Chen, Z.,
Lee, H.J.,
Knowledge-Guided Visual Perception of 3-D Human Gait from a
Single Image Sequence,
SMC(22), 1992, pp. 336-342.
BibRef
9200
Earlier: A2, A1:
Optimal Search Procedures for 3D Human Movement Determination,
CAIA84(389-394).
BibRef
Sappa, A.D.[Angel D.],
Aifanti, N.[Niki],
Malassiotis, S.[Sotiris],
Strintzis, M.G.[Michael G.],
Prior Knowledge Based Motion Model Representation,
ELCVIA(5), No. 3, 2005, pp. 55-67.
DOI Link
0505
BibRef
Earlier:
Monocular 3D human body reconstruction towards depth augmentation of
television sequences,
ICIP03(III: 325-328).
IEEE DOI
0312
BibRef
Earlier:
3D Human Walking Modeling,
AMDO04(111-122).
Springer DOI
0505
BibRef
And:
3D gait estimation from monoscopic video,
ICIP04(III: 1963-1966).
IEEE DOI
0505
BibRef
Earlier:
Unsupervised motion classification by means of efficient feature
selection and tracking,
3DPVT04(912-917).
IEEE DOI
0412
Human walking modeling from monocular sequences.
Compute feature trajectories, find changes to get key frames.
Feature point trajectories for determing walking and running.
BibRef
Ioannidis, D.[Dimosthenis],
Tzovaras, D.[Dimitrios],
Moustakas, K.[Konstantinos],
Gait Identification using the 3D Protrusion Transform,
ICIP07(I: 349-352).
IEEE DOI
0709
BibRef
Igual, L.[Laura],
Lapedriza, À.[Àgata],
Borràs, R.[Ricard],
Robust gait-based gender classification using depth cameras,
JIVP(2012), No. 1, 2013, pp. 1.
DOI Link
1302
BibRef
Earlier: A3, A2, A1:
Depth Information in Human Gait Analysis:
An Experimental Study on Gender Recognition,
ICIAR12(II: 98-105).
Springer DOI
1206
BibRef
Kellokumpu, V.P.[Vili-Petteri],
Zhao, G.Y.[Guo-Ying],
Pietikäinen, M.[Matti],
Recognition of human actions using texture descriptors,
MVA(22), No. 5, September 2011, pp. 767-780.
WWW Link.
1108
BibRef
Earlier:
Dynamic textures for human movement recognition,
CIVR10(470-476).
DOI Link
1007
BibRef
Earlier:
Human Activity Recognition Using a Dynamic Texture Based Method,
BMVC08(xx-yy).
PDF File.
0809
See also Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions.
BibRef
Chen, J.[Jie],
Zhao, G.Y.[Guo-Ying],
Kellokumpu, V.P.[Vili-Petteri],
Pietikainen, M.[Matti],
Combining sparse and dense descriptors with temporal semantic
structures for robust human action recognition,
VECTaR11(1524-1531).
IEEE DOI
1201
BibRef
Kellokumpu, V.P.[Vili-Petteri],
Zhao, G.Y.[Guo-Ying],
Li, S.Z.[Stan Z.],
Pietikäinen, M.[Matti],
Dynamic Texture Based Gait Recognition,
ICB09(1000-1009).
Springer DOI
0906
BibRef
Zhao, G.Y.[Guo-Ying],
Liu, G.Y.[Guo-Yi],
Li, H.[Hua],
Pietikainen, M.,
3D Gait Recognition Using Multiple Cameras,
FGR06(529-534).
IEEE DOI
0604
BibRef
Zhao, G.Y.[Guo-Ying],
Cui, L.[Li],
Li, H.[Hua],
Pietikainen, M.[Matti],
Gait Recognition Using Fractal Scale and Wavelet Moments,
ICPR06(IV: 453-456).
IEEE DOI
0609
BibRef
Liu, N.[Nini],
Lu, J.W.[Ji-Wen],
Tan, Y.P.[Yap-Peng],
Joint Subspace Learning for View-Invariant Gait Recognition,
SPLetters(18), No. 7, July 2011, pp. 431-434.
IEEE DOI
1101
BibRef
Liu, N.[Nini],
Lu, J.W.[Ji-Wen],
Yang, G.[Gao],
Tan, Y.P.[Yap-Peng],
Robust gait recognition via discriminative set matching,
JVCIR(24), No. 4, May 2013, pp. 439-447.
Elsevier DOI
1305
Multiview gait recognition; Subspace distance; Set-to-set matching
BibRef
Liu, N.[Nini],
Lu, J.W.[Ji-Wen],
Tan, Y.P.[Yap-Peng],
Chen, Z.Z.[Zhen-Zhong],
Enhanced gait recognition based on weighted dynamic feature,
ICIP09(3581-3584).
IEEE DOI
0911
BibRef
Kusakunniran, W.[Worapan],
Wu, Q.A.[Qi-Ang],
Zhang, J.[Jian],
Li, H.D.[Hong-Dong],
Cross-View and Multi-View Gait Recognitions Based on View
Transformation Model Using Multi-Layer Perceptron,
PRL(33), No. 7, 1 May 2012, pp. 882-889.
Elsevier DOI
1203
BibRef
Earlier:
Multi-view Gait Recognition Based on Motion Regression Using Multilayer
Perceptron,
ICPR10(2186-2189).
IEEE DOI
1008
Award, ICPR.
BibRef
And:
Support vector regression for multi-view gait recognition based on
local motion feature selection,
CVPR10(974-981).
IEEE DOI
1006
BibRef
Earlier: A1, A2, A4, A3:
Multiple Views Gait Recognition Using View Transformation Model Based
on Optimized Gait Energy Image,
THEMIS09(1058-1064).
IEEE DOI
0910
BibRef
Earlier:
Automatic Gait Recognition Using Weighted Binary Pattern on Video,
AVSBS09(49-54).
IEEE DOI
0909
Gait recognition; Cross-view; Multi-view; View transformation model;
Multi-layer perceptron
BibRef
Yao, L.X.[Ling-Xiang],
Kusakunniran, W.[Worapan],
Wu, Q.[Qiang],
Zhang, J.[Jian],
Tang, Z.M.[Zhen-Min],
Yang, W.K.[Wan-Kou],
Robust gait recognition using hybrid descriptors based on Skeleton
Gait Energy Image,
PRL(150), 2021, pp. 289-296.
Elsevier DOI
2109
Gait recognition, Hybrid descriptor, SGEI
BibRef
Kusakunniran, W.[Worapan],
Wu, Q.A.[Qi-Ang],
Zhang, J.[Jian],
Li, H.D.[Hong-Dong],
Gait Recognition Under Various Viewing Angles Based on Correlated
Motion Regression,
CirSysVideo(22), No. 6, June 2012, pp. 966-980.
IEEE DOI
1206
BibRef
Earlier:
Pairwise Shape configuration-based PSA for gait recognition under small
viewing angle change,
AVSBS11(17-22).
IEEE DOI
1111
BibRef
Kusakunniran, W.[Worapan],
Wu, Q.A.[Qi-Ang],
Zhang, J.[Jian],
Action Recognition Based on Correlated Codewords of Body Movements,
DICTA17(1-8)
IEEE DOI
1804
correlation methods, feature extraction, image motion analysis,
image recognition, image representation, support vector machines,
BibRef
Kusakunniran, W.[Worapan],
Wu, Q.A.[Qi-Ang],
Zhang, J.[Jian],
Li, H.D.[Hong-Dong],
Gait Recognition Across Various Walking Speeds Using Higher Order Shape
Configuration Based on a Differential Composition Model,
SMC-B(42), No. 6, December 2012, pp. 1654-1668.
IEEE DOI
1212
BibRef
Earlier:
Speed-invariant gait recognition based on Procrustes Shape Analysis
using higher-order shape configuration,
ICIP11(545-548).
IEEE DOI
1201
BibRef
Kusakunniran, W.[Worapan],
Wu, Q.A.[Qi-Ang],
Zhang, J.[Jian],
Li, H.D.[Hong-Dong],
Wang, L.[Liang],
Recognizing Gaits Across Views Through Correlated Motion
Co-Clustering,
IP(23), No. 2, February 2014, pp. 696-709.
IEEE DOI
1402
approximation theory
BibRef
Hu, H.F.[Hai-Feng],
Enhanced Gabor Feature Based Classification Using a Regularized
Locally Tensor Discriminant Model for Multiview Gait Recognition,
CirSysVideo(23), No. 7, 2013, pp. 1274-1286.
IEEE DOI
1307
eigenvalues and eigenfunctions
BibRef
Hu, H.F.[Hai-Feng],
Multiview Gait Recognition Based on Patch Distribution Features and
Uncorrelated Multilinear Sparse Local Discriminant Canonical
Correlation Analysis,
CirSysVideo(24), No. 4, April 2014, pp. 617-630.
IEEE DOI
1405
feature extraction
BibRef
Milovanovic, M.,
Minovic, M.,
Starcevic, D.,
Walking in Colors: Human Gait Recognition Using Kinect and CBIR,
MultMedMag(20), No. 4, October 2013, pp. 28-36.
IEEE DOI
1403
content-based retrieval
BibRef
Rogez, G.,
Rihan, J.,
Guerrero, J.J.,
Orrite, C.,
Monocular 3-D Gait Tracking in Surveillance Scenes,
Cyber(44), No. 6, June 2014, pp. 894-909.
IEEE DOI
1406
Cameras
BibRef
Chen, X.[Xin],
Luo, X.Z.[Xi-Zhao],
Weng, J.[Jian],
Luo, W.Q.[Wei-Qi],
Li, H.T.[Hui-Ting],
Tian, Q.[Qi],
Multi-View Gait Image Generation for Cross-View Gait Recognition,
IP(30), 2021, pp. 3041-3055.
IEEE DOI
2103
Gait recognition, Generative adversarial networks,
Feature extraction, Generators, Training,
convolutional neural networks
BibRef
Chen, G.L.[Gui-Long],
Huang, J.Y.[Jia-Yi],
Chen, G.[Guanghai],
Chen, X.[Xin],
Deng, X.L.[Xiao-Ling],
Lan, Y.[Yubin],
Long, Y.B.[Yong-Bing],
Tian, Q.[Qi],
GaitGMT: Global feature mapping transformer for gait recognition,
JVCIR(100), 2024, pp. 104139.
Elsevier DOI
2405
Gait recognition, Deep learning, Vision transformer, Global feature mapping
BibRef
Chen, X.[Xin],
Yang, T.Q.[Tian-Qi],
Xu, J.M.[Jia-Ming],
Cross-view gait recognition based on human walking trajectory,
JVCIR(25), No. 8, 2014, pp. 1842-1855.
Elsevier DOI
1411
Gait recognition
BibRef
Chen, X.[Xin],
Xu, J.M.[Jia-Ming],
Uncooperative gait recognition: Re-ranking based on sparse coding and
multi-view hypergraph learning,
PR(53), No. 1, 2016, pp. 116-129.
Elsevier DOI
1602
Uncooperative gait recognition
BibRef
Chen, X.[Xin],
Xu, J.M.[Jia-Ming],
Weng, J.[Jian],
Multi-gait recognition using hypergraph partition,
MVA(28), No. 1-2, February 2017, pp. 117-127.
WWW Link.
1702
BibRef
Chen, X.[Xin],
Weng, J.[Jian],
Lu, W.,
Xu, J.M.[Jia-Ming],
Multi-Gait Recognition Based on Attribute Discovery,
PAMI(40), No. 7, July 2018, pp. 1697-1710.
IEEE DOI
1806
Data privacy, Data security, Feature extraction, Gait recognition,
Hidden Markov models, Legged locomotion, Pose estimation,
latent structural SVM
BibRef
Hofmann, M.[Martin],
Geiger, J.[Jürgen],
Bachmann, S.[Sebastian],
Schuller, B.[Björn],
Rigoll, G.[Gerhard],
The TUM Gait from Audio, Image and Depth (GAID) database:
Multimodal recognition of subjects and traits,
JVCIR(25), No. 1, 2014, pp. 195-206.
Elsevier DOI
1502
Dataset, Gait. Gait recognition
BibRef
Chattopadhyay, P.[Pratik],
Roy, A.[Aditi],
Sural, S.[Shamik],
Mukhopadhyay, J.[Jayanta],
Pose Depth Volume extraction from RGB-D streams for frontal gait
recognition,
JVCIR(25), No. 1, 2014, pp. 53-63.
Elsevier DOI
1502
Frontal gait recognition
BibRef
Michel, D.[Damien],
Panagiotakis, C.[Costas],
Argyros, A.A.[Antonis A.],
Tracking the articulated motion of the human body with two RGBD cameras,
MVA(26), No. 1, January 2015, pp. 41-54.
WWW Link.
1503
BibRef
Ahmed, F.[Faisal],
Paul, P.P.[Padma Polash],
Gavrilova, M.L.[Marina L.],
DTW-based kernel and rank-level fusion for 3D gait recognition using
Kinect,
VC(31), No. 6-8, June 2015, pp. 915-924.
WWW Link.
1506
See also Evolutionary fusion of local texture patterns for facial expression recognition.
BibRef
López-Fernández, D.,
Madrid-Cuevas, F.J.,
Carmona-Poyato, A.,
Muñoz-Salinas, R.,
Medina-Carnicer, R.[Rafael],
Entropy volumes for viewpoint-independent gait recognition,
MVA(26), No. 7-8, November 2015, pp. 1079-1094.
Springer DOI
1511
BibRef
López-Fernández, D.,
Madrid-Cuevas, F.J.,
Carmona-Poyato, A.,
Muñoz-Salinas, R.,
Medina-Carnicer, R.,
A new approach for multi-view gait recognition on unconstrained paths,
JVCIR(38), No. 1, 2016, pp. 396-406.
Elsevier DOI
1605
Gait recognition
BibRef
Castro, F.M.[Francisco M.],
Marin-Jimenez, M.J.[Manuel J.],
Medina-Carnicer, R.[Rafael],
Pyramidal Fisher Motion for Multiview Gait Recognition,
ICPR14(1692-1697)
IEEE DOI
1412
Cameras
BibRef
Hsu, S.C.[Shih-Chung],
Huang, J.Y.[Jun-Yang],
Kao, W.C.[Wei-Chia],
Huang, C.L.[Chung-Lin],
Human body motion parameters capturing using kinect,
MVA(26), No. 7-8, November 2015, pp. 919-932.
Springer DOI
1511
BibRef
Kastaniotis, D.[Dimitris],
Theodorakopoulos, I.[Ilias],
Theoharatos, C.[Christos],
Economou, G.[George],
Fotopoulos, S.[Spiros],
A framework for gait-based recognition using Kinect,
PRL(68, Part 2), No. 1, 2015, pp. 327-335.
Elsevier DOI
1512
Keywords
BibRef
Kastaniotis, D.[Dimitris],
Theodorakopoulos, I.[Ilias],
Economou, G.[George],
Fotopoulos, S.[Spiros],
Gait based recognition via fusing information from Euclidean and
Riemannian manifolds,
PRL(84), No. 1, 2016, pp. 245-251.
Elsevier DOI
1612
Pose-based gait recognition
See also Pose-based human action recognition via sparse representation in dissimilarity space.
BibRef
López-Fernández, D.,
Madrid-Cuevas, F.,
Carmona-Poyato, A.,
Marín-Jiménez, M.J.,
Muñoz-Salinas, R.,
Medina-Carnicer, R.,
Viewpoint-independent gait recognition through morphological
descriptions of 3D human reconstructions,
IVC(48-49), No. 1, 2016, pp. 1-13.
Elsevier DOI
1604
Gait recognition
BibRef
Yang, K.[Ke],
Dou, Y.[Yong],
Lv, S.[Shaohe],
Zhang, F.[Fei],
Lv, Q.[Qi],
Relative distance features for gait recognition with Kinect,
JVCIR(39), No. 1, 2016, pp. 209-217.
Elsevier DOI
1608
Relative distance feature
BibRef
López-Fernández, D.[David],
Contributions to Gait Recognition Using Multiple-Views,
ELCVIA(15), No. 2, 2016, pp. 22-23.
DOI Link
1611
BibRef
Luo, J.[Jian],
Tang, J.[Jin],
Tjahjadi, T.[Tardi],
Xiao, X.M.[Xiao-Ming],
Robust arbitrary view gait recognition based on parametric 3D human
body reconstruction and virtual posture synthesis,
PR(60), No. 1, 2016, pp. 361-377.
Elsevier DOI
1609
Gait recognition
BibRef
Tang, J.[Jin],
Luo, J.[Jian],
Tjahjadi, T.[Tardi],
Guo, F.,
Robust Arbitrary-View Gait Recognition Based on 3D Partial Similarity
Matching,
IP(26), No. 1, January 2017, pp. 7-22.
IEEE DOI
1612
feature extraction
BibRef
Benedek, C.,
Gálai, B.,
Nagy, B.,
Jankó, Z.,
Lidar-Based Gait Analysis and Activity Recognition in a 4D
Surveillance System,
CirSysVideo(28), No. 1, January 2018, pp. 101-113.
IEEE DOI
1801
Databases, Laser radar, Legged locomotion, Surveillance,
Trajectory, Visualization, multibeam Lidar
BibRef
Li, Q.N.[Qian-Nan],
Wang, Y.F.[Ya-Fang],
Sharf, A.[Andrei],
Cao, Y.[Ya],
Tu, C.H.[Chang-He],
Chen, B.Q.[Bao-Quan],
Yu, S.Y.[Sheng-Yuan],
Classification of gait anomalies from kinect,
VC(34), No. 2, February 2018, pp. 229-241.
Springer DOI
1802
BibRef
Xu, W.J.[Wan-Jiang],
Zhu, C.Y.[Can-Yan],
Wang, Z.[Ziou],
Multiview max-margin subspace learning for cross-view gait
recognition,
PRL(107), 2018, pp. 75-82.
Elsevier DOI
1805
Subspace learning, Gait recognition, Transform matrices
BibRef
Switonski, A.[Adam],
Krzeszowski, T.[Tomasz],
Josinski, H.[Henryk],
Kwolek, B.[Bogdan],
Wojciechowski, K.[Konrad],
Gait recognition on the basis of markerless motion tracking and DTW
transform,
IET-Bio(7), No. 5, September 2018, pp. 415-422.
DOI Link
1809
BibRef
Krzeszowski, T.[Tomasz],
Michalczuk, A.[Agnieszka],
Kwolek, B.[Bogdan],
Switonski, A.[Adam],
Josinski, H.[Henryk],
Gait recognition based on marker-less 3D motion capture,
AVSS13(232-237)
IEEE DOI
1311
Biological system modeling
BibRef
Michalczuk, A.[Agnieszka],
Switonski, A.[Adam],
Josinski, H.[Henryk],
Polanski, A.[Andrzej],
Wojciechowski, K.[Konrad],
Gait Identification Based on MPCA Reduction of a Video Recordings Data,
ICCVG12(525-532).
Springer DOI
1210
BibRef
Krzeszowski, T.[Tomasz],
Kwolek, B.[Bogdan],
Michalczuk, A.[Agnieszka],
Switonski, A.[Adam],
Josinski, H.[Henryk],
View Independent Human Gait Recognition Using Markerless 3D Human
Motion Capture,
ICCVG12(491-500).
Springer DOI
1210
BibRef
Polanski, A.[Andrzej],
Switonski, A.[Adam],
Josinski, H.[Henryk],
Jedrasiak, K.[Karol],
Wojciechowski, K.[Konrad],
Estimation System for Forces and Torques in a Biped Motion,
ICCVG10(I: 185-192).
Springer DOI
1009
BibRef
Switonski, A.[Adam],
Josinski, H.[Henryk],
Jedrasiak, K.[Karol],
Polanski, A.[Andrzej],
Wojciechowski, K.[Konrad],
Classification of Poses and Movement Phases,
ICCVG10(I: 193-200).
Springer DOI
1009
BibRef
Vandersmissen, B.[Baptist],
Knudde, N.[Nicolas],
Jalalvand, A.[Azarakhsh],
Couckuyt, I.[Ivo],
Bourdoux, A.[André],
de Neve, W.[Wesley],
Dhaene, T.[Tom],
Indoor Person Identification Using a Low-Power FMCW Radar,
GeoRS(56), No. 7, July 2018, pp. 3941-3952.
IEEE DOI
1807
Gait with micro-doppler.
Cameras, Doppler effect, Doppler radar, Legged locomotion,
Machine learning, Robustness, Convolutional neural network (CNN),
person identification
BibRef
Tong, S.B.[Sui-Bing],
Fu, Y.Z.[Yu-Zhuo],
Ling, H.F.[He-Fei],
Cross-view gait recognition based on a restrictive triplet network,
PRL(125), 2019, pp. 212-219.
Elsevier DOI
1909
Cross-view, Gait recognition, View variations, RTN
BibRef
Wang, X.H.[Xiu-Hui],
Feng, S.L.[Shi-Ling],
Multi-perspective gait recognition based on classifier fusion,
IET-IPR(13), No. 11, 19 September 2019, pp. 1885-1891.
DOI Link
1909
BibRef
Bai, X.R.[Xue-Ru],
Hui, Y.[Ye],
Wang, L.[Li],
Zhou, F.[Feng],
Radar-Based Human Gait Recognition Using Dual-Channel Deep
Convolutional Neural Network,
GeoRS(57), No. 12, December 2019, pp. 9767-9778.
IEEE DOI
1912
Bones, Feature extraction, Radar, Gait recognition, Torso,
Legged locomotion, Training,
short-time Fourier transform (STFT)
BibRef
Ji, H.R.[Hao-Ran],
Hou, C.P.[Chun-Ping],
Yang, Y.[Yang],
Fioranelli, F.[Francesco],
Lang, Y.[Yue],
A One-Class Classification Method for Human Gait Authentication Using
Micro-Doppler Signatures,
SPLetters(28), 2021, pp. 2182-2186.
IEEE DOI
2112
Authentication, Training, Radar, Generative adversarial networks,
Data models, Spectrogram, Convolution, Gait authentication,
one class classification
BibRef
Zhong, J.X.[Jin-Xiao],
Jin, L.N.[Liang-Nian],
Mao, Q.[Qiang],
Real-time recognition of human motions using multidimensional
features in ultrawideband biological radar,
IET-Bio(11), No. 1, 2022, pp. 1-9.
DOI Link
2112
BibRef
Hor, S.[Soheil],
Pilanci, M.[Mert],
Arbabian, A.[Amin],
A Data-Driven Waveform Adaptation Method for Mm-Wave Gait
Classification at the Edge,
SPLetters(29), 2022, pp. 26-30.
IEEE DOI
2202
Q-learning, Program processors,
Signal processing algorithms, Dynamic scheduling, reinforcement learning
BibRef
Chao, H.Q.[Han-Qing],
Wang, K.[Kun],
He, Y.W.[Yi-Wei],
Zhang, J.P.[Jun-Ping],
Feng, J.F.[Jian-Feng],
GaitSet:
Cross-View Gait Recognition Through Utilizing Gait As a Deep Set,
PAMI(44), No. 7, July 2022, pp. 3467-3478.
IEEE DOI
2206
Gait recognition, Feature extraction, Legged locomotion,
Deep learning, Pipelines, Data mining, Gait recognition,
deep learning
BibRef
Huang, T.H.[Tian-Huan],
Ben, X.Y.[Xian-Ye],
Gong, C.[Chen],
Zhang, B.C.[Bao-Chang],
Yan, R.[Rui],
Wu, Q.[Qiang],
Enhanced Spatial-Temporal Salience for Cross-View Gait Recognition,
CirSysVideo(32), No. 10, October 2022, pp. 6967-6980.
IEEE DOI
2210
Feature extraction, Convolution, Solid modeling, Gait recognition,
Data mining, Correlation, Gait recognition, cross view,
multi-scale salient feature extraction
BibRef
Hassan, S.[Shahid],
Wang, X.R.[Xiang-Rong],
Ishtiaq, S.[Saima],
Ullah, N.[Nasim],
Mohammad, A.[Alsharef],
Noorwali, A.[Abdulfattah],
Human Activity Classification Based on Dual Micro-Motion Signatures
Using Interferometric Radar,
RS(15), No. 7, 2023, pp. 1752.
DOI Link
2304
BibRef
Rao, P.S.[P. Sankara],
Parida, P.[Priyadarsan],
Sahu, G.[Gupteswar],
Dash, S.[Sonali],
A multi-view human gait recognition using hybrid whale and gray wolf
optimization algorithm with a random forest classifier,
IVC(136), 2023, pp. 104721.
Elsevier DOI
2308
Gait recognition, Gradient gait energy image,
Hybrid whale and gray wolf optimization algorithm, And random forest classifier
BibRef
Zeng, Z.Y.[Zhi-Yuan],
Liang, X.D.[Xing-Dong],
Li, Y.L.[Yan-Lei],
Dang, X.W.[Xiang-Wei],
Vulnerable Road User Skeletal Pose Estimation Using mmWave Radars,
RS(16), No. 4, 2024, pp. 633.
DOI Link
2402
BibRef
Zheng, J.[Jinkai],
Liu, X.C.[Xin-Chen],
Liu, W.[Wu],
He, L.X.[Ling-Xiao],
Yan, C.G.[Cheng-Gang],
Mei, T.[Tao],
Gait Recognition in the Wild with Dense 3D Representations and A
Benchmark,
CVPR22(20196-20205)
IEEE DOI
2210
Solid modeling, Shape, Biological system modeling,
Feature extraction, Cameras, Skeleton, Biometrics, Datasets and evaluation
BibRef
Sadeghzadehyazdi, N.,
Batabyal, T.,
Glandon, A.,
Dhar, N.K.,
Familoni, B.O.,
Iftekharuddin, K.M.,
Acton, S.T.,
Glidar3DJ: a View-Invariant Gait Identification via Flash Lidar Data
Correction,
ICIP19(2606-2610)
IEEE DOI
1910
gait recognition, lidar, feature correction
BibRef
Hosni, N.,
Drira, H.,
Chaieb, F.,
Amor, B.B.,
3D Gait Recognition based on Functional PCA on Kendall's Shape Space,
ICPR18(2130-2135)
IEEE DOI
1812
Trajectory, Shape, Space vehicles,
Principal component analysis, Geometry, Tools, 3D gait recognition,
Riemannian geometry
BibRef
Le, H.T.,
Phung, S.L.,
Bouzerdoum, A.,
Human Gait Recognition with Micro-Doppler Radar and Deep Autoencoder,
ICPR18(3347-3352)
IEEE DOI
1812
Doppler radar, Feature extraction, Wavelet transforms, Training,
Time-frequency analysis, Optimization, micro-Doppler radar,
Bayesian optimization
BibRef
Ozen, H.,
Boulgouris, N.V.,
Swash, R.,
Gait recognition based on 3D holoscopic gait energy image,
IC3D17(1-4)
IEEE DOI
1804
gait analysis, image motion analysis, object recognition,
3D holoscopic gait energy image, HGEI, gait recognition,
silhouette
BibRef
Altuntas, C.,
Turkmen, F.,
Ucar, A.,
Akgul, Y.A.,
Measurement And Analysis Of Gait By Using A Time-of-flight Camera,
ISPRS16(B3: 459-464).
DOI Link
1610
BibRef
Babaee, M.,
Rigoll, G.,
Babaee, M.,
Joint tracking and gait recognition of multiple people in video,
ICIP17(2592-2596)
IEEE DOI
1803
Feature extraction, Gait recognition, Hidden Markov models,
Support vector machines, Switches, Target tracking, Trajectory,
Multi-people tracking
BibRef
Wolf, T.,
Babaee, M.,
Rigoll, G.,
Multi-view gait recognition using 3D convolutional neural networks,
ICIP16(4165-4169)
IEEE DOI
1610
Clothing
BibRef
Ndayikengurukiye, D.[Didier],
Mignotte, M.[Max],
High-Frequency Spectral Energy Map Estimation Based Gait Analysis
System Using a Depth Camera for Pathology Detection,
ICIAR16(38-45).
Springer DOI
1608
BibRef
Zhang, H.[He],
Ye, C.[Cang],
An RGB-D Camera Based Walking Pattern Detection Method for Smart
Rollators,
ISVC15(I: 624-633).
Springer DOI
1601
BibRef
Wang, Y.,
Sun, J.,
Li, J.,
Zhao, D.,
Gait recognition based on 3D skeleton joints captured by kinect,
ICIP16(3151-3155)
IEEE DOI
1610
Circuits and systems
BibRef
Jiang, S.M.[Shu-Ming],
Wang, Y.F.[Yu-Fei],
Zhang, Y.Y.[Yuan-Yuan],
Sun, J.[Jiande],
Real Time Gait Recognition System Based on Kinect Skeleton Feature,
Gait14(I: 46-57).
Springer DOI
1504
BibRef
Prochazka, A.,
Schatz, M.,
Tupa, O.,
Yadollahi, M.,
Vysata, O.,
Walls, M.,
The MS kinect image and depth sensors use for gait features detection,
ICIP14(2271-2274)
IEEE DOI
1502
Accuracy
BibRef
Nguyen, H.A.[Hoang Anh],
Meunier, J.[Jean],
Video-based analysis of gait with side views,
IPTA14(1-8)
IEEE DOI
1503
BibRef
And:
Gait Analysis from Video: Camcorders vs. Kinect,
ICIAR14(II: 66-73).
Springer DOI
1410
BibRef
Krzeszowski, T.[Tomasz],
Switonski, A.[Adam],
Kwolek, B.[Bogdan],
Josinski, H.[Henryk],
Wojciechowski, K.[Konrad],
DTW-Based Gait Recognition from Recovered 3-D Joint Angles and
Inter-ankle Distance,
ICCVG14(356-363).
Springer DOI
1410
BibRef
Sivapalan, S.[Sabesan],
Chen, D.[Daniel],
Denman, S.[Simon],
Sridharan, S.[Sridha],
Fookes, C.[Clinton],
Histogram of Weighted Local Directions for Gait Recognition,
Biometrics13(125-130)
IEEE DOI
1309
BibRef
Earlier:
The Backfilled GEI: A Cross-Capture Modality Gait Feature for Frontal
and Side-View Gait Recognition,
DICTA12(1-8).
IEEE DOI
1303
Gait energy image;HOG;MDA;PCA;SRC;gait;local directional pattern
BibRef
Sivapalan, S.,
Rana, R.K.,
Chen, D.,
Sridharan, S.,
Denmon, S.,
Fookes, C.,
Compressive Sensing for Gait Recognition,
DICTA11(567-571).
IEEE DOI
1205
BibRef
Sivapalan, S.,
Chen, D.,
Denman, S.[Simon],
Sridharan, S.[Sridha],
Fookes, C.[Clinton],
3D ellipsoid fitting for multi-view gait recognition,
AVSBS11(355-360).
IEEE DOI
1111
BibRef
Hu, M.[Maodi],
Wang, Y.H.[Yun-Hong],
Zhang, Z.X.[Zhao-Xiang],
Zhang, D.[De],
Multi-view multi-stance gait identification,
ICIP11(541-544).
IEEE DOI
1201
BibRef
Hu, R.Z.L.[Richard Zhi-Ling],
Hartfiel, A.[Adam],
Tung, J.[James],
Fakih, A.H.[Adel H.],
Hoey, J.[Jesse],
Poupart, P.[Pascal],
3D Pose tracking of walker users' lower limb with a structured-light
camera on a moving platform,
HAU3D11(29-36).
IEEE DOI
1106
BibRef
Navarro, S.[Sergio],
López-Méndez, A.[Adolfo],
Alcoverro, M.[Marcel],
Casas, J.R.[Josep Ramon],
Multi-view Body Tracking with a Detector-Driven Hierarchical Particle
Filter,
AMDO12(82-91).
Springer DOI
1208
BibRef
Alcoverro, M.[Marcel],
Lopez-Mendez, A.[Adolfo],
Pardas, M.[Montse],
Casas, J.R.[Josep R.],
Connected operators on 3D data for human body analysis,
HAU3D11(9-14).
IEEE DOI
1106
BibRef
Canton-Ferrer, C.,
Casas, J.R.,
Pardas, M.,
Spatio-temporal alignment and hyperspherical radon transform for 3D
gait recognition in multi-view environments,
Biometrics10(116-121).
IEEE DOI
1006
See also Human motion capture using scalable body models.
BibRef
Tahmoush, D.,
Silvious, J.,
Radar micro-doppler for long range front-view gait recognition,
BTAS09(1-6).
IEEE DOI
0909
BibRef
Jensen, R.R.[Rasmus R.],
Paulsen, R.R.[Rasmus R.],
Larsen, R.[Rasmus],
Analysis of Gait Using a Treadmill and a Time-of-Flight Camera,
Dyn3D09(154-166).
Springer DOI
0909
BibRef
And:
Analyzing Gait Using a Time-of-Flight Camera,
SCIA09(21-30).
Springer DOI
0906
BibRef
Hild, M.,
Estimation of 3D motion trajectory and velocity from monocular image
sequences in the context of human gait recognition,
ICPR04(IV: 231-235).
IEEE DOI
0409
BibRef
Fuerstenberg, K.C.,
Dietmayer, K.,
Object tracking and classification for multiple active safety and
comfort applications using a multilayer laser scanner,
IVS04(802-807).
IEEE DOI
0411
Detect pedestrians by the motion.
BibRef
Rao, Q.[Qing],
Krüger, L.[Lars],
Dietmayer, K.[Klaus],
3D Shape Reconstruction in Traffic Scenarios Using Monocular Camera and
Lidar,
3DModelApp16(II: 3-18).
Springer DOI
1704
BibRef
Streller, D.,
Dietmayer, K.,
Object tracking and classification using a multiple hypothesis approach,
IVS04(808-812).
IEEE DOI
0411
BibRef
Johnson, A.Y.[Amos Y.],
Bobick, A.F.[Aaron F.],
A Multi-view Method for Gait Recognition Using Static Body Parameters,
AVBPA01(301).
Springer DOI
0310
BibRef
Earlier: A2, A1:
Gait Recognition Using Static, Activity-Specific Parameters,
CVPR01(I:423-430).
IEEE DOI
0110
BibRef
Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Gait Analysis, Diagnosis of Difference, Medical Diagnosis, Motion Capture .