17.1.3.5.7 Gait Analysis, Depth, 3-D Data, LiDAR, Radar, 3-D from Gait

Chapter Contents (Back)
Walking. Gait Analysis. Depth. Radar.

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, 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


Shen, C.F.[Chuan-Fu], Chao, F.[Fan], Wu, W.[Wei], Wang, R.[Rui], Huang, G.Q.[George Q.], Yu, S.Q.[Shi-Qi],
LidarGait: Benchmarking 3D Gait Recognition with Point Clouds,
CVPR23(1054-1063)
IEEE DOI 2309
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 .


Last update:Mar 16, 2024 at 20:36:19