springer DOI 1708
BibRef

Isaac, E.R.H.P., Elias, S., Rajagopalan, S., Easwarakumar, K.S.,
View-Invariant Gait Recognition Through Genetic Template Segmentation,
SPLetters(24), No. 8, August 2017, pp. 1188-1192.
IEEE DOI 1708
gait analysis, genetic algorithms, image recognition, image segmentation, active energy image template, boundary selection process, gait energy image template, gait entropy image template, genetic algorithm, genetic template segmentation, template-based model-free approach, view-invariant gait recognition, Biological cells, Clothing, Feature extraction, Gait recognition, Genetic algorithms, Genetics, Legged locomotion, Biometrics, gait recognition, genetic algorithms (GAs), linear, discriminant, analysis, (LDA) BibRef

Chaurasia, P., Yogarajah, P., Condell, J.V.[Joan V.], Prasad, G.[Girijesh],
Fusion of Random Walk and Discrete Fourier Spectrum Methods for Gait Recognition,
HMS(47), No. 6, December 2017, pp. 751-762.
IEEE DOI 1712
Clothing, Data mining, Discrete Fourier transforms, Feature extraction, Fourier transforms, Gait recognition, random walk (RW) BibRef

Zou, Q., Ni, L., Wang, Q., Li, Q., Wang, S.,
Robust Gait Recognition by Integrating Inertial and RGBD Sensors,
Cyber(48), No. 4, April 2018, pp. 1136-1150.
IEEE DOI 1804
Feature extraction, Gait recognition, Hidden Markov models, Image color analysis, Legged locomotion, Sensors, Trajectory, person identification BibRef

Medikonda, J.[Jeevan], Madasu, H.[Hanmandlu], Ketan, P.B.[Panigrahi Bijaya],
Information set based features for the speed invariant gait recognition,
IET-Bio(7), No. 3, May 2018, pp. 269-277.
DOI Link 1804
BibRef

Jia, N.[Ning], Sanchez, V.[Victor], Li, C.T.[Chang-Tsun],
On view-invariant gait recognition: a feature selection solution,
IET-Bio(7), No. 4, July 2018, pp. 287-295.
DOI Link 1807
BibRef

Zhang, Z., Chen, J., Wu, Q., Shao, L.,
GII Representation-Based Cross-View Gait Recognition by Discriminative Projection With List-Wise Constraints,
Cyber(48), No. 10, October 2018, pp. 2935-2947.
IEEE DOI 1809
Gait recognition, Cameras, Feature extraction, Robustness, Correlation, Probes, Databases, Cross-view gait recognition, list-wise constraints BibRef

Khan, M.H., Farid, M.S., Zahoor, M., Grzegorzek, M.,
Cross- View Gait Recognition Using Non-Linear View Transformations of Spatiotemporal Features,
ICIP18(773-777)
IEEE DOI 1809
Spatiotemporal phenomena, Gait recognition, Support vector machines, Training, view transformation BibRef

Rida, I.[Imad], Almaadeed, N.[Noor], Almaadeed, S.[Somaya],
Robust gait recognition: a comprehensive survey,
IET-Bio(8), No. 1, January 2019, pp. 14-28.
DOI Link 1901
Survey, Gait Analysis. BibRef

Wang, M.[Mo], Wang, X.[Xin'an], Fan, Z.C.[Zhuo-Chen], Chen, F.[Fei], Zhang, S.[Sixu], Peng, C.[Chen],
Research on feature extraction algorithm for plantar pressure image and gait analysis in stroke patients,
JVCIR(58), 2019, pp. 525-531.
Elsevier DOI 1901
Plantar pressure, Feature extraction, Image denoising, Clustering analysis, Gait analysis BibRef

Ghaeminia, M.H.[Mohammad H.], Shokouhi, S.B.[Shahriar B.],
On the selection of spatiotemporal filtering with classifier ensemble method for effective gait recognition,
SIViP(13), No. 1, February 2019, pp. 43-51.
WWW Link. 1901
BibRef

Bandera, J.P.[Juan Pedro], Marfil, R.[Rebeca], Romero-Garcés, A.[Adrián], Voilmy, D.[Dimitri],
A new paradigm for autonomous human motion description and evaluation: Application to the Get Up & Go test use case,
PRL(118), 2019, pp. 51-60.
Elsevier DOI 1902
Human motion analysis, Socially assistive robots, Gait analysis BibRef

Ben, X.[Xianye], Zhang, P.[Peng], Lai, Z.H.[Zhi-Hui], Yan, R.[Rui], Zhai, X.L.[Xin-Liang], Meng, W.X.[Wei-Xiao],
A general tensor representation framework for cross-view gait recognition,
PR(90), 2019, pp. 87-98.
Elsevier DOI 1903
Gait recognition, Cross-view gait, Tensor representation, Framework BibRef

Zhang, P.[Peng], Xu, J.S.[Jing-Song], Wu, Q.[Qiang], Huang, Y.[Yan], Ben, X.[Xianye],
Learning Spatial-Temporal Representations Over Walking Tracklet for Long-Term Person Re-Identification in the Wild,
MultMed(23), 2021, pp. 3562-3576.
IEEE DOI 2110
Skeleton, Tracking, Image color analysis, Cameras, Streaming media, Trajectory, dataset collection BibRef

Behera, P.K.[Pravat Kumar], Mandava, R.K.[Ravi Kumar], Vundavilli, P.R.[Pandu Ranga],
Push recovery system and balancing of a biped robot on steadily increasing slope of an inclined plane,
IJCVR(9), No. 1, 2019, pp. 70-89.
DOI Link 1903
BibRef

Rashwan, H.A.[Hatem A.], García, M.Á.[Miguel Ángel], Chambon, S.[Sylvie], Puig, D.[Domenec],
Gait representation and recognition from temporal co-occurrence of flow fields,
MVA(30), No. 1, February 2019, pp. 139-152.
Springer DOI 1904
BibRef

Khan, M.H.[Muhammad Hassan], Farid, M.S.[Muhammad Shahid], Grzegorzek, M.[Marcin],
Spatiotemporal features of human motion for gait recognition,
SIViP(13), No. 2, March 2019, pp. 369-377.
Springer DOI 1904
BibRef

Ben, X., Gong, C., Zhang, P., Jia, X., Wu, Q., Meng, W.,
Coupled Patch Alignment for Matching Cross-View Gaits,
IP(28), No. 6, June 2019, pp. 3142-3157.
IEEE DOI 1905
Gait recognition, Cameras, Feature extraction, Optimization, Probes, Clothing, multi-dimensional patch alignment BibRef

Wang, Q.[Qu], Ye, L.L.[Lang-Lang], Luo, H.Y.[Hai-Yong], Men, A.D.[Ai-Dong], Zhao, F.[Fang], Ou, C.H.[Chang-Hai],
Pedestrian Walking Distance Estimation Based on Smartphone Mode Recognition,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Liao, R.J.[Ri-Jun], Yu, S.Q.[Shi-Qi], An, W.Z.[Wei-Zhi], Huang, Y.Z.[Yong-Zhen],
A model-based gait recognition method with body pose and human prior knowledge,
PR(98), 2020, pp. 107069.
Elsevier DOI 1911
Gait recognition, Human body pose, Spatio-temporal feature, BibRef

Hou, S.H.[Sai-Hui], Cao, C.S.[Chun-Shui], Liu, X.[Xu], Huang, Y.Z.[Yong-Zhen],
Gait Lateral Network: Learning Discriminative and Compact Representations for Gait Recognition,
ECCV20(IX:382-398).
Springer DOI 2011
BibRef

Truong, C.[Charles], Barrois-Müller, R.[Rémi], Moreau, T.[Thomas], Provost, C.[Clément], Vienne-Jumeau, A.[Aliénor], Moreau, A.[Albane], Vidal, P.P.[Pierre-Paul], Vayatis, N.[Nicolas], Buffat, S.[Stéphane], Yelnik, A.[Alain], Ricard, D.[Damien], Oudre, L.[Laurent],
A Data Set for the Study of Human Locomotion with Inertial Measurements Units,
IPOL(9), 2019, pp. 381-390.
DOI Link 1911
Dataset, Gait. Data set of 1020 multivariate gait signals collected with two inertial measurement units, from 230 subjects undergoing a fixed protocol: standing still, walking 10 m, turning around, walking back and stopping. In total, 8.5~h of gait time series are distributed. BibRef

Hirose, Y.[Yuki], Nakamura, K.[Kazuaki], Nitta, N.[Naoko], Babaguchi, N.[Noboru],
Discrimination between Genuine and Cloned Gait Silhouette Videos via Autoencoder-Based Training Data Generation,
IEICE(E102-D), No. 12, December 2019, pp. 2535-2546.
WWW Link. 1912
BibRef

de Marsico, M.[Maria], Mecca, A.[Alessio],
A Survey on Gait Recognition via Wearable Sensors,
Surveys(52), No. 4, September 2019, pp. Article No 86.
DOI Link 1912
Survey, Gait. BibRef

Dai, S.J.[Shi-Jie], Wang, R.[Rui], Zhang, H.[Huibo],
A gait skeleton model extraction method based on the fusion between vision and tactility,
VC(35), No. 12, December 2018, pp. 1713-1723.
WWW Link. 1912
BibRef

Wu, Q.T.[Qing-Tian], Zhou, Y.M.[Yi-Min], Wu, X.Y.[Xin-Yu], Liang, G.Y.[Guo-Yuan], Ou, Y.S.[Yong-Sheng], Sun, T.F.[Tian-Fu],
Real-time running detection system for UAV imagery based on optical flow and deep convolutional networks,
IET-ITS(14), No. 5, May 2020, pp. 278-287.
DOI Link 2005
BibRef

Kusakunniran, W.[Worapan],
Review of gait recognition approaches and their challenges on view changes,
IET-Bio(9), No. 6, November 2020, pp. 238-250.
DOI Link 2010
Survey, Gait. BibRef

Wu, H., Tian, J., Fu, Y., Li, B., Li, X.,
Condition-Aware Comparison Scheme for Gait Recognition,
IP(30), 2021, pp. 2734-2744.
IEEE DOI 2102
Feature extraction, Gait recognition, Adaptation models, Data models, Shape, Legged locomotion, Geometry, Gait recognition, geometry-guided data augmentation BibRef

Iwamura, M.[Masakazu], Mori, S.[Shunsuke], Nakamura, K.[Koichiro], Tanoue, T.[Takuya], Utsumi, Y.[Yuzuko], Makihara, Y.S.[Yasu-Shi], Muramatsu, D.[Daigo], Kise, K.[Koichi], Yagi, Y.S.[Yasu-Shi],
Individuality-Preserving Silhouette Extraction for Gait Recognition and Its Speedup,
IEICE(E104-D), No. 7, July 2021, pp. 992-1001.
WWW Link. 2107
BibRef

Amsaprabhaa, M., Nancy Jane, Y., Khanna Nehemiah, H.,
A survey on spatio-temporal framework for kinematic gait analysis in RGB videos,
JVCIR(79), 2021, pp. 103218.
Elsevier DOI 2109
Survey, Gait. Human gait recognition, Spatio-temporal features, Gait databases, Gait recognition representation, Gait prediction BibRef

Hasan, M.M.[Md Mahedi], Mustafa, H.A.[Hossen Asiful],
Learning view-invariant features using stacked autoencoder for skeleton-based gait recognition,
IET-CV(15), No. 7, 2021, pp. 527-545.
DOI Link 2109
BibRef

Wen, J.Q.[Jun-Qin], Wang, X.[Xiuhui],
Gait recognition based on sparse linear subspace,
IET-IPR(15), No. 12, 2021, pp. 2761-2769.
DOI Link 2109
BibRef

Tan, X.W.[Xiao-Wei], Zhang, B.[Bi], Liu, G.J.[Guang-Jun], Zhao, X.G.[Xin-Gang], Zhao, Y.W.[Yi-Wen],
Phase Variable Based Recognition of Human Locomotor Activities Across Diverse Gait Patterns,
HMS(51), No. 6, December 2021, pp. 684-695.
IEEE DOI 2112
Activity recognition, Classification algorithms, Gait recognition, Patient monitoring, Legged locomotion, phase BibRef

Gao, S.[Shuo], Yun, J.[Jing], Zhao, Y.[Yumeng], Liu, L.M.[Li-Min],
Gait-D: Skeleton-based gait feature decomposition for gait recognition,
IET-CV(16), No. 2, 2022, pp. 111-125.
DOI Link 2202
biometrics, convolutional neural nets, feature extraction, pose estimation, video signal processing BibRef

Liu, X.K.[Xiao-Kai], You, Z.Y.[Zhao-Yang], He, Y.X.[Yu-Xiang], Bi, S.[Sheng], Wang, J.[Jie],
Symmetry-Driven hyper feature GCN for skeleton-based gait recognition,
PR(125), 2022, pp. 108520.
Elsevier DOI 2203
Dynamics of skeleton, Gait recognition, Graph convolutional networks, Symmetric interaction pattern, Hyper feature BibRef

Li, H.K.[Hua-Kang], Qiu, Y.[Yidan], Zhao, H.M.[Hui-Min], Zhan, J.[Jin], Chen, R.J.[Rong-Jun], Wei, T.J.[Tuan-Jie], Huang, Z.H.[Zhi-Hui],
GaitSlice: A gait recognition model based on spatio-temporal slice features,
PR(124), 2022, pp. 108453.
Elsevier DOI 2203
Gait recognition, Key frame, Cross-view, Attention mechanism, Slice feature, GaitSlice BibRef

Han, F.[Feng], Li, X.J.[Xue-Jian], Zhao, J.[Jian], Shen, F.[Furao],
A unified perspective of classification-based loss and distance-based loss for cross-view gait recognition,
PR(125), 2022, pp. 108519.
Elsevier DOI 2203
Biometrics, Gait recognition, Metric learning, Angular softmax loss function, Triplet loss function BibRef

Song, X.[Xu], Huang, Y.[Yan], Huang, Y.[Yan], Shan, C.F.[Cai-Feng], Wang, J.L.[Ji-Long], Chen, Y.[Yu],
Distilled light GaitSet: Towards scalable gait recognition,
PRL(157), 2022, pp. 27-34.
Elsevier DOI 2205
Gait recognition, Lightweight network, Knowledge distillation BibRef

Qin, H.[Hao], Chen, Z.[Zhenxue], Guo, Q.Q.[Qing-Qiang], Wu, Q.M.J.[Q. M. Jonathan], Lu, M.X.[Meng-Xu],
RPNet: Gait Recognition With Relationships Between Each Body-Parts,
CirSysVideo(32), No. 5, May 2022, pp. 2990-3000.
IEEE DOI 2205
Feature extraction, Gait recognition, Legged locomotion, Data models, Analytical models, Convolutional neural networks, different scale blocks BibRef

Yao, L.X.[Ling-Xiang], Kusakunniran, W.[Worapan], Wu, Q.[Qiang], Xu, J.S.[Jing-Song], Zhang, J.[Jian],
Collaborative Feature Learning for Gait Recognition Under Cloth Changes,
CirSysVideo(32), No. 6, June 2022, pp. 3615-3629.
IEEE DOI 2206
Feature extraction, Gait recognition, Clothing, Skeleton, Transformers, Visualization, Legged locomotion, Gait recognition, deep learning BibRef

Wang, Y.X.[Yan-Xiang], Zhang, X.[Xian], Shen, Y.R.[Yi-Ran], Du, B.[Bowen], Zhao, G.R.[Guang-Rong], Cui, L.Z.[Li-Zhen], Wen, H.K.[Hong-Kai],
Event-Stream Representation for Human Gaits Identification Using Deep Neural Networks,
PAMI(44), No. 7, July 2022, pp. 3436-3449.
IEEE DOI 2206
Sensors, Voltage control, Feature extraction, Cameras, Task analysis, Gait recognition, Convolution, Gait recognition, graph-based convolutional networks BibRef

Wang, Y.X.[Yan-Xiang], Du, B.[Bowen], Shen, Y.R.[Yi-Ran], Wu, K.[Kai], Zhao, G.R.[Guang-Rong], Sun, J.G.[Jian-Guo], Wen, H.K.[Hong-Kai],
EV-Gait: Event-Based Robust Gait Recognition Using Dynamic Vision Sensors,
CVPR19(6351-6360).
IEEE DOI 2002
BibRef

Wang, L.K.[Li-Kai], Chen, J.Y.[Jin-Yan], Liu, Y.X.[Yu-Xin],
Frame-level refinement networks for skeleton-based gait recognition,
CVIU(222), 2022, pp. 103500.
Elsevier DOI 2209
Gait recognition, Graph convolution, Frame-level refinement BibRef

He, Z.[Ziwen], Wang, W.[Wei], Dong, J.[Jing], Tan, T.N.[Tie-Niu],
Temporal sparse adversarial attack on sequence-based gait recognition,
PR(133), 2023, pp. 109028.
Elsevier DOI 2210
Adversarial attack, Gait recognition, Temporal sparsity BibRef

Parashar, A.[Anubha], Parashar, A.[Apoorva], Shekhawat, R.S.[Rajveer Singh],
A robust covariate-invariant gait recognition based on pose features,
IET-Bio(11), No. 6, 2022, pp. 601-613.
DOI Link 2212
biometrics, covariates, deep learning, gait recognition, pose estimation BibRef

Shi, X.[Xin], Wang, Z.[Zhelong], Zhao, H.Y.[Hong-Yu], Qiu, S.[Sen], Liu, R.[Ruichen], Lin, F.[Fang], Tang, K.[Kai],
Threshold-Free Phase Segmentation and Zero Velocity Detection for Gait Analysis Using Foot-Mounted Inertial Sensors,
HMS(53), No. 1, February 2023, pp. 176-186.
IEEE DOI 2301
Micromechanical devices, Inertial sensors, Estimation, Quaternions, Manuals, Man-machine systems, Labeling, Gait analysis, zero velocity updates (ZUPT) BibRef

Shehata, A.[Allam], Makihara, Y.S.[Yasu-Shi], Muramatsu, D.[Daigo], Ahad, M.A.R.[Md Atiqur Rahman], Yagi, Y.S.[Yasu-Shi],
Annotator-dependent uncertainty-aware estimation of gait relative attributes,
PR(136), 2023, pp. 109197.
Elsevier DOI 2301
Gait relative attribute, Relative label distribution, Relative score distribution, Annotator's uncertainty, Transition matrix BibRef

Li, X.[Xiang], Makihara, Y.S.[Yasu-Shi], Xu, C.[Chi], Yagi, Y.S.[Yasu-Shi], Yu, S.Q.[Shi-Qi], Ren, M.W.[Ming-Wu],
End-to-end Model-based Gait Recognition,
ACCV20(III:3-20).
Springer DOI 2103
BibRef

Song, C.F.[Chun-Feng], Huang, Y.Z.[Yong-Zhen], Wang, W.N.[Wei-Ning], Wang, L.[Liang],
CASIA-E: A Large Comprehensive Dataset for Gait Recognition,
PAMI(45), No. 3, March 2023, pp. 2801-2815.
IEEE DOI 2302
Dataset, Gait Recognition. Videos, Gait recognition, Legged locomotion, Face recognition, Training, Lighting, Benchmark testing, Deep learning, gait dataset, soft biometrics BibRef

Yao, L.X.[Ling-Xiang], Kusakunniran, W.[Worapan], Zhang, P.[Peng], Wu, Q.[Qiang], Zhang, J.[Jian],
Improving Disentangled Representation Learning for Gait Recognition Using Group Supervision,
MultMed(25), 2023, pp. 4187-4198.
IEEE DOI 2310
BibRef

Fan, C.[Chao], Hou, S.[Saihui], Wang, J.[Jilong], Huang, Y.Z.[Yong-Zhen], Yu, S.Q.[Shi-Qi],
Learning Gait Representation From Massive Unlabelled Walking Videos: A Benchmark,
PAMI(45), No. 12, December 2023, pp. 14920-14937.
IEEE DOI 2311
BibRef

Chen, Y.F.[Yi-Fan], Li, X.L.[Xue-Long],
Gait feature learning via spatio-temporal two-branch networks,
PR(147), 2024, pp. 110090.
Elsevier DOI 2312
Gait recognition, Spatio-temporal gait feature, Convolutional neural networks BibRef

Sezavar, A.[Ahmadreza], Atta, R.[Randa], Ghanbari, M.[Mohammed],
DCapsNet: Deep capsule network for human activity and gait recognition with smartphone sensors,
PR(147), 2024, pp. 110054.
Elsevier DOI 2312
Gait recognition, Human activity recognition, Capsule network, Smartphone sensors BibRef

Vijayvargiya, A.[Ankit], Kumar, R.[Rajesh], Sharma, P.[Parul],
PC-GNN: Pearson Correlation-Based Graph Neural Network for Recognition of Human Lower Limb Activity Using sEMG Signal,
HMS(53), No. 6, December 2023, pp. 945-954.
IEEE DOI 2312
BibRef

Deng, M.Q.[Mu-Qing], Fan, Z.Y.[Zhu-Yao], Lin, P.[Peng], Feng, X.R.[Xiao-Reng],
Human Gait Recognition Based on Frontal-View Sequences Using Gait Dynamics and Deep Learning,
MultMed(26), 2024, pp. 117-126.
IEEE DOI 2401
BibRef

Li, A.[Aoqi], Hou, S.[Saihui], Cai, Q.Y.[Qing-Yuan], Fu, Y.[Yang], Huang, Y.Z.[Yong-Zhen],
Gait Recognition With Drones: A Benchmark,
MultMed(26), 2024, pp. 3530-3540.
IEEE DOI 2402
Gait recognition, Drones, Cameras, Task analysis, Feature extraction, Probes, Gait recognition, drones, high vertical views BibRef

Wang, R.S.[Run-Sheng], Shi, Y.X.[Yu-Xuan], Ling, H.[Hefei], Li, Z.Y.[Zong-Yi], Zhao, C.X.[Cheng-Xin], Wei, B.[Bohao], Li, H.[He], Li, P.[Ping],
Gait Recognition With Multi-Level Skeleton-Guided Refinement,
MultMed(26), 2024, pp. 4515-4526.
IEEE DOI 2403
Feature extraction, Bones, Joints, Visualization, Heating systems, Gait recognition, Semantics, Gait recognition, multi-modality BibRef

Hodossy, B.K.[Balint K.], Guez, A.S.[Annika S.], Jing, S.[Shibo], Huo, W.G.[Wei-Guang], Vaidyanathan, R.[Ravi], Farina, D.[Dario],
Leveraging High-Density EMG to Investigate Bipolar Electrode Placement for Gait Prediction Models,
HMS(54), No. 2, April 2024, pp. 192-201.
IEEE DOI 2404
Electrodes, Muscles, Measurement, Predictive models, Knee, Electromyography, Standards, signal processing BibRef

Huo, W.[Wei], Wang, K.[Ke], Tang, J.[Jun], Wang, N.[Nian], Liang, D.[Dong],
GaitSCM: Causal representation learning for gait recognition,
CVIU(243), 2024, pp. 103995.
Elsevier DOI Code:
WWW Link. 2405
Gait recognition, Global and local feature extractor, Disentangled representation learning, Causal representation learning BibRef

Hou, S.H.[Sai-Hui], Huang, P.J.[Pan-Jian], Liu, X.[Xu], Cao, C.S.[Chun-Shui], Huang, Y.Z.[Yong-Zhen],
Cloth-Imbalanced Gait Recognition via Hallucination,
CirSysVideo(34), No. 7, July 2024, pp. 5665-5676.
IEEE DOI 2407
Tail, Headphones, Gait recognition, Feature extraction, Training, Benchmark testing, cross-clothes hallucination BibRef

Wang, Z.Y.[Zheng-You], Du, C.Y.[Cheng-Yu], Zhang, Y.P.[Yun-Peng], Bai, J.[Jing], Zhuang, S.[Shanna],
EM-Gait: Gait recognition using motion excitation and feature embedding self-attention,
JVCIR(103), 2024, pp. 104266.
Elsevier DOI 2409
Gait recognition, Motion excitation, Embedding self-attention, Identity recognition BibRef

Hua, C.S.[Chun-Sheng], Zhang, H.[Hao], Li, J.[Jia], Pan, Y.J.[Ying-Jie],
Continuous-dilated temporal and inter-frame motion excitation feature learning for gait recognition,
IET-CV(18), No. 6, 2024, pp. 788-800.
DOI Link 2409
gait analysis, image motion analysis, spatiotemporal phenomena BibRef

Hu, Y.C.[Yu-Chen], Chen, Z.[Zhenxue], Liu, C.Y.[Cheng-Yun], Liang, T.[Tian], Lu, D.[Dan],
SAFLFusionGait: Gait recognition network with separate attention and different granularity feature learnability fusion,
JVCIR(104), 2024, pp. 104284.
Elsevier DOI 2411
Gait recognition, Convolutional neural network (CNN), Deep learning, Feature fusion, Supervised learning BibRef

Peng, G.Z.[Guo-Zhen], Li, R.[Rui], Li, A.[Annan], Wang, Y.H.[Yun-Hong],
Synthesis Pyramid Pooling: A Strong Pooling Method for Gait Recognition in the Wild,
SPLetters(31), 2024, pp. 3159-3163.
IEEE DOI 2411
Data mining, Pedestrians, Gait recognition, Aggregates, Vectors, Feature extraction, Legged locomotion, Face recognition, Cameras, synthesis pyramid pooling BibRef

He, W.T.[Wen-Tao], Ren, J.F.[Jian-Feng], Bai, R.B.[Rui-Bin], Jiang, X.D.[Xu-Dong],
Radar gait recognition using Dual-branch Swin Transformer with Asymmetric Attention Fusion,
PR(159), 2025, pp. 111101.
Elsevier DOI Code:
WWW Link. 2412
Micro-Doppler signature, Radar gait recognition, Spectrogram, Cadence velocity diagram, Asymmetric Attention Fusion BibRef

Junaid, M.I.[Mohammad Iman], Prakash, A.J.[Allam Jaya], Ari, S.[Samit],
Human gait recognition using joint spatiotemporal modulation in deep convolutional neural networks,
JVCIR(105), 2024, pp. 104322.
Elsevier DOI 2501
Convolutional neural network (CNN), Gait recognition, Joint learning, Spatial modulation, Temporal modulation BibRef

Huang, P.[Panjian], Peng, Y.J.[Yun-Jie], Hou, S.[Saihui], Cao, C.[Chunshui], Liu, X.[Xu], He, Z.Q.[Zhi-Qiang], Huang, Y.Z.[Yong-Zhen],
Occluded Gait Recognition with Mixture of Experts: An Action Detection Perspective,
ECCV24(VI: 380-397).
Springer DOI 2412
BibRef

Fu, Y.[Yang], Hou, S.[Saihui], Meng, S.[Shibei], Hu, X.C.[Xue-Cai], Cao, C.[Chunshui], Liu, X.[Xu], Huang, Y.Z.[Yong-Zhen],
Cut Out the Middleman: Revisiting Pose-based Gait Recognition,
ECCV24(XXXI: 112-128).
Springer DOI 2412
BibRef

Thapar, D.[Daksh], Chaudhari, J.[Jayesh], Manchanda, S.[Sunny], Nigam, A.[Aditya], Arora, C.[Chetan],
Gaitw: Enhancing Gait Recognition in the Wild Using Dynamic Information,
ACCV24(I: 24-43).
Springer DOI 2412
BibRef

Ma, K.[Kang], Fu, Y.[Ying], Cao, C.S.[Chun-Shui], Hou, S.H.[Sai-Hui], Huang, Y.Z.[Yong-Zhen], Zheng, D.Z.[De-Zhi],
Learning Visual Prompt for Gait Recognition,
CVPR24(593-603)
IEEE DOI 2410
Deep learning, Visualization, Pedestrians, Limiting, Dynamics, Feature extraction, Transformers BibRef

Catruna, A.[Andy], Cosma, A.[Adrian], Radoi, E.[Emilian],
GaitPT: Skeletons are All You Need for Gait Recognition,
FG24(1-10)
IEEE DOI Code:
WWW Link. 2408
Legged locomotion, Accuracy, Pose estimation, Transformers, Feature extraction, Skeleton, Robustness BibRef

Liao, R.[Rijun], Li, Z.[Zhu], Bhattacharyya, S.S.[Shuvra S.], York, G.[George],
View DiffGait: View Pyramid Diffusion for Gait Recognition,
FG24(1-9)
IEEE DOI 2408
Face recognition, Gaussian noise, Noise reduction, Diffusion processes, Transforms, Gesture recognition, View Noise Removing BibRef

Catruna, A.[Andy], Cosma, A.[Adrian], Radoi, E.[Emilian],
The Paradox of Motion: Evidence for Spurious Correlations in Skeleton-Based Gait Recognition Models,
FG24(1-9)
IEEE DOI 2408
Legged locomotion, Degradation, Analytical models, Correlation, Accuracy, Face recognition, Gesture recognition BibRef

Niculae, A.[Andrei], Catruna, A.[Andy], Cosma, A.[Adrian], Rosner, D.[Daniel], Radoi, E.[Emilian],
Gait Recognition from Highly Compressed Videos,
FG24(1-7)
IEEE DOI 2408
Analytical models, Surveillance, Pose estimation, Pipelines, Video compression, Data models, Noise measurement BibRef

Chivereanu, R.[Radu], Cosma, A.[Adrian], Catruna, A.[Andy], Rughinis, R.[Razvan], Radoi, E.[Emilian],
Aligning Actions and Walking to LLM-Generated Textual Descriptions,
FG24(1-7)
IEEE DOI Code:
WWW Link. 2408
Legged locomotion, Large language models, Gesture recognition, Footwear, Linguistics, Data augmentation, Skeleton BibRef

Habib, G.[Gavriel], Barzilay, N.[Noa], Shimshi, O.[Or], Ben-Ari, R.[Rami], Darshan, N.[Nir],
Watch Where You Head: A View-biased Domain Gap in Gait Recognition and Unsupervised Adaptation,
WACV24(6097-6107)
IEEE DOI 2404
Legged locomotion, Adaptation models, Computational modeling, Task analysis, Gait recognition, Algorithms, Biometrics, face, gesture BibRef

Gupta, A.[Ayush], Chellappa, R.[Rama],
You Can Run but not Hide: Improving Gait Recognition with Intrinsic Occlusion Type Awareness,
WACV24(5881-5890)
IEEE DOI 2404
Detectors, Feature extraction, Data mining, Task analysis, Gait recognition, Videos, Algorithms, Biometrics, face, gesture BibRef

Guo, H.J.[Hong-Ji], Ji, Q.[Qiang],
Physics-Augmented Autoencoder for 3D Skeleton-Based Gait Recognition,
ICCV23(19570-19581)
IEEE DOI 2401
BibRef

Wang, L.[Lei], Liu, B.[Bo], Liang, F.F.[Fang-Fang], Wang, B.[Bincheng],
Hierarchical Spatio-Temporal Representation Learning for Gait Recognition,
ICCV23(19582-19592)
IEEE DOI Code:
WWW Link. 2401
BibRef

Xu, C.[Chi], Tsuji, S.[Shogo], Makihara, Y.S.[Yasu-Shi], Li, X.[Xiang], Yagi, Y.S.[Yasu-Shi],
Occluded Gait Recognition via Silhouette Registration Guided by Automated Occlusion Degree Estimation,
AMFG23(3191-3201)
IEEE DOI 2401
BibRef

Ma, K.[Kang], Fu, Y.[Ying], Zheng, D.[Dezhi], Peng, Y.J.[Yun-Jie], Cao, C.[Chunshui], Huang, Y.Z.[Yong-Zhen],
Fine-grained Unsupervised Domain Adaptation for Gait Recognition,
ICCV23(11279-11288)
IEEE DOI 2401
BibRef

Wang, M.[Ming], Guo, X.D.[Xian-Da], Lin, B.B.[Bei-Bei], Yang, T.[Tian], Zhu, Z.[Zheng], Li, L.C.[Lin-Cheng], Zhang, S.L.[Shun-Li], Yu, X.[Xin],
DyGait: Exploiting Dynamic Representations for High-performance Gait Recognition,
ICCV23(13378-13387)
IEEE DOI 2401
BibRef

Fu, Y.[Yang], Meng, S.[Shibei], Hou, S.[Saihui], Hu, X.C.[Xue-Cai], Huang, Y.Z.[Yong-Zhen],
GPGait: Generalized Pose-based Gait Recognition,
ICCV23(19538-19547)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yu, H.[Hao], Liang, Y.C.[Yu-Chen], Liu, Y.H.[Yue-Hu], Zhang, C.[Chi],
Reuse Non-Terrain Policies for Learning Terrain-Adaptive Humanoid Locomotion Skills,
ICIP23(695-699)
IEEE DOI 2312
BibRef

Wang, L.[Lei], Liu, B.[Bo], Wang, B.C.[Bin-Cheng], Yu, F.Q.[Fu-Qiang],
GAITMM: Multi-Granularity Motion Sequence Learning for Gait Recognition,
ICIP23(845-849)
IEEE DOI 2312
BibRef

Xu, C.[Chi], Makihara, Y.S.[Yasu-Shi], Li, X.[Xiang], Yagi, Y.S.[Yasu-Shi],
Gait Recognition from Fisheye Images,
Biometrics23(1030-1040)
IEEE DOI 2309
BibRef

Fan, C.[Chao], Liang, J.H.[Jun-Hao], Shen, C.[Chuanfu], Hou, S.[Saihui], Huang, Y.Z.[Yong-Zhen], Yu, S.Q.[Shi-Qi],
OpenGait: Revisiting Gait Recognition Toward Better Practicality,
CVPR23(9707-9716)
IEEE DOI 2309
BibRef

Cui, Y.F.[Yu-Feng], Kang, Y.[Yimei],
Multi-modal Gait Recognition via Effective Spatial-Temporal Feature Fusion,
CVPR23(17949-17957)
IEEE DOI 2309
BibRef

Dou, H.Z.[Huan-Zhang], Zhang, P.Y.[Peng-Yi], Su, W.[Wei], Yu, Y.L.[Yun-Long], Lin, Y.[Yining], Li, X.[Xi],
GaitGCI: Generative Counterfactual Intervention for Gait Recognition,
CVPR23(5578-5588)
IEEE DOI 2309
BibRef

Das, D.[Dhritimaan], Agarwal, A.[Ayush], Chattopadhyay, P.[Pratik],
Gait Recognition from Occluded Sequences in Surveillance Sites,
RealWorld22(703-719).
Springer DOI 2304
BibRef

Zhu, H.D.[Hai-Dong], Zheng, Z.H.[Zhao-Heng], Nevatia, R.[Ram],
Gait Recognition Using 3-D Human Body Shape Inference,
WACV23(909-918)
IEEE DOI 2302
Training, Legged locomotion, Shape, Clothing, Cameras, Task analysis, Algorithms: Biometrics, face, gesture, body pose BibRef

Segundo, M.P.[Mauricio Pamplona], Hill, C.[Cole], Sarkar, S.[Sudeep],
Long range gait matching using 3D body fitting with gait-specific motion constraints,
LongRange23(603-612)
IEEE DOI 2302
Legged locomotion, Deformable models, Training, Solid modeling, Shape, Fitting BibRef

Chen, L.[Lu], Wei, Q.[Qing], Zhang, Z.T.[Zhi-Tong], Chang, X.[Xu], Wei, X.J.[Xiao-Jian], An, H.L.[Hong-Lei],
Learning to Walk on Low Friction Terrain by Reinforcement Learning,
ICRVC22(355-359)
IEEE DOI 2301
Legged locomotion, Training, Friction, Reinforcement learning, Robustness, Nonlinear dynamical systems, legged robot, low friction BibRef

Li, Z.Q.[Zi-Qiong], Li, Y.R.[Yan-Ran], Yu, S.Q.[Shi-Qi],
FedGait: A Benchmark for Federated Gait Recognition,
ICPR22(1371-1377)
IEEE DOI 2212
Training, Privacy, Data privacy, Machine learning algorithms, Federated learning, Satellite broadcasting, Benchmark testing BibRef

Hsu, H.M.[Hung-Min], Wang, Y.Z.[Yi-Zhou], Yang, C.Y.[Cheng-Yen], Hwang, J.N.[Jenq-Neng], Thuc, H.L.U.[Hoang Le Uyen], Kim, K.J.[Kwang-Ju],
GAITTAKE: Gait Recognition by Temporal Attention and Keypoint-Guided Embedding,
ICIP22(2546-2550)
IEEE DOI 2211
Legged locomotion, Image recognition, Shape, Fuses, Forensics, Pose estimation, Benchmark testing, Gait Recognition, Human Pose Estimation BibRef

Teepe, T.[Torben], Gilg, J.[Johannes], Herzog, F.[Fabian], Hörmann, S.[Stefan], Rigoll, G.[Gerhard],
Towards a Deeper Understanding of Skeleton-based Gait Recognition,
Biometrics22(1568-1576)
IEEE DOI 2210
Training, Visualization, Pose estimation, Performance gain, Feature extraction BibRef

Chai, T.R.[Tian-Rui], Li, A.[Annan], Zhang, S.X.[Shao-Xiong], Li, Z.L.[Zi-Long], Wang, Y.H.[Yun-Hong],
Lagrange Motion Analysis and View Embeddings for Improved Gait Recognition,
CVPR22(20217-20226)
IEEE DOI 2210
Legged locomotion, Representation learning, Visualization, Shape, Mathematical models, Biometrics, Representation learning BibRef

Huang, X.H.[Xiao-Hu], Zhu, D.W.[Duo-Wang], Wang, H.[Hao], Wang, X.G.[Xing-Gang], Yang, B.[Bo], He, B.T.[Bo-Tao], Liu, W.Y.[Wen-Yu], Feng, B.[Bin],
Context-Sensitive Temporal Feature Learning for Gait Recognition,
ICCV21(12889-12898)
IEEE DOI 2203
Representation learning, Legged locomotion, Adaptation models, Codes, Convolution, Aggregates, Action and behavior recognition, Gestures and body pose BibRef

Zhu, Z.[Zheng], Guo, X.D.[Xian-Da], Yang, T.[Tian], Huang, J.J.[Jun-Jie], Deng, J.K.[Jian-Kang], Huang, G.[Guan], Du, D.L.[Da-Long], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Gait Recognition in the Wild: A Benchmark,
ICCV21(14769-14779)
IEEE DOI 2203
Dataset, Gait Recognition.
WWW Link. Biometrics, Datasets and evaluation, Emergency Reviewer BibRef

Huang, Z.[Zhen], Xue, D.X.[Di-Xiu], Shen, X.[Xu], Tian, X.M.[Xin-Mei], Li, H.Q.[Hou-Qiang], Huang, J.Q.[Jian-Qiang], Hua, X.S.[Xian-Sheng],
3D Local Convolutional Neural Networks for Gait Recognition,
ICCV21(14900-14909)
IEEE DOI 2203
Torso, Legged locomotion, Convolutional codes, Solid modeling, Shape, Spatiotemporal phenomena, Biometrics, Recognition and classification BibRef

Wang, M.[Ming], Lin, B.B.[Bei-Bei], Guo, X.D.[Xian-Da], Li, L.C.[Lin-Cheng], Zhu, Z.[Zheng], Sun, J.D.[Jian-De], Zhang, S.L.[Shun-Li], Liu, Y.[Yu], Yu, X.[Xin],
Gaitstrip: Gait Recognition via Effective Strip-based Feature Representations and Multi-level Framework,
ACCV22(IV:711-727).
Springer DOI 2307
BibRef

Lin, B.B.[Bei-Bei], Zhang, S.L.[Shun-Li], Yu, X.[Xin],
Gait Recognition via Effective Global-Local Feature Representation and Local Temporal Aggregation,
ICCV21(14628-14636)
IEEE DOI 2203
Visualization, Convolution, Aggregates, Feature extraction, Data mining, Biometrics, BibRef

Lin, B.B.[Bei-Bei], Zhang, S.L.[Shun-Li], Liu, Y.[Yu], Qin, S.D.[Sheng-Di],
Multi-Scale Temporal Information Extractor for Gait Recognition,
ICIP21(2998-3002)
IEEE DOI 2201
Image recognition, Aggregates, Feature extraction, Data mining, Convolutional neural networks, Gait recognition, Combined loss function BibRef

Chai, T.R.[Tian-Rui], Mei, X.Y.[Xin-Yu], Li, A.[Annan], Wang, Y.H.[Yun-Hong],
Silhouette-Based View-Embeddings for Gait Recognition Under Multiple Views,
ICIP21(2319-2323)
IEEE DOI 2201
Training, Image recognition, Refining, Estimation, Gait recognition, silhouette-based, multi-task BibRef

Su, J.R.[Jing-Ran], Zhao, Y.[Yang], Li, X.L.[Xue-Long],
Progressive Spatio-Temporal Feature Extraction Model for Gait Recognition,
ICIP21(1004-1008)
IEEE DOI 2201
Adaptation models, Image recognition, Fuses, Biological system modeling, Feature extraction, spatiotemporal feature extraction BibRef

Chen, Y.F.[Yi-Fan], Zhao, Y.[Yang], Li, X.L.[Xue-Long],
Effective Gait Feature Extraction Using Temporal Fusion and Spatial Partial,
ICIP21(1244-1248)
IEEE DOI 2201
Legged locomotion, Emotion recognition, Image recognition, Fuses, Feature extraction, Finite element analysis, Gait Recognition, Fine-grained Feature Extraction BibRef

Delgado-Escaño, R.[Rubén], Castro, F.M.[Francisco M.], Guil, N.[Nicolás], Kalogeiton, V.[Vicky], Marín-Jiménez, M.J.[Manuel J.],
Multimodal Gait Recognition Under Missing Modalities,
ICIP21(3003-3007)
IEEE DOI 2201
Image processing, Logic gates, Sensors, Gait recognition, Optical flow BibRef

Zhang, S.X.[Shao-Xiong], Wang, Y.H.[Yun-Hong], Li, A.[Annan],
Cross-View Gait Recognition with Deep Universal Linear Embeddings,
CVPR21(9091-9100)
IEEE DOI 2111
Legged locomotion, Visualization, Linear approximation, Feature extraction, Solids, Nonlinear dynamical systems, Task analysis BibRef

Yu, J., Xia, C., Xie, J., Zhang, H.,
Research on Feature Importance of Gait Mechanomyography Signal Based on Random Forest,
CVIDL20(191-196)
IEEE DOI 2102
accelerometers, biomechanics, electromyography, feature extraction, gait analysis, medical signal processing, muscle, random forest BibRef

Fan, C., Peng, Y., Cao, C., Liu, X., Hou, S., Chi, J., Huang, Y., Li, Q., He, Z.,
GaitPart: Temporal Part-Based Model for Gait Recognition,
CVPR20(14213-14221)
IEEE DOI 2008
Feature extraction, Convolution, Gait recognition, Biological system modeling, Task analysis, Kernel, Legged locomotion BibRef

Hosni, N., Amor, B.B.,
A Geometric ConvNet on 3D Shape Manifold for Gait Recognition,
Diff-CVML20(3725-3734)
IEEE DOI 2008
Pattern recognition BibRef

Mangalam, K., Adeli, E., Lee, K., Gaidon, A., Niebles, J.C.,
Disentangling Human Dynamics for Pedestrian Locomotion Forecasting with Noisy Supervision,
WACV20(2773-2782)
IEEE DOI 2006
Forecasting, Trajectory, Noise measurement, Task analysis, Predictive models, Vehicle dynamics, Dynamics BibRef

Pandey, N., Abdulla, W., Salcic, Z.,
Multi-view Gait recognition using sparse representation,
IVCNZ19(1-6)
IEEE DOI 2004
feature extraction, gait analysis, image motion analysis, image representation, minimisation, minimization, biometrics BibRef

Kato, H.[Hirotaka], Hirayama, T.[Takatsugu], Ide, I.[Ichiro], Doman, K.[Keisuke], Kawanishi, Y.[Yasutomo], Deguchi, D.[Daisuke], Murase, H.[Hiroshi],
More-natural Mimetic Words Generation for Fine-grained Gait Description,
MMMod20(II:214-225).
Springer DOI 2003
BibRef

Nouredanesh, M.[Mina], Li, A.W.[Aaron W.], Godfrey, A.[Alan], Hoey, J.[Jesse], Tung, J.[James],
Chasing Feet in the Wild: A Proposed Egocentric Motion-Aware Gait Assessment Tool,
ACVR18(VI:176-192).
Springer DOI 1905
BibRef

Dehzangi, O., Sahu, V.,
IMU-Based Robust Human Activity Recognition using Feature Analysis, Extraction, and Reduction,
ICPR18(1402-1407)
IEEE DOI 1812
Feature extraction, Legged locomotion, Activity recognition, Accelerometers, Dimensionality reduction, Kernel, Generalization. BibRef

Narváez, F.[Fabián], Árbito, F.[Fernando], Proaño, R.[Ricardo],
A Quaternion-Based Method to IMU-to-Body Alignment for Gait Analysis,
DHM18(217-231).
Springer DOI 1807
BibRef

Evans, M., Colyer, S., Cosker, D., Salo, A.,
Foot Contact Timings and Step Length for Sprint Training,
WACV18(1652-1660)
IEEE DOI 1806
gait analysis, motion measurement, sport, biomechanics, coaching staff, computer vision based approach, Tracking BibRef

Liu, D.[Dan], Ye, M.[Mao], Li, X.D.[Xu-Dong], Zhang, F.[Feng], Lin, L.[Lan],
Memory-based Gait Recognition,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Yao, L., Kusakunniran, W., Wu, Q., Zhang, J., Tang, Z.,
Robust Gait Recognition under Unconstrained Environments Using Hybrid Descriptions,
DICTA17(1-7)
IEEE DOI 1804
clothing, feature extraction, gait analysis, image motion analysis, image sequences, video signal processing, Gait Energy Image, Videos BibRef

Matsumoto, R., Yoshimura, H., Nishiyama, M., Iwai, Y.,
Feature extraction using gaze of participants for classifying gender of pedestrians in images,
ICIP17(3545-3549)
IEEE DOI 1803
Atmospheric measurements, Feature extraction, Kernel, Particle measurements, Task analysis, Training, Visualization, Gender BibRef

Kato, H., Hirayama, T., Kawanishi, Y., Doman, K., Ide, I., Deguchi, D., Murase, H.,
Toward Describing Human Gaits by Onomatopoeias,
AMFG17(1573-1580)
IEEE DOI 1802
Computational modeling, Feature extraction, Kinetic theory, Legged locomotion, Videos, Visualization BibRef

Yeoh, T.[Tze_Wei], Aguirre, H.E.[Hernán E.], Tanaka, K.[Kiyoshi],
Stacked Progressive Auto-Encoders for Clothing-Invariant Gait Recognition,
CAIP17(II: 151-161).
Springer DOI 1708
BibRef

Yu, S., Wang, Q.[Qing], Shen, L.L.[Lin-Lin], Huang, Y.Z.[Yong-Zhen],
View invariant gait recognition using only one uniform model,
ICPR16(889-894)
IEEE DOI 1705
Computational modeling, Feature extraction, Gait recognition, Legged locomotion, Probes, Training, Transforms BibRef

Matin, A., Paul, J., Sayeed, T.,
Segment based co-factor detection and elimination for effective gait recognition,
IVPR17(1-5)
IEEE DOI 1704
Databases BibRef

Kellokumpu, V.[Vili], Särkiniemi, M.[Markus], Zhao, G.Y.[Guo-Ying],
Affective Gait Recognition and Baseline Evaluation from Real World Samples,
SFBA16(I: 567-575).
Springer DOI 1704
BibRef

Binsaadoon, A.G.[Amer G.], El-Alfy, E.S.M.[El-Sayed M.],
Multi-Kernel Fuzzy-Based Local Gabor Patterns for Gait Recognition,
ISVC16(I: 790-799).
Springer DOI 1701
BibRef

Manikashani, P.[Peyman], Boyd, J.E.[Jeffrey E.],
A Phase-Entrained Particle Filter for Audio-Locomotion Synchronization,
CRV16(242-249)
IEEE DOI 1612
gait analysis; particle filter; sonification; syncrhonization BibRef

Liang, G., Li, Q., Kang, X.,
Pedestrian detection via a leg-driven physiology framework,
ICIP16(2926-2930)
IEEE DOI 1610
Context BibRef

Lai, C.Y.[Cheng-Yuan], McMahan, R.P., Hall, J.,
March-and-Reach: A realistic ladder climbing technique,
3DUI15(15-18)
IEEE DOI 1511
gait analysis BibRef

Yeoh, T.W.[Tze Wei], Zapotecas-Martínez, S.[Saúl], Akimoto, Y.[Youhei], Aguirre, H.E.[Hernán E.], Tanaka, K.[Kiyoshi],
Feature Selection in Gait Classification Using Geometric PSO Assisted by SVM,
CAIP15(II:566-578).
Springer DOI 1511
BibRef

Kappel, M.[Moritz], Golyanik, V.[Vladislav], Elgharib, M.[Mohamed], Henningson, J.O.[Jann-Ole], Seidel, H.P.[Hans-Peter], Castillo, S.[Susana], Theobalt, C.[Christian], Magnor, M.[Marcus],
High-Fidelity Neural Human Motion Transfer from Monocular Video,
CVPR21(1541-1550)
IEEE DOI 2111
Deep learning, Visualization, Codes, Shape, Image synthesis, Clothing BibRef

Alldieck, T.[Thiemo], Kassubeck, M.[Marc], Wandt, B.[Bastian], Rosenhahn, B.[Bodo], Magnor, M.[Marcus],
Optical Flow-Based 3D Human Motion Estimation from Monocular Video,
GCPR17(347-360).
Springer DOI 1711
BibRef

Zell, P.[Petrissa], Wandt, B.[Bastian], Rosenhahn, B.[Bodo],
Joint 3D Human Motion Capture and Physical Analysis from Monocular Videos,
Cognition17(17-26)
IEEE DOI 1709
BibRef
Earlier: A1, A3, Only:
A Physics-Based Statistical Model for Human Gait Analysis,
GCPR15(169-180).
Springer DOI 1511
Cameras, Computational modeling, Optimization, Solid modeling, Torque. BibRef

Iwashita, Y.[Yumi], Sakano, H.[Hitoshi], Kurazume, R.[Ryo],
Gait Recognition Robust to Speed Transition Using Mutual Subspace Method,
CIAP15(I:141-149).
Springer DOI 1511
BibRef

Derlatka, M.[Marcin], Bogdan, M.[Mariusz],
Fusion of Static and Dynamic Parameters at Decision Level in Human Gait Recognition,
PReMI15(515-524).
Springer DOI 1511
BibRef

Rida, I.[Imad], Bouridane, A.[Ahmed], Marcialis, G.L.[Gian Luca], Tuveri, P.[Pierluigi],
Improved Human Gait Recognition,
CIAP15(II:119-129).
Springer DOI 1511
BibRef

Makihara, Y., Mansur, A., Muramatsu, D., Uddin, Z., Yagi, Y.,
Multi-view discriminant analysis with tensor representation and its application to cross-view gait recognition,
FG15(1-8)
IEEE DOI 1508
gait analysis BibRef

Kondo, T., Kato, K., Yamamoto, K.,
A proposal of ambient light estimation methods for skin region detection,
FCV15(1-6)
IEEE DOI 1506
gait analysis BibRef

Pu, R.[Rui], Wang, Y.H.[Yun-Hong],
2-D Structure-Based Gait Recognition in Video Using Incremental GMM-HMM,
Gait14(I: 58-70).
Springer DOI 1504
BibRef

Wang, T.[Ting], Dune, C.[Claire], Merlet, J.P.[Jean-Pierre], Gorce, P.[Philippe], Sacco, G.[Guillaume], Robert, P.[Philippe], Turpin, J.M.[Jean-Michel], Teboul, B.[Bernard], Marteu, A.[Audrey], Guerin, O.[Olivier],
A New Application of Smart Walker for Quantitative Analysis of Human Walking,
ACVR14(464-480).
Springer DOI 1504
BibRef

Derbel, A., Chetouani, A., Treuillet, S., Emile, B., Mansouri, N., Ben Jemaa, Y.[Yousra],
Interest lower body point's detection for markerless gait analysis,
IPTA14(1-6)
IEEE DOI 1503
computer vision BibRef

Tafazzoli, F.[Faezeh], Bebis, G.N.[George N.], Louis, S.[Sushil], Hussain, M.[Muhammad],
Improving Human Gait Recognition Using Feature Selection,
ISVC14(II: 830-840).
Springer DOI 1501
BibRef

de Cann, B.[Brian], Ross, A.[Arun], Culp, M.[Mark],
On Clustering Human Gait Patterns,
ICPR14(1794-1799)
IEEE DOI 1412
Clustering algorithms BibRef

Deng, X.M.[Xiao-Ming], Xia, S.H.[Shi-Hong], Wang, W.Z.[Wen-Zhong], Wang, Z.Q.[Zhao-Qi], Chang, L.[Liang], Wang, H.A.[Hong-An],
Automatic Gait Motion Capture with Missing-Marker Fillings,
ICPR14(2507-2512)
IEEE DOI 1412
Cameras BibRef

Yang, Y.Z.[Ya-Zhou], Tu, D.[Dan], Li, G.H.[Guo-Hui],
Gait Recognition Using Flow Histogram Energy Image,
ICPR14(444-449)
IEEE DOI 1412
Computer vision BibRef

Okada, T., Yamazoe, H., Mitsugami, I., Yagi, Y.,
Preliminary Analysis of Gait Changes That Correspond to Gaze Directions,
ACPR13(788-792)
IEEE DOI 1408
gait analysis BibRef

Sengupta, S., Halder, U., Panda, R., Chowdhury, A.S.,
A frequency domain approach to silhouette based gait recognition,
NCVPRIPG13(1-4)
IEEE DOI 1408
Fourier transforms BibRef

Deepak, N.A., Hariharan, R., Sinha, U.N.,
Analysing gait sequences using Latent Dirichlet Allocation for certain human actions,
NCVPRIPG13(1-4)
IEEE DOI 1408
gait analysis BibRef

Nakazawa, M., Mitsugami, I., Yamazoe, H., Yagi, Y.,
Distinguishing Pedestrians Facing to the Front and the Side by Gait Observation,
ACPR13(486-490)
IEEE DOI 1408
gait analysis BibRef

Lombardi, S.[Stephen], Nishino, K.[Ko], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi],
Two-Point Gait: Decoupling Gait from Body Shape,
ICCV13(1041-1048)
IEEE DOI 1403
Gait Recognition BibRef

Jeevan, M., Jain, N.[Neha], Hanmandlu, M., Chetty, G.[Girija],
Gait recognition based on gait pal and pal entropy image,
ICIP13(4195-4199)
IEEE DOI 1402
Gait Pal and Pal Entropy Image (GPPE);Gait Recognition BibRef

Yang, C.[Cheng], Ugbolue, U.[Ukadike], Carse, B.[Bruce], Stankovic, V.[Vladimir], Stankovic, L.[Lina], Rowe, P.[Philip],
Multiple marker tracking in a single-camera system for gait analysis,
ICIP13(3128-3131)
IEEE DOI 1402
Gait analysis; Marker tracking; bStructural-Similarity BibRef

Derbel, A.[Ahmed], Mansouri, N.[Nabila], Ben Jemaa, Y.[Yousra], Emile, B.[Bruno], Treuillet, S.[Sylvie],
Comparative Study between Spatio/Temporal Descriptors for Pedestrians Recognition by Gait,
ICIAR13(35-42).
Springer DOI 1307
BibRef

Derbel, A.[Ahmed], Ben Jemaa, Y.[Yousra], Canals, R., Emile, B.[Bruno], Treuillet, S.[Sylvie], Ben Hamadou, A.,
Comparative study between color texture and shape descriptors for multi-camera pedestrians identification,
IPTA12(313-318)
IEEE DOI 1503
cameras BibRef

Chaubey, H., Hanmandlu, M., Vasikarla, S.,
Enhanced view invariant gait recognition using feature level fusion,
AIPR14(1-5)
IEEE DOI 1504
gait analysis BibRef

Kochhar, A., Gupta, D., Hanmandlu, M., Vasikarla, S.,
Novel features for silhouette based gait recognition systems,
AIPR12(1-6)
IEEE DOI 1307
feature extraction BibRef

Lorenzo, J.O.[Javier Ortells], Martín-Félez, R.[Raúl], Cárdenas, R.A.M.[Ramón A. Mollineda],
A Complexity Measure of Gait Perception,
IbPRIA13(492-499).
Springer DOI 1307
BibRef

Jung, D.U.[Da-Un], Oh, W.G.[Wean Geun], Choi, J.S.[Jong-Soo],
Model-based gait tracking method: A review of recent development gesture interaction,
FCV13(250-253).
IEEE DOI 1304
BibRef

Schuldhaus, D.[Dominik], Kugler, P.[Patrick], Jensen, U.[Ulf], Eskofier, B.[Bjoern], Schlarb, H.[Heiko], Leible, M.[Magnus],
Classification of surfaces and inclinations during outdoor running using shoe-mounted inertial sensors,
ICPR12(2258-2261).
WWW Link. 1302
Other sensors. not images. BibRef

Zhu, Y.Y.[Ying-Ying], Valmadre, J.[Jack], Lucey, S.[Simon],
Camera-less articulated trajectory reconstruction,
ICPR12(841-844).
WWW Link. 1302
Given 2D projections of articulated structure BibRef

Martin-Felez, R.[Raul], Orteils, J.[Javier], Mollineda, R.A.[Ramon A.],
Exploring the effects of video length on gait recognition,
ICPR12(3411-3414).
WWW Link. 1302
BibRef

Liu, Y.S.[Yu-Shu], Zhang, J.P.[Jun-Ping], Wang, C.[Chen], Wang, L.[Liang],
Multiple HOG templates for gait recognition,
ICPR12(2930-2933).
WWW Link. 1302
BibRef

Li, Y.[Yanan], Yin, Y.L.[Yi-Long], Liu, L.[Lili], Pang, S.H.[Shao-Hua], Yu, Q.H.[Qiu-Hong],
Semi-supervised Gait Recognition Based on Self-Training,
AVSS12(288-293).
IEEE DOI 1211
BibRef

Kolawole, A.[Akintola], Tavakkoli, A.[Alireza],
A Novel Gait Recognition System Based on Hidden Markov Models,
ISVC12(II: 125-134).
Springer DOI 1209
BibRef

Lin, H.W.[Hung-Wei], Hu, M.C.[Min-Chun], Wu, J.L.[Ja-Ling],
Gait-Based Action Recognition via Accelerated Minimum Incremental Coding Length Classifier,
MMMod12(266-276).
Springer DOI 1201
BibRef

Harle, R.[Robert], Cameron, J.[Jonathan], Lasenby, J.[Joan],
Foot Contact Detection for Sprint Training,
VECTaR10(297-306).
Springer DOI 1109
BibRef

Zhang, Z.[Zheng], Seah, H.S.[Hock Soon],
Real-time tracking of unconstrained full-body motion using Niching Swarm Filtering combined with local optimization,
HAU3D11(23-28).
IEEE DOI 1106
BibRef

Ishikawa, E.[Eri], Karungaru, S.[Stephen], Terada, K.[Kenji],
Gait features extraction method using image processing,
FCV11(1-6).
IEEE DOI 1102
BibRef

Watanabe, Y.[Yoshihiro], Hatanaka, T.[Tetsuo], Komuro, T.[Takashi], Ishikawa, M.[Masatoshi],
Human gait estimation using a wearable camera,
WACV11(276-281).
IEEE DOI 1101
BibRef

Kotsia, I.[Irene], Patras, I.[Ioannis],
Exploring the Similarities of Neighboring Spatiotemporal Points for Action Pair Matching,
ACCV12(III:624-635).
Springer DOI 1304
BibRef
And:
Support tensor action spotting,
ICIP12(1397-1400).
IEEE DOI 1302
BibRef
Earlier:
Relative Margin Support Tensor Machines for gait and action recognition,
CIVR10(446-453).
DOI Link 1007

See also Support tucker machines.
See also Higher rank Support Tensor Machines for visual recognition. BibRef

Olivier, A.H.[Anne-Hélène], Kulpa, R.[Richard], Pettré, J.[Julien], Crétual, A.[Armel],
A Velocity-Curvature Space Approach for Walking Motions Analysis,
MIG09(104-115).
Springer DOI 0911
BibRef

Zhang, Y.Y.[Yuan-Yuan], Yang, N.[Niqing], Li, W.[Wei], Wu, X.J.[Xiao-Juan], Ruan, Q.Q.[Qiu-Qi],
Gait Recognition Using Procrustes Shape Analysis and Shape Context,
ACCV09(III: 256-265).
Springer DOI 0909
BibRef

Tahmoush, D., Silvious, J.,
Remote detection of humans and animals,
AIPR09(1-8).
IEEE DOI 0910
BibRef

Ng, H.[Hu], Tan, W.H.[Wooi-Haw], Tong, H.L.[Hau-Lee], Abdullah, J.[Junaidi], Komiya, R.[Ryoichi],
Extraction and Classification of Human Gait Features,
IVIC09(596-606).
Springer DOI 0911
BibRef

Dadashi, F., Araabi, B.N., Soltanian-Zadeh, H.,
Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines,
CISP09(1-5).
IEEE DOI 0910
BibRef

Lawson, W.[Wallace], Duric, Z.[Zoran],
Analyzing Human Gait Using Patterns of Translation and Rotation,
ICIAR09(408-417).
Springer DOI 0907
BibRef

Lawson, W.[Wallace], Duric, Z.[Zoran], Wechsler, H.[Harry],
Gait Analysis using Independent Components of image motion,
FG08(1-6).
IEEE DOI 0809
BibRef

Tanaka, H., Wu, X., Arai, H., Koike, H.,
Modeling timing structures in gait image sequences using bottom-up clustering,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Lee, T.K.M.[Tracey K. M.], Belkhatir, M., Lee, P.A., Sanei, S.,
Fronto-normal gait incorporating accurate practical looming compensation,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Wu, C.C.[Chun-Chih], Medina, J.[Jose], Zordan, V.B.[Victor B.],
Simple Steps for Simply Stepping,
ISVC08(I: 97-106).
Springer DOI 0812
Animating stepping motion. BibRef

Lawson, W.[Wallace], Wechsler, H.[Harry],
Comparative Assessment of ICA Architectures for Gait Recognition,
BTAS07(1-5).
IEEE DOI 0709
BibRef

Romero-Moreno, M., Martínez-Trinidad, J.F.[J. Francisco], Carrasco-Ochoa, J.A.,
Gait Recognition Based on Silhouette, Contour and Classifier Ensembles,
CIARP08(527-534).
Springer DOI 0809
BibRef

Ding, T.[Tao],
A robust identification approach to gait recognition,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Srivastava, S.[Shruti], Sural, S.[Shamik],
Human Gait Recognition Using Temporal Slices,
PReMI07(592-599).
Springer DOI 0712
BibRef

Memisoglu, A.[Aydemir], Gudukbay, U.[Ugur], Ozguc, B.[Bulent],
Motion Control for Realistic Walking Behavior using Inverse Kinematics,
3DTV07(1-4).
IEEE DOI 0705
BibRef

Lee, S.K.[Seung-Kyu], Liu, Y.X.[Yan-Xi], Collins, R.T.[Robert T.],
Shape Variation-Based Frieze Pattern for Robust Gait Recognition,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Suk, H.I.[Heung-Il], Sin, B.K.[Bong-Kee],
HMM-Based Gait Recognition with Human Profiles,
SSPR06(596-603).
Springer DOI 0608
BibRef

Emoto, M., Hayashi, A., Suematsu, N., Iwata, K.,
View Independent Gait Identification Using a Particle Filter,
AVSBS06(74-74).
IEEE DOI 0611
BibRef

Ran, Y.[Yang], Chellappa, R.[Rama], Zheng, Q.F.[Qin-Fen],
Finding Gait in Space and Time,
ICPR06(IV: 586-589).
IEEE DOI 0609
BibRef

Chai, Y.M.[Yan-Mei], Wang, Q.[Qing], Jia, J.P.[Jing-Ping], Zhao, R.C.[Rong-Chun],
A Novel Gait Recognition Method Via Fusing Shape and Kinematics Features,
ISVC06(I: 80-89).
Springer DOI 0611
BibRef
Earlier:
A Novel Human Gait Recognition Method by Segmenting and Extracting the Region Variance Feature,
ICPR06(IV: 425-428).
IEEE DOI 0609
BibRef

Hu, S., Buxton, B.F.,
Using Temporal Coherence for Gait Pose Estimation From a Monocular Camera View,
BMVC05(xx-yy).
HTML Version. 0509
BibRef

Fusco, N.[Nicolas], Nicolas, G.[Guillaume], Multon, F.[Franck], Crétual, A.[Armel],
Simulation of Hemiplegic Subjects' Locomotion,
GW05(236-247).
Springer DOI 0505
BibRef

Das, S.R., Wilson, R.C., Lazarewicz, M.T., Finkel, L.H.,
Gait Recognition by Two-Stage Principal Component Analysis,
FGR06(579-584).
IEEE DOI 0604
BibRef

Zhao, G.Y.[Guo-Ying], Cui, L.[Li], Li, H.[Hua],
Combining Wavelet Velocity Moments and Reflective Symmetry for Gait Recognition,
IWBRS05(205).
Springer DOI 0601
BibRef

Zhao, G.Y.[Guo-Ying], Chen, R.[Rui], Liu, G.Y.[Guo-Yi], Li, H.[Hua],
Amplitude spectrum-based gait recognition,
AFGR04(23-28).
IEEE DOI 0411
BibRef

Chai, Y.M.[Yan-Mei], Ren, J.C.[Jin-Chang], Zhao, R.C.[Rong-Chun], Jia, J.P.[Jing-Ping],
Automatic Gait Recognition using Dynamic Variance Features,
FGR06(475-480).
IEEE DOI 0604
BibRef

Yang, H.D.[Hee-Deok], Sin, B.K.[Bong-Kee], Lee, S.W.[Seong-Whan],
Automatic Pedestrian Detection and Tracking for Real-Time Video Surveillance,
AVBPA03(242-250).
Springer DOI 0310
BibRef

Ye, B.[Bo], Wen, Y.[Yumei],
A New Gait Recognition Method Based on Body Contour,
ICARCV06(1-6).
IEEE DOI 0612
BibRef

Lie, A.S.[Agus Santoso], Shimomoto, R.[Ryo], Sakaguchi, S.[Shohei], Ishimura, T.[Toshiyuki], Enokida, S.[Shuichi], Wada, T.[Tomohito], Ejima, T.[Toshiaki],
Gait Recognition Using Spectral Features of Foot Motion,
AVBPA05(767).
Springer DOI 0509
BibRef

Lie, A.S.[Agus Santoso], Enokida, S.[Shuichi], Wada, T.[Tomohito], Ejima, T.[Toshiaki],
Magnitude and Phase Spectra of Foot Motion for Gait Recognition,
CAIP05(390).
Springer DOI 0509
BibRef

Fei, H., Reid, I.D.[Ian D.],
Dynamic Classifier for Non-rigid Human motion analysis,
BMVC04(xx-yy).
HTML Version. 0508
BibRef

Roy Chowdhury, A.K.[Amit K.],
A Measure of Deformability of Shapes, with Applications to Human Motion Analysis,
CVPR05(I: 398-404).
IEEE DOI 0507
BibRef

Cabo, J.M., Salgado, L., Cabrera, J.,
Adaptive segmentation for gymnastic exercises based on change detection over multiresolution combined differences,
ICIP04(I: 337-340).
IEEE DOI 0505
BibRef

Buades, J.M., Perales, F.J., Gonzalez, M., Aguiló, A., Martinez, P.,
Human Body Analysis with Biomechanics Criteria,
AMDO04(239-248).
Springer DOI 0505
BibRef

Tanawongsuwan, R.[Rawesak], Bobick, A.[Aaron],
Performance Analysis of Time-Distance Gait Parameters under Different Speeds,
AVBPA03(715-724).
Springer DOI 0310
BibRef

Calow, R.[Roman], Michaelis, B.[Bernd], Al-Hamadi, A.[Ayoub],
Solutions for Model-Based Analysis of Human Gait,
DAGM03(540-547).
Springer DOI 0310

See also New Multi-camera Based Facial Expression Analysis Concept, A. BibRef

Davis, J.W.[James W.],
Visual Categorization of Children and Adult Walking Styles,
AVBPA01(295).
Springer DOI 0310
BibRef

Davis, J.W., Taylor, S.R.,
Analysis and recognition of walking movements,
ICPR02(I: 315-318).
IEEE DOI 0211
BibRef

Tassone, E., West, G.A.W., Venkatesh, S.,
Temporal PDMs for gait classification,
ICPR02(II: 1065-1068).
IEEE DOI 0211
BibRef

Meyer, D., Posl, J., Niemann, H.,
Gait Classification with HMMS for Trajectories of Body Parts Extracted by Mixture Densities,
BMVC98(459-468).
PS File. BibRef 9800

Denzler, J.[Joachim], Niemann, H.[Heinrich],
Real-time pedestrian tracking in natural scenes,
CAIP97(42-49).
Springer DOI 9709
BibRef

Meyer, D., Denzler, J.[Joachim], Niemann, H.[Heinrich],
Model Based Extraction of Articulated Objects in Image Sequences for Gait Analysis,
ICIP97(III: 78-81).
IEEE DOI
PS File. BibRef 9700

Cheng, J.C., and Moura, J.,
Tracking Human Walking in Dynamic Scenes,
ICIP97(I: 137-140).
IEEE DOI BibRef 9700

Geiger, D., Liu, T.L.[Tyng-Luh],
Recognizing articulated objects with information theoretic methods,
AFGR96(45-50).
IEEE DOI 9610
BibRef

Qian, R.J., and Huang, T.S.,
Motion Analysis of Articulated Objects with Applications to Human Ambulatory Patterns,
DARPA92(549-553). BibRef 9200
And:
Motion Analysis of Human Ambulatory Patterns,
ICPR92(I:220-223).
IEEE DOI Motion, Walking. BibRef

Niyogi, S.A.,
Spatiotemporal junction analysis for motion boundary detection,
ICIP95(III: 468-471).
IEEE DOI 9510
BibRef

Niyogi, S.A., Adelson, E.H.,
Analyzing and Recognizing Walking Figures in XYT,
CVPR94(469-474).
IEEE DOI BibRef 9400
And: Vismod-223, 1993.
PS File. BibRef
And:
Analyzing Gait with Spatiotemporal Surfaces,
Vismod-290, 1994.
PS File. Walking Motion. BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Walking, Gait Recognition, Neural Networks, CNN, Learning .

Last update:Jan 20, 2025 at 11:36:25