17.1.3.5.8 Gait Analysis, Diagnosis of Difference, Medical Diagnosis, Motion Capture

Chapter Contents (Back)
Walking. Gait Analysis. Diagnosis. Medical Diagnosis. Motion Capture. Medical diagnosis, detection of abnormal gait.
See also Human Motion Capture, Joint Information, Special Activities.

Semwal, S.K.[Sudhanshu K.], Parker, M.J.[Michael J.],
An Animation System for Biomechanical Analysis of Leg Motion and Predicting Injuries during Cycling,
RealTimeImg(5), No. 2, April 1999, pp. 109-123. BibRef 9904

Tan, T.W.[Tee-Woon], Guan, L.[Ling], Burne, J.[John],
A Real-time Image Analysis System for Computer-Assisted Diagnosis of Neurological Disorders,
RealTimeImg(5), No. 4, August 1999, pp. 253-269. BibRef 9908

Lee, H.[Howard], Guan, L.[Ling], Lee, I.[Ivan],
Video Analysis of Human Gait and Posture to Determine Neurological Disorders,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link 0811
BibRef

Lee, H.[Howard], Guan, L.[Ling], Burne, J.,
Human Gait and Posture Analysis for Diagnosing Neurological Disorders,
ICIP00(Vol II: 435-438).
IEEE DOI 0008
BibRef

You, B.M., Siy, P., Anderst, W., Tashman, S.,
In vivo measurement of 3-D skeletal kinematics from sequences of biplane radiographs: Application to knee kinematics,
MedImg(20), No. 6, June 2001, pp. 514-525.
IEEE Top Reference. 0110
BibRef

Beynon, M.J., Jones, L., Holt, C.A.,
Classification of Osteoarthritic and Normal Knee Function Using Three-Dimensional Motion Analysis and the Dempster-Shafer Theory of Evidence,
SMC-A(36), No. 1, January 2006, pp. 173-186.
IEEE DOI 0601
BibRef

Roetenberg, D.,
Inertial and Magnetic Sensing of Human Motion,
Ph.D.Thesis, University of Twente, May 2006.
PDF File. 1109
BibRef

Luinge, H.J.,
Inertial Sensing of Human Movement,
Ph.D.Thesis, University of Twente, December 2002.
PDF File. 1109
BibRef

Pronost, N.[Nicolas], Dumont, G.[Georges],
Dynamics-based analysis and synthesis of human locomotion,
VC(23), No. 7, July 2007, pp. 513-522.
Springer DOI 0707
BibRef

Ramasso, E.[Emmanuel], Rombaut, M.[Michèle], Pellerin, D.[Denis],
State Filtering and Change Detection Using TBM Conflict Application to Human Action Recognition in Athletics Videos,
CirSysVideo(17), No. 7, July 2007, pp. 944-949.
IEEE DOI 0707
BibRef

Guironnet, M., Pellerin, D., Rombaut, M.,
A fusion architecture based on TBM for camera motion classification,
IVC(25), No. 11, 1 November 2007, pp. 1737-1747.
Elsevier DOI 0709
Camera motion classification; Transferable belief model; Motion estimation; Motion description; Video indexing BibRef

Ramasso, E.[Emmanuel], Panagiotakis, C.[Costas], Rombaut, M.[Michèle], Pellerin, D.[Denis], Tziritas, G.[Georgios],
Human Shape-Motion Analysis In Athletics Videos for Coarse To Fine Action/Activity Recognition Using Transferable Belief Model,
ELCVIA(7), No. 4, 2008, pp. xx-yy.
DOI Link 0909
BibRef
Earlier: A2, A1, A5, A3, A4:
Automatic people detection and counting for athletic videos classification,
AVSBS07(429-434).
IEEE DOI 0709
BibRef

Lakany, H.M.[Heba M.],
Extracting a diagnostic gait signature,
PR(41), No. 5, May 2008, pp. 1644-1654.
Elsevier DOI 0711
Human locomotion; Gait analysis; Feature extraction; Self-organising maps; Diagnostic signatures BibRef

Schepers, H.M.,
Ambulatory Assessment of Human Body Kinematics and Kinetics,
Ph.D.Thesis, Universiteit Twente, June 2009.
PDF File. 1109
BibRef

Klein Horstman, M.D.[Martijn D.],
The Twente Lower Extremity Model: Consistent Dynamic Simulation of the Human Locomoter Apparatus,
Ph.D.Thesis, University of Twente, December 2007.
PDF File. 1109
BibRef

Zhang, B.L.[Bai-Ling], Zhang, Y.C.[Yan-Chun], Begg, R.K.[Rezaul K.],
Gait classification in children with cerebral palsy by Bayesian approach,
PR(42), No. 4, April 2009, pp. 581-586.
Elsevier DOI 0812
Gait classification; Cerebral palsy; Bayesian approach BibRef

Gu, J.X.[Jun-Xia], Ding, X.Q.[Xiao-Qing], Wang, S.J.[Sheng-Jin], Wu, Y.S.[You-Shou],
Action and Gait Recognition From Recovered 3-D Human Joints,
SMC-B(40), No. 4, August 2010, pp. 1021-1033.
IEEE DOI 1008
BibRef

Koktas, N.S.[Nigar Sen], Yalabik, N.[Nese], Yavuzer, G.[Gunes], Duin, R.P.W.[Robert P.W.],
A multi-classifier for grading knee osteoarthritis using gait analysis,
PRL(31), No. 9, 1 July 2010, pp. 898-904.
Elsevier DOI 1004
BibRef
Earlier: A1, A2, A3, Only:
Combining Neural Networks for Gait Classification,
CIARP06(381-388).
Springer DOI 0611
Combining classifiers; Grading knee OA; Gait analysis BibRef

Charbonnier, C.[Caecilia], Assassi, L.[Lazhari], Volino, P.[Pascal], Magnenat-Thalmann, N.[Nadia],
Motion study of the hip joint in extreme postures,
VC(25), No. 9, September 2009, pp. xx-yy.
Springer DOI 0909
BibRef

Bauckhage, C.[Christian], Tsotsos, J.K.[John K.], Bunn, F.E.[Frank E.],
Automatic detection of abnormal gait,
IVC(27), No. 1-2, January 2009, pp. 108-115.
Elsevier DOI 0811
BibRef
Earlier:
Detecting Abnormal Gait,
CRV05(282-288).
IEEE DOI 0505
Gait analysis; Shape encoding; Vector space embedding; SVM classification BibRef

Karg, M., Kuhnlenz, K., Buss, M.,
Recognition of Affect Based on Gait Patterns,
SMC-B(40), No. 4, August 2010, pp. 1050-1061.
IEEE DOI 1008
BibRef

Kurihara, Y., Watanabe, K., Yoneyama, M.,
Estimation of Walking Exercise Intensity Using 3-D Acceleration Sensor,
SMC-C(42), No. 4, July 2012, pp. 495-500.
IEEE DOI 1206
BibRef

Shimura, K.[Kenichiro], Ohtsuka, K.[Kazumichi], Vizzari, G.[Giuseppe], Nishinari, K.[Katsuhiro], Bandini, S.[Stefania],
Mobility analysis of the aged pedestrians by experiment and simulation,
PRL(44), No. 1, 2014, pp. 58-63.
Elsevier DOI 1407
Aging society BibRef

Kadu, H., Kuo, C.C.J.[C.C. Jay],
Automatic Human Mocap Data Classification,
MultMed(16), No. 8, December 2014, pp. 2191-2202.
IEEE DOI 1502
image classification BibRef

Parascandolo, P.[Patrizia], Cesario, L.[Lorenzo], Vosilla, L.[Loris], Viano, G.[Gianni],
RheumaSCORE: A CAD System for Rheumatoid Arthritis Diagnosis and Follow-Up,
RHEUMA15(135-142).
Springer DOI 1511
BibRef

Hwang, K., Lin, J., Yeh, K.,
Learning to Adjust and Refine Gait Patterns for a Biped Robot,
SMCS(45), No. 12, December 2015, pp. 1481-1490.
IEEE DOI 1512
Foot BibRef

Tao, L.[Lili], Paiement, A.[Adeline], Damen, D.[Dima], Mirmehdi, M.[Majid], Hannuna, S.[Sion], Camplani, M.[Massimo], Burghardt, T.[Tilo], Craddock, I.[Ian],
A comparative study of pose representation and dynamics modelling for online motion quality assessment,
CVIU(148), No. 1, 2016, pp. 136-152.
Elsevier DOI 1606
BibRef
Earlier: A2, A1, A6, A5, A3, A4, Only:
Online quality assessment of human motion from skeleton data,
BMVC14(xx-yy).
HTML Version. 1410
Human motion quality BibRef

Yu, Z., Chen, X., Huang, Q., Zhang, W., Meng, L., Zhang, W., Gao, J.,
Gait Planning of Omnidirectional Walk on Inclined Ground for Biped Robots,
SMCS(46), No. 7, July 2016, pp. 888-897.
IEEE DOI 1606
Digital signal processing BibRef

Saputra, A.A., Botzheim, J., Sulistijono, I.A., Kubota, N.,
Biologically Inspired Control System for 3-D Locomotion of a Humanoid Biped Robot,
SMCS(46), No. 7, July 2016, pp. 898-911.
IEEE DOI 1606
Humanoid robots BibRef

Cheng, T.H., Wang, Q., Kamalapurkar, R., Dinh, H.T., Bellman, M., Dixon, W.E.,
Identification-Based Closed-Loop NMES Limb Tracking With Amplitude-Modulated Control Input,
Cyber(46), No. 7, July 2016, pp. 1679-1690.
IEEE DOI 1606
Fatigue BibRef

Parisi, F., Ferrari, G., Giuberti, M., Contin, L., Cimolin, V., Azzaro, C., Albani, G., Mauro, A.,
Inertial BSN-Based Characterization and Automatic UPDRS Evaluation of the Gait Task of Parkinsonians,
AffCom(7), No. 3, July 2016, pp. 258-271.
IEEE DOI 1609
BibRef

Zaki, M.H., Sayed, T.,
Exploring walking gait features for the automated recognition of distracted pedestrians,
IET-ITS(10), No. 2, 2016, pp. 106-113.
DOI Link 1602
gait analysis BibRef

Ameli, S.[Sina], Naghdy, F.[Fazel], Stirling, D.[David], Naghdy, G.[Golshah], Aghmesheh, M.[Morteza],
Objective clinical gait analysis using inertial sensors and six minute walking test,
PR(63), No. 1, 2017, pp. 246-257.
Elsevier DOI 1612
Physical performance status BibRef

Higashiguchi, T.[Tsuyoshi], Shimoyama, T.[Toma], Ukita, N.[Norimichi], Kanbara, M.[Masayuki], Hagita, N.[Norihiro],
Classification of Gait Anomaly due to Lesion Using Full-Body Gait Motions,
IEICE(E100-D), No. 4, April 2017, pp. 874-881.
WWW Link. 1704
BibRef
Earlier:
Lesioned-Part Identification by Classifying Entire-Body Gait Motions,
PSIVT15(136-147).
Springer DOI 1602
BibRef

Paulo, J., Peixoto, P., Nunes, U.J.,
ISR-AIWALKER: Robotic Walker for Intuitive and Safe Mobility Assistance and Gait Analysis,
HMS(47), No. 6, December 2017, pp. 1110-1122.
IEEE DOI 1712
Cameras, Gait recognition, Legged locomotion, Rehabilitation robotics, Robot sensing systems, Safety, user intention BibRef

Ansari, A.F.[Abdul Fatir], Roy, P.P.[Partha Pratim], Dogra, D.P.[Debi Prosad],
Exercise classification and event segmentation in Hammersmith Infant Neurological Examination videos,
MVA(29), No. 2, February 2018, pp. 233-245.
Springer DOI 1802
BibRef

Li, B., Zhu, C., Li, S., Zhu, T.,
Identifying Emotions from Non-Contact Gaits Information Based on Microsoft Kinects,
AffCom(9), No. 4, October 2018, pp. 585-591.
IEEE DOI 1812
Feature extraction, Legged locomotion, Emotion recognition, Time-frequency analysis, Discrete Fourier transforms, discrete fourier transform BibRef

Choi, M.G.[Myung Geol], Kwon, T.[Taesoo],
Motion rank: applying page rank to motion data search,
VC(35), No. 2, February 2019, pp. 289-300.
Springer DOI 1906
Visualize motion data. BibRef

Xu, C.[Chi], Makihara, Y.S.[Yasu-Shi], Yagi, Y.S.[Yasu-Shi], Lu, J.F.[Jian-Feng],
Gait-based age progression/regression: a baseline and performance evaluation by age group classification and cross-age gait identification,
MVA(30), No. 4, June 2019, pp. 629-644.
Springer DOI 1906
BibRef

Bargiotas, I.[Ioannis], Audiffren, J.[Julien], Vayatis, N.[Nicolas], Vidal, P.P.[Pierre-Paul], Yelnik, A.P.[Alain P.], Ricard, D.[Damien],
Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm,
IPOL(9), 2019, pp. 143-157.
DOI Link 1906
Code, Posture. postural control evaluation in elderly. BibRef

Raman, R.[Rahul], Boubchir, L.[Larbi], Sa, P.K.[Pankaj Kumar], Majhi, B.[Banshidhar], Bakshi, S.[Sambit],
Beyond estimating discrete directions of walk: a fuzzy approach,
MVA(30), No. 5, July 2019, pp. 901-917.
Springer DOI 1907
BibRef

Xu, M.L.[Ming-Liang], Zhai, Y.F.[Ya-Fang], Guo, Y.[Yibo], Lv, P.[Pei], Li, Y.[Yafei], Wang, M.[Meng], Zhou, B.[Bing],
Personalized training through Kinect-based games for physical education,
JVCIR(62), 2019, pp. 394-401.
Elsevier DOI 1908
Kinect, Educational games BibRef

Li, S., Liu, W., Ma, H.,
Attentive Spatial-Temporal Summary Networks for Feature Learning in Irregular Gait Recognition,
MultMed(21), No. 9, September 2019, pp. 2361-2375.
IEEE DOI 1909
Gait recognition, Feature extraction, Surveillance, Semantics, Biological system modeling, irregular gait sequence BibRef

Yamakawa, K., Okamoto, S., Kubo, R., Yamada, N., Akiyama, Y., Yamada, Y.,
Knee Pain Patient Simulation for Recommendation of Sit-to-Stand Handrail Positions,
HMS(49), No. 5, October 2019, pp. 461-467.
IEEE DOI 1909
Knee, Pain, Modeling, Senior citizens, Muscles, Electrical stimulation, Skin, Knee osteoarthritis (OA), knee moment, motion simulation BibRef

Ma, Y., Lee, E.W., Hu, Z., Shi, M., Yuen, R.K.,
An Intelligence-Based Approach for Prediction of Microscopic Pedestrian Walking Behavior,
ITS(20), No. 10, October 2019, pp. 3964-3980.
IEEE DOI 1910
Legged locomotion, Microscopy, Predictive models, Neural networks, Decision making, Mathematical model, Numerical models, prediction BibRef

Prabhu, P.[Pooja], Karunakar, A.K., Anitha, H., Pradhan, N.,
Classification of gait signals into different neurodegenerative diseases using statistical analysis and recurrence quantification analysis,
PRL(139), 2020, pp. 10-16.
Elsevier DOI 2011
Gait, Neurological disorder, Probabilistic neural networks, Recurrence quantification analysis, Sports medicine, Support vector machine BibRef

Bhattacharya, U.[Uttaran], Roncal, C.[Christian], Mittal, T.[Trisha], Chandra, R.[Rohan], Kapsaskis, K.[Kyra], Gray, K.[Kurt], Bera, A.[Aniket], Manocha, D.[Dinesh],
Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping,
ECCV20(X:145-163).
Springer DOI 2011
BibRef

Koop, M.M., Rosenfeldt, A.B., Johnston, J.D., Streicher, M.C., Qu, J., Alberts, J.L.,
The HoloLens Augmented Reality System Provides Valid Measures of Gait Performance in Healthy Adults,
HMS(50), No. 6, December 2020, pp. 584-592.
IEEE DOI 2011
Legged locomotion, Biomechanics, Wearable computers, Data collection, Augmented reality, Augmented reality (AR), gait, wearable computers BibRef

Ongun, M.F.[Mehmet Faruk], Güdükbay, U.[Ugur], Aksoy, S.[Selim],
Recognition of occupational therapy exercises and detection of compensation mistakes for Cerebral Palsy,
JVCIR(73), 2020, pp. 102970.
Elsevier DOI 2012
Gesture recognition, Cerebral palsy, Occupational therapy, Compensation mistake, Hidden Markov model, Virtual rehabilitation BibRef

Webering, F.[Fritz], Blume, H.[Holger], Allaham, I.[Issam],
Markerless camera-based vertical jump height measurement using OpenPose,
CVPM21(3863-3869)
IEEE DOI 2109
Power measurement, Tracking, Pose estimation, Neural networks, Tools, vertical jump height, parabola BibRef

Sanz-Pena, I.[Inigo], Blanco, J.[Julio], Kim, J.H.[Joo H.],
Computer Interface for Real-Time Gait Biofeedback Using a Wearable Integrated Sensor System for Data Acquisition,
HMS(51), No. 5, October 2021, pp. 484-493.
IEEE DOI 2109
Exoskeletons, Robots, Training, Knee, Kinematics, Computer interfaces, Real-time systems, Biofeedback (BF) computer interface, wearable sensors BibRef

Liao, R.C.[Ruo-Chen], Moriwaki, K.[Kousuke], Makihara, Y.S.[Yasu-Shi], Muramatsu, D.[Daigo], Takemura, N.[Noriko], Yagi, Y.S.[Yasu-Shi],
Health Indicator Estimation by Video-Based Gait Analysis,
IEICE(E104-D), No. 10, October 2021, pp. 1678-1690.
WWW Link. 2110
BibRef

Li, J.W.[Jian-Wei], Hu, Q.R.[Qing-Rui], Guo, T.X.[Tian-Xiao], Wang, S.Q.[Si-Qi], Shen, Y.F.[Yan-Fei],
What and how well you exercised? An efficient analysis framework for fitness actions,
JVCIR(80), 2021, pp. 103304.
Elsevier DOI 2110
Action assessment, Image processing, Action recognition, Intelligent sports, Performance analysis BibRef

Ribet, S.[Sarah], Wannous, H.[Hazem], Vandeborre, J.P.[Jean-Philippe],
Survey on Style in 3D Human Body Motion: Taxonomy, Data, Recognition and Its Applications,
AffCom(12), No. 4, October 2021, pp. 928-948.
IEEE DOI 2112
Market research, Taxonomy, Animation, Legged locomotion, Motion analysis, Machine learning, motion style generation BibRef

Wang, Y.H.[Yan-Hong], Zou, Q.S.[Qiao-Sha], Tang, Y.M.[Yan-Min], Wang, Q.[Qing], Ding, J.[Jing], Wang, X.[Xin], Shi, C.J.R.[C.J. Richard],
SAIL: A Deep-Learning-Based System for Automatic Gait Assessment From TUG Videos,
HMS(52), No. 1, February 2022, pp. 110-122.
IEEE DOI 2201
Videos, Skeleton, Legged locomotion, Pose estimation, Detectors, Feature extraction, Support vector machines, timed "up & go" (TUG) BibRef

Zhou, G.Y.[Guo-Yang], Aggarwal, V.[Vaneet], Yin, M.[Ming], Yu, D.[Denny],
A Computer Vision Approach for Estimating Lifting Load Contributors to Injury Risk,
HMS(52), No. 2, April 2022, pp. 207-219.
IEEE DOI 2203
Task analysis, Feature extraction, Injuries, Videos, Predictive models, Cameras, facial expression, lifting risk assessment BibRef

Du, C.[Chen], Graham, S.[Sarah], Depp, C.[Colin], Nguyen, T.[Truong],
Multi-Task Center-of-Pressure Metrics Estimation With Graph Convolutional Network,
MultMed(24), No. 2022, pp. 2018-2033.
IEEE DOI 2204
Understanding, diagnosis, human body movement. Measurement, Estimation, Task analysis, Adaptation models, Computational modeling, Predictive models, Multi-task learning, balance control BibRef

Zhang, Y.[Yu], Xiong, W.[Wei], Mi, S.[Siya],
Learning time-aware features for action quality assessment,
PRL(158), 2022, pp. 104-110.
Elsevier DOI 2205
Action quality assessment, Time-aware attention, Video clips, Time-aware (TA), Adversarial BibRef

Abbas, M.[Manuel], Jeannès, R.L.B.[Régine Le Bouquin],
Acceleration-based gait analysis for frailty assessment in older adults,
PRL(161), 2022, pp. 45-51.
Elsevier DOI 2209
Gait quality, Acceleration signals, Frailty, Elderly, Free-living conditions BibRef

Zhou, J.J.[Jun-Jie], Zhong, S.[Shanlin], Wu, W.[Wei],
Hierarchical Motion Learning for Goal-Oriented Movements With Speed-Accuracy Tradeoff of a Musculoskeletal System,
Cyber(52), No. 11, November 2022, pp. 11453-11466.
IEEE DOI 2211
Muscles, Adaptation models, Task analysis, Arms, Mathematical model, Integrated circuit modeling, Basal ganglia, speed-accuracy tradeoff (SAT) BibRef

Pan, J.H.[Jia-Hui], Gao, J.[Jibin], Zheng, W.S.[Wei-Shi],
Adaptive Action Assessment,
PAMI(44), No. 12, December 2022, pp. 8779-8795.
IEEE DOI 2212
Adaptation models, Computer architecture, Task analysis, Visualization, Training, Videos, Image quality, Action assessment, action modelling BibRef

Yang, H.[Hu], Li, M.L.[Ming-Lun], Guo, B.[Bao], Zhang, F.[Fan], Wang, P.[Pu],
A vector field approach for identifying anomalous human mobility,
IET-ITS(17), No. 4, 2023, pp. 649-666.
DOI Link 2304
BibRef

Gedamu, K.[Kumie], Ji, Y.L.[Yan-Li], Yang, Y.[Yang], Shao, J.[Jie], Shen, H.T.[Heng Tao],
Fine-Grained Spatio-Temporal Parsing Network for Action Quality Assessment,
IP(32), 2023, pp. 6386-6400.
IEEE DOI 2311
BibRef

Voisard, C.[Cyril], de l'Escalopier, N.[Nicolas], Moreau, A.[Albane], Vienne-Jumeau, A.[Alienor], Ricard, D.[Damien], Oudre, L.[Laurent],
A Reference Data Set for the Study of Healthy Subject Gait with Inertial Measurements Units,
IPOL(13), 2023, pp. 314-320.
DOI Link 2312
Dataset, Gait. BibRef

Zhou, K.L.[Kang-Lei], Ma, Y.[Yue], Shum, H.P.H.[Hubert P. H.], Liang, X.H.[Xiao-Hui],
Hierarchical Graph Convolutional Networks for Action Quality Assessment,
CirSysVideo(33), No. 12, December 2023, pp. 7749-7763.
IEEE DOI 2312
BibRef

Hwang, Y.T.[Yi-Ting], Hsu, Y.R.[Ya-Ru], Lin, B.S.[Bor-Shing],
Using B-Spline Model on Depth Camera Data to Predict Physical Activity Energy Expenditure of Different Levels of Human Exercise,
HMS(54), No. 1, February 2024, pp. 79-88.
IEEE DOI 2402
Task analysis, Cameras, Splines (mathematics), Predictive models, Hip, Elbow, Calorimetry, B-spline regression, depth camera, physical activity (PA) BibRef

Zeng, L.A.[Ling-An], Zheng, W.S.[Wei-Shi],
Multimodal Action Quality Assessment,
IP(33), 2024, pp. 1600-1613.
IEEE DOI Code:
WWW Link. 2403
Decoding, Adaptation models, Feature extraction, Task analysis, Quality assessment, Visualization, Rhythm, video understanding BibRef


Chiquier, M.[Mia], Vondrick, C.[Carl],
Muscles in Action,
ICCV23(22034-22044)
IEEE DOI 2401
Dataset, motion, with surface electromyography data. BibRef

Araújo, J.P.[João Pedro], Li, J.[Jiaman], Vetrivel, K.[Karthik], Agarwal, R.[Rishi], Wu, J.J.[Jia-Jun], Gopinath, D.[Deepak], Clegg, A.[Alexander], Liu, C.K.[C. Karen],
CIRCLE: Capture In Rich Contextual Environments,
CVPR23(21211-21221)
IEEE DOI 2309
BibRef

Dunnhofer, M.[Matteo], Sordi, L.[Luca], Micheloni, C.[Christian],
Visualizing Skiers' Trajectories in Monocular Videos,
CVSports23(5188-5198)
IEEE DOI 2309
BibRef

Suman, H.K.[Himanshu Kumar], Verlekar, T.T.[Tanmay Tulsidas],
Video-based Gait Analysis for Spinal Deformity,
PeopleAn22(278-288).
Springer DOI 2304
BibRef

Huang, Z.[Zhuo], Liu, C.[Changhui], Zhu, R.[Rui], Zhao, T.Z.[Tong-Zhou],
An AHP-based Physical Fitness Assessment Model for College Students,
ICRVC22(277-280)
IEEE DOI 2301
Training, Computational modeling, Market research, Data models, Health and safety, Physical fitness assessment model, AHP, Multidimensional assessment BibRef

Bai, Y.[Yang], Zhou, D.[Desen], Zhang, S.Y.[Song-Yang], Wang, J.[Jian], Ding, E.[Errui], Guan, Y.[Yu], Long, Y.[Yang], Wang, J.D.[Jing-Dong],
Action Quality Assessment with Temporal Parsing Transformer,
ECCV22(IV:422-438).
Springer DOI 2211
BibRef

Xu, A.C.[Ang-Chi], Zeng, L.A.[Ling-An], Zheng, W.S.[Wei-Shi],
Likert Scoring with Grade Decoupling for Long-term Action Assessment,
CVPR22(3222-3231)
IEEE DOI 2210
Computational modeling, Estimation, Transformers, Feature extraction, Decoding, Video analysis and understanding BibRef

Peng, K.Y.[Kun-Yu], Roitberg, A.[Alina], Yang, K.L.[Kai-Lun], Zhang, J.M.[Jia-Ming], Stiefelhagen, R.[Rainer],
Should I take a walk? Estimating Energy Expenditure from Video Data,
CVPM22(2074-2084)
IEEE DOI 2210
Training, Weight measurement, Target tracking, Annotations, Estimation, Benchmark testing, Muscles BibRef

Xu, J.L.[Jing-Lin], Rao, Y.M.[Yong-Ming], Yu, X.[Xumin], Chen, G.Y.[Guang-Yi], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment,
CVPR22(2939-2948)
IEEE DOI 2210
Codes, Annotations, Semantics, Quality assessment, Pattern recognition, Reliability, Action and event recognition BibRef

Lannan, N.[Nate], Zhou, L.[Le], Fan, G.L.[Guo-Liang],
A Multiview Depth-based Motion Capture Benchmark Dataset for Human Motion Denoising and Enhancement Research,
PBVS22(426-435)
IEEE DOI 2210
Conferences, Software algorithms, Noise reduction, Benchmark testing, Cameras, Motion capture, Adaptive optics BibRef

Chatzitofis, A.[Anargyros], Albanis, G.[Georgios], Zioulis, N.[Nikolaos], Thermos, S.[Spyridon],
A Low-cost & Realtime Motion Capture System,
CVPR22(21421-21426)
IEEE DOI 2210
Costs, Noise reduction, Virtual reality, Motion capture, Sensor systems, Real-time systems BibRef

Farabi, S.[Shafkat], Himel, H.[Hasibul], Gazzali, F.[Fakhruddin], Hasan, M.B.[Md. Bakhtiar], Kabir, M.H.[Md. Hasanul], Farazi, M.[Moshiur],
Improving Action Quality Assessment Using Weighted Aggregation,
IbPRIA22(576-587).
Springer DOI 2205
BibRef

Parmar, P.[Paritosh], Morris, B.[Brendan],
Win-Fail Action Recognition,
Activity22(161-171)
IEEE DOI 2202
Code, Action Recognition.
WWW Link. Did the attempt fail or succeed. Analytical models, Pediatrics, Limiting, Benchmark testing, Spatial databases, Spatiotemporal phenomena, Pattern recognition BibRef

Li, Y.[Yue], Habermann, M.[Marc], Thomaszewski, B.[Bernhard], Coros, S.[Stelian], Beeler, T.[Thabo], Theobalt, C.[Christian],
Deep Physics-aware Inference of Cloth Deformation for Monocular Human Performance Capture,
3DV21(373-384)
IEEE DOI 2201
Training, Learning systems, Deformable models, Tracking, Dynamics, Clothing BibRef

Nagai, T.[Takasuke], Takeda, S.[Shoichiro], Matsumura, M.[Masaaki], Shimizu, S.[Shinya], Yamamoto, S.[Susumu],
Action Quality Assessment with Ignoring Scene Context,
ICIP21(1189-1193)
IEEE DOI 2201
Training, Correlation, Shape, Convolution, Predictive models, Feature extraction, Action quality assessment, Scene context, Regression problem BibRef

Fieraru, M.[Mihai], Zanfir, M.[Mihai], Pirlea, S.C.[Silviu Cristian], Olaru, V.[Vlad], Sminchisescu, C.[Cristian],
AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training,
CVPR21(9914-9923)
IEEE DOI 2111
Training, Visualization, Solid modeling, Shape, Real-time systems, Sensors BibRef

Nonaka, N.[Naoki], Fujihira, R.[Ryo], Nishio, M.[Monami], Murakami, H.[Hidetaka], Tajima, T.[Takuya], Yamada, M.[Mutsuo], Maeda, A.[Akira], Seita, J.[Jun],
End-to-End High-Risk Tackle Detection System for Rugby,
CVSports22(3549-3558)
IEEE DOI 2210
Deep learning, Protocols, Head, Pose estimation, Pattern recognition BibRef

Martin, Z.[Zubair], Hendricks, S.[Sharief], Patel, A.[Amir],
Automated Tackle Injury Risk Assessment in Contact-Based Sports: A Rugby Union Example,
CVSports21(4589-4598)
IEEE DOI 2109
Protocols, Tracking, System dynamics, Stability analysis, Time factors, Risk management BibRef

Zhou, Q.X.[Qian-Xiang], Jin, Y.[Yu], Liu, Z.Q.[Zhong-Qi],
The Measurement and Analysis of Chinese Adults' Range of Motion Joint,
DHM21(I:163-177).
Springer DOI 2108
BibRef

Seo, C.J.[Chan-Jin], Sabanai, M.[Masato], Goto, Y.[Yuta], Tagami, K.[Koji], Ogata, H.[Hiroyuki], Kanosue, K.[Kazuyuki], Ohya, J.[Jun],
Extracting and Interpreting Unknown Factors with Classifier for Foot Strike Types in Running,
ICPR21(3217-3224)
IEEE DOI 2105
Accelerometers, Deep learning, Radio frequency, Video sequences, raining data, Cameras, Data models, foot strike types, running BibRef

Fu, B.Y.[Bi-Ying], Damer, N.[Naser], Kirchbuchner, F.[Florian], Kuijper, A.[Arjan],
Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-adaption and Few-shot Learning,
HCAU20(203-218).
Springer DOI 2103
BibRef

Masuda, M.[Mana], Hachiuma, R.[Ryo], Fujii, R.[Ryo], Saito, H.[Hideo],
Unsupervised Anomaly Detection of the First Person in Gait from an Egocentric Camera,
ISVC20(II:604-617).
Springer DOI 2103
BibRef

Zhuang, Y.[Yuan], Lin, L.F.[Lan-Fen], Tong, R.F.[Ruo-Feng], Liu, J.Q.[Jia-Qing], Iwamoto, Y.[Yutaro], Chen, Y.W.[Yen-Wei],
G-GCSN: Global Graph Convolution Shrinkage Network for Emotion Perception from Gait,
MLCSA20(46-57).
Springer DOI 2103
BibRef

Haider, F., Albert, P., Luz, S.,
Automatic Recognition of Low-Back Chronic Pain Level and Protective Movement Behaviour using Physical and Muscle Activity Information,
FG20(834-838)
IEEE DOI 2102
Pain, Task analysis, Radio frequency, Feature extraction, Muscles, Neurons, Support vector machines, Social Signal Processing, Pain Recognition BibRef

Loureiro, J., Correia, P.L.,
Using a Skeleton Gait Energy Image for Pathological Gait Classification,
FG20(503-507)
IEEE DOI 2102
Pathology, Feature extraction, Skeleton, Legged locomotion, Support vector machines, Training, Computational modeling, Gait, Skeleton BibRef

Shao, D., Zhao, Y., Dai, B., Lin, D.,
FineGym: A Hierarchical Video Dataset for Fine-Grained Action Understanding,
CVPR20(2613-2622)
IEEE DOI 2008
Semantics, Benchmark testing, Quality control, Pipelines, Bars, Space exploration BibRef

Gao, J.B.[Ji-Bin], Zheng, W.S.[Wei-Shi], Pan, J.H.[Jia-Hui], Gao, C.Y.[Cheng-Ying], Wang, Y.W.[Yao-Wei], Zeng, W.[Wei], Lai, J.H.[Jian-Huang],
An Asymmetric Modeling for Action Assessment,
ECCV20(XXX: 222-238).
Springer DOI 2010
BibRef

Wu, E., Nozawa, T., Perteneder, F., Koike, H.,
VR Alpine Ski Training Augmentation using Visual Cues of Leading Skier,
CVSports20(3836-3845)
IEEE DOI 2008
Training, Visualization, Tracking, Resists, Eye protection, Sensors BibRef

Pan, J.H.[Jia-Hui], Gao, J.[Jibin], Zheng, W.S.[Wei-Shi],
Action Assessment by Joint Relation Graphs,
ICCV19(6330-6339)
IEEE DOI 2004
graph theory, image motion analysis, learning (artificial intelligence), video signal processing, Kinetic theory BibRef

Parmar, P.[Paritosh], Morris, B.T.[Brendan Tran],
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment,
CVPR19(304-313).
IEEE DOI 2002
BibRef

Saponaro, P., Wei, H., Dominick, G., Kambhamettu, C.,
Estimating Physical Activity Intensity And Energy Expenditure Using Computer Vision On Videos,
ICIP19(3631-3635)
IEEE DOI 1910
Convolutional neural networks, energy expenditure, physical activity intensity, action recognition BibRef

Blanchard, N., Skinner, K., Kemp, A., Scheirer, W., Flynn, P.J.[Patrick J.],
'Keep Me In, Coach!': A Computer Vision Perspective on Assessing ACL Injury Risk in Female Athletes,
WACV19(1366-1374)
IEEE DOI 1904
biomechanics, bone, injuries, medical image processing, sport, video signal processing, Cameras BibRef

Fani, H., Mirlohi, A., Hosseini, H., Herperst, R.,
Swim Stroke Analytic: Front Crawl Pulling Pose Classification,
ICIP18(4068-4072)
IEEE DOI 1809
Elbow, Videos, Cameras, Feature extraction, Forestry, Task analysis, Swim Stroke Analysis, Pose Estimation BibRef

Zhao, C.J.[Cai-Jun], Li, K.W.[Kai-Way],
Perception of Floor Slipperiness Before and After a Walk,
DHM18(242-252).
Springer DOI 1807
BibRef

Wang, B., Tao, L., Burghardt, T., Mirmehdi, M.,
Calorific Expenditure Estimation Using Deep Convolutional Network Features,
Assist18(69-76)
IEEE DOI 1806
biomedical measurement, convolution, feedforward neural nets, health care, mean square error methods, activity recognition, Visualization BibRef

Saadat, S., Pickering, M.R., Perriman, D., Scarvell, J.M., Smith, P.N.,
Fast and Robust Multi-Modal Image Registration for 3D Knee Kinematics,
DICTA17(1-5)
IEEE DOI 1804
edge detection, image matching, image registration, medical image processing, stereo image processing, BibRef

Zell, P., Rosenhahn, B.,
Learning-Based Inverse Dynamics of Human Motion,
CMBFH17(842-850)
IEEE DOI 1802
Computational modeling, Dynamics, Force, Force measurement, Mathematical model, Optimization BibRef

Brattoli, B.[Biagio], Büchler, U.[Uta], Wahl, A.S.[Anna-Sophia], Schwab, M.E.[Martin E.], Ommer, B.[Björn],
LSTM Self-Supervision for Detailed Behavior Analysis,
CVPR17(3747-3756)
IEEE DOI 1711
Grasping, Manuals, Tracking, Training, Trajectory, Videos BibRef

Palma, C.[Carlos], Salazar, A.[Augusto], Vargas, F.[Francisco],
Automatic Detection of Deviations in Human Movements Using HMM: Discrete vs Continuous,
ISVC16(II: 534-543).
Springer DOI 1701
BibRef

Gianaria, E., Grangetto, M., Roppolo, M., Mulasso, A., Rabaglietti, E.,
Kinect-based gait analysis for automatic frailty syndrome assessment,
ICIP16(1314-1318)
IEEE DOI 1610
Aging BibRef

Dyshel, M., Arkadir, D., Bergman, H., Weinshall, D.,
Quantifying Levodopa-Induced Dyskinesia Using Depth Camera,
ACVR15(511-518)
IEEE DOI 1602
Biomedical monitoring BibRef

Pradhan, N.[Neera], Benavides, A.[Angela], Zhu, Q.[Qin], Banic, A.U.[Amy Ulinski],
Evaluation of Fatigue Measurement Using Human Motor Coordination for Gesture-Based Interaction in 3D Environments,
ISVC15(II: 443-452).
Springer DOI 1601
BibRef

Nabiyouni, M., Saktheeswaran, A., Bowman, D.A., Karanth, A.,
Comparing the performance of natural, semi-natural, and non-natural locomotion techniques in virtual reality,
3DUI15(3-10)
IEEE DOI 1511
gait analysis BibRef

Boutaayamou, M.[Mohamed], Schwartz, C.[Cedric], Denoel, V.[Vincent], Forthomme, B.[Benedicte], Croisier, J.L.[Jean-Louis], Garraux, G.[Gaetan], Verly, J.G.[Jacques G.], Bruls, O.[Olivier],
Development and validation of a 3D kinematic-based method for determining gait events during overground walking,
IC3D14(1-6)
IEEE DOI 1503
Accuracy BibRef

Boutaayamou, M., Schwartz, C., Stamatakis, J., Denoel, V., Maquet, D., Forthomme, B., Croisier, J.L., Macq, B., Verly, J.G., Garraux, G., Bruls, O.,
Validated extraction of gait events from 3D accelerometer recordings,
IC3D12(1-4)
IEEE DOI 1503
accelerometers BibRef

Samaraweera, G., Guo, R.[Rongkai], Quarles, J.,
Latency and avatars in Virtual Environments and the effects on gait for persons with mobility impairments,
3DUI13(23-30)
IEEE DOI 1406
avatars BibRef

Nakamura, T., Nishimura, N., Asahi, T., Oyama, G., Sato, M., Kajimoto, H.,
Kinect-based automatic scoring system for spasmodic torticollis,
3DUI14(155-156)
IEEE DOI 1406
diseases BibRef

Baumgartner, T.[Tobias], Mitzel, D.[Dennis], Leibe, B.[Bastian],
Tracking People and Their Objects,
CVPR13(3658-3665)
IEEE DOI 1309
BibRef

Manjanna, S.[Sandeep], Dudek, G.[Gregory], Giguere, P.[Philippe],
Using Gait Change for Terrain Sensing by Robots,
CRV13(16-22)
IEEE DOI 1308
Acceleration BibRef

Vieira, A.W.[Antonio W.], Lewiner, T.[Thomas], Schwartz, W.R.[William Robson], Campos, M.[Mario],
Distance matrices as invariant features for classifying MoCap data,
ICPR12(2934-2937).
WWW Link. 1302
BibRef

Zong, C.[Cong], Chetouani, M., Tapus, A.,
Automatic gait characterization for a mobility assistance system,
ICARCV10(473-478).
IEEE DOI 1109
BibRef

Svendsen, J.[Jeremy], Albu, A.B.[Alexandra Branzan], Virji-Babul, N.[Naznin],
Analysis of patterns of motor behavior in gamers with down syndrome,
CVCG11(1-6).
IEEE DOI 1106
BibRef

Spurlock, S.[Scott], Chang, R.[Remco], Wang, X.Y.[Xiao-Yu], Arceneaux, G.[George], Keefe, D.F.[Daniel F.], Souvenir, R.[Richard],
Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data,
ISVC10(II: 564-573).
Springer DOI 1011
BibRef

Choi, W.[Woong], Mukaida, S.[Sho], Sekiguchi, H.[Hiroyuki], Hachimura, K.[Kozaburo],
Quantitative analysis of Iaido proficiency by using motion data,
ICPR08(1-4).
IEEE DOI 0812
Iaido: Japanese sword technique BibRef

Fothergill, S.[Simon], Harle, R.[Robert], Holden, S.[Sean],
Modeling the Model Athlete: Automatic Coaching of Rowing Technique,
SSPR08(372-381).
Springer DOI 0812
BibRef

Wang, Y.[Ying], Huang, K.Q.[Kai-Qi], Tan, T.N.[Tie-Niu],
Multi-view Gymnastic Activity Recognition with Fused HMM,
ACCV07(I: 667-677).
Springer DOI 0711
BibRef

Kobashi, S.[Syoji], Shibanuma, N.[Nao], Kondo, K.[Katsuya], Kurosaka, M.[Masahiro], Hata, Y.[Yutaka],
Robust Estimation of Knee Kinematics After Total Knee Arthroplasty with Evolutional Computing Approach,
ICIP07(VI: 9-12).
IEEE DOI 0709
BibRef

Li, H.J.[Hao-Jie], Lin, S.X.[Shou-Xun], Zhang, Y.D.[Yong-Dong],
Combining Template Matching and Model Fitting for Human Body Segmentation and Tracking with Applications to Sports Training,
ICIAR06(II: 823-831).
Springer DOI 0610
BibRef

Tong, X.F.[Xiao-Feng], Duan, L.Y.[Ling-Yu], Xu, C.S.[Chang-Sheng], Tian, Q.[Qi], Lu, H.Q.[Han-Qing],
Local Motion Analysis and Its Application in Video based Swimming Style Recognition,
ICPR06(II: 1258-1261).
IEEE DOI 0609
BibRef

Lakany, H.M., Birbilis, A., and Hayes, G.M.,
Recognising Walkers Using Moving Light Displays,
DAINo. 811, June 1996. Neural network classifier applied to 2-D FFT features. BibRef 9606

Lakany, H.M., and Hayes, G.M.,
An Algorithm for Recognising Walkers,
DAINo. 848, March 1997. Spatio temporal analysis of joint features, uses moving light display. BibRef 9703

Lakany, H.M., and Hayes, G.M.,
A Neural Network for Moving Light Display Trajectory Prediction,
DAINo. 847, March 1997. Radial Basis Function Neural Network to predict location of lights on joints of walking person. BibRef 9703

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Rehabilitation Systems, Rehabilitation Techniques .


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