Human motion tracking for rehabilitation - A survey

Abstract Human motion tracking for rehabilitation has been an active research topic since the 1980s. It has been motivated by the increased number of patients who have suffered a stroke, or some other motor function disability. Rehabilitation is a dynamic process which allows patients to restore their functional capability to normal. To reach this target, a patients’ activities need to be continuously monitored, and subsequently corrected. This paper reviews recent progress in human movement detection/tracking systems in general, and existing or potential application for stroke rehabilitation in particular. Major achievements in these systems are summarised, and their merits and limitations individually presented. In addition, bottleneck problems in these tracking systems that remain open are highlighted, along with possible solutions.

[1]  J. Rosen,et al.  Medical Robotics , 2004 .

[2]  Rashid Ansari,et al.  Cyclic articulated human motion tracking by sequential ancestral simulation , 2004, CVPR 2004.

[3]  M. J. Caruso,et al.  Applications of magnetic sensors for low cost compass systems , 2000, IEEE 2000. Position Location and Navigation Symposium (Cat. No.00CH37062).

[4]  J. Cauraugh,et al.  Two Coupled Motor Recovery Protocols Are Better Than One: Electromyogram-Triggered Neuromuscular Stimulation and Bilateral Movements , 2002, Stroke.

[5]  I. Kakadiaris,et al.  A convex penalty method for optical human motion tracking , 2003, IWVS '03.

[6]  Gary K. Fedder,et al.  A CMOS z-axis capacitive accelerometer with comb-finger sensing , 2000, Proceedings IEEE Thirteenth Annual International Conference on Micro Electro Mechanical Systems (Cat. No.00CH36308).

[7]  宇野 洋二,et al.  Formation and control of optimal trajectory in human multijoint arm movement : minimum torque-change model , 1988 .

[8]  Pietro Perona,et al.  Monocular tracking of the human arm in 3D , 1995, Proceedings of IEEE International Conference on Computer Vision.

[9]  I. Charlton,et al.  Repeatability of an optimised lower body model. , 2004, Gait & posture.

[10]  Emil M. Petriu,et al.  Real-time 2(1/2)-D head pose recovery for model-based video-coding , 2001, IEEE Trans. Instrum. Meas..

[11]  David C. Hogg,et al.  An efficient method for contour tracking using active shape models , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.

[12]  Nicholas Ayache,et al.  Tracking brain deformations in time sequences of 3D US images , 2003, Pattern Recognit. Lett..

[13]  B. Steele,et al.  Bodies in motion: monitoring daily activity and exercise with motion sensors in people with chronic pulmonary disease. , 2003, Journal of rehabilitation research and development.

[14]  A. David Marshall,et al.  A Hierarchical Model of Dynamics for Tracking People with a Single Video Camera , 2000, BMVC.

[15]  Hendrik Johannes Luinge,et al.  Inertial sensing of human movement , 2002 .

[16]  K. Cleary,et al.  Navigation with electromagnetic tracking for interventional radiology procedures: a feasibility study. , 2005, Journal of vascular and interventional radiology : JVIR.

[17]  Nicholas Ayache,et al.  Rigid registration of 3-D ultrasound with MR images: a new approach combining intensity and gradient information , 2001, IEEE Transactions on Medical Imaging.

[18]  R. B. Davis,et al.  A gait analysis data collection and reduction technique , 1991 .

[19]  Kerstin Dautenhahn,et al.  Issues of Robot-Human Interaction Dynamics in the Rehabilitation of Children with Autism , 2000 .

[20]  Stefan Carlsson,et al.  Recognizing and Tracking Human Action , 2002, ECCV.

[21]  H. F. Machiel van der Loos,et al.  Development of robots for rehabilitation therapy: the Palo Alto VA/Stanford experience. , 2000, Journal of rehabilitation research and development.

[22]  D. Hartfiel,et al.  Understanding , 2003 .

[23]  Hugh F. Durrant-Whyte,et al.  Initial calibration and alignment of low-cost inertial navigation units for land vehicle applications , 1999, J. Field Robotics.

[24]  William T. Freeman,et al.  Bayesian Reconstruction of 3D Human Motion from Single-Camera Video , 1999, NIPS.

[25]  Michael J. Black,et al.  Implicit Probabilistic Models of Human Motion for Synthesis and Tracking , 2002, ECCV.

[26]  Jorge Dias,et al.  Vision and Inertial Sensor Cooperation Using Gravity as a Vertical Reference , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  V. Dietz,et al.  Treadmill training of paraplegic patients using a robotic orthosis. , 2000, Journal of rehabilitation research and development.

[28]  Huosheng Hu,et al.  Upper limb motion estimation from inertial measurements , 2007 .

[29]  J. Aggarwal,et al.  Lower limb kinematics of human walking with the medial axis transformation , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.

[30]  Mubarak Shah,et al.  Camera handoff: tracking in multiple uncalibrated stationary cameras , 2000, Proceedings Workshop on Human Motion.

[31]  Ramakant Nevatia,et al.  Recognizing 3-D Objects Using Surface Descriptions , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Lucia Ballerini,et al.  Time-Varying Image Processing and Moving Object Recognition , 1997 .

[33]  T Tamata,et al.  HOME or hospital? , 1979, Lancet.

[34]  Thomas S. Huang,et al.  Estimating Articulated Motion by Decomposition , 1994 .

[35]  Mansoor Sarhadi,et al.  Reconstructing 3D Pose and Motion from a Single Camera View , 1998, BMVC.

[36]  David Beymer,et al.  A real-time computer vision system for vehicle tracking and traffic surveillance , 1998 .

[37]  Huosheng Hu,et al.  Kinematic model aided inertial motion tracking of human upper limb , 2005, 2005 IEEE International Conference on Information Acquisition.

[38]  R. D. Jackson,et al.  Rehabilitation robotics in Europe , 1995 .

[39]  Noboru Ohnishi,et al.  Cue circles: image feature for measuring 3-D motion of articulated objects using sequential image pair , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[40]  Jurgen Broeren,et al.  A kinematic analysis of a haptic handheld stylus in a virtual environment: a study in healthy subjects , 2006, Journal of NeuroEngineering and Rehabilitation.

[41]  Devesh K Bhatnagar.  Position trackers for Head Mounted Display systems: A survey , 1993 .

[42]  Stephen J. McKenna,et al.  Adaptive Learning of Statistical Appearance Models for 3D Human Tracking , 2002, BMVC.

[43]  H. Vanharanta,et al.  The relationship between anthropometric factors and body-balancing movements in postural balance. , 2003, Archives of physical medicine and rehabilitation.

[44]  Huosheng Hu,et al.  Wearable inertial sensors for arm motion tracking in home-based rehabilitation , 2006, IAS.

[45]  Andrew Blake,et al.  A framework for spatiotemporal control in the tracking of visual contours , 1993, International Journal of Computer Vision.

[46]  Olivier D. Faugeras,et al.  3D articulated models and multi-view tracking with silhouettes , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[47]  Michael Hillman,et al.  Rehabilitation robotics from past to present - a historical perspective , 2003 .

[48]  M J Caruso,et al.  VEHICLE DETECTION AND COMPASS APPLICATIONS USING AMR MAGNETIC SENSORS , 1999 .

[49]  Zhengrong Yao,et al.  Is A Magnetic Sensor Capable of Evaluating A Vision-Based Face Tracking System? , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.

[50]  W. Rymer,et al.  Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide. , 2014, Journal of rehabilitation research and development.

[51]  Tariq Rahman,et al.  Analysis of force-reflecting telerobotic systems for rehabilitation applications , 1996 .

[52]  N. Hogan,et al.  Robot-aided neurorehabilitation. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[53]  Michael J. Black,et al.  Automatic Detection and Tracking of Human Motion with a View-Based Representation , 2002, ECCV.

[54]  M Busnel,et al.  The robotized workstation "MASTER" for users with tetraplegia: description and evaluation. , 1999, Journal of rehabilitation research and development.

[55]  K. Rohr.  Towards model-based recognition of human movements in image sequences , 1994 .

[56]  G. Johansson.  Visual motion perception. , 1975, Scientific American.

[57]  W. Rymer,et al.  Robotic Devices for Movement Therapy After Stroke: Current Status and Challenges to Clinical Acceptance , 2002, Topics in stroke rehabilitation.

[58]  Paul A. Viola,et al.  Learning silhouette features for control of human motion , 2004, SIGGRAPH '04.

[59]  Jake K. Aggarwal,et al.  Tracking human motion using multiple cameras , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[60]  Michael Harrington,et al.  FlightTracker: a novel optical/inertial tracker for cockpit enhanced vision , 2004, Third IEEE and ACM International Symposium on Mixed and Augmented Reality.

[61]  M. Kawato,et al.  Formation and control of optimal trajectory in human multijoint arm movement , 1989, Biological Cybernetics.

[62]  Cordelia Schmid,et al.  Learning to Parse Pictures of People , 2002, ECCV.

[63]  Zhihui Wang,et al.  Personal customizing exercise with a wearable measurement and control unit , 2005, Journal of NeuroEngineering and Rehabilitation.

[64]  C. Anderson,et al.  Home or hospital for stroke Rehabilitation? Results of a randomized controlled trial : II: cost minimization analysis at 6 months. , 2000, Stroke.

[65]  Alberto Esquenazi,et al.  Instrumented Assessment of Muscle Overactivity and Spasticity with Dynamic Polyelectromyographic and Motion Analysis for Treatment Planning , 2004, American journal of physical medicine & rehabilitation.

[66]  Michael J. Black,et al.  Parameterized Modeling and Recognition of Activities , 1999, Comput. Vis. Image Underst..

[67]  R. Nelson,et al.  Low level recognition of human motion (or how to get your man without finding his body parts) , 1994, Proceedings of 1994 IEEE Workshop on Motion of Non-rigid and Articulated Objects.

[68]  Kamiar Aminian,et al.  Measurement of stand-sit and sit-stand transitions using a miniature gyroscope and its application in fall risk evaluation in the elderly , 2002, IEEE Transactions on Biomedical Engineering.

[69]  Larry S. Davis,et al.  A distributed system for real-time volume reconstruction , 2000, Proceedings Fifth IEEE International Workshop on Computer Architectures for Machine Perception.

[70]  A. Prochazka,et al.  Quantification of the UPDRS rigidity scale , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[71]  Patrick Langdon,et al.  Proceedings of the 1st Cambridge Workshop on Universal Access and Assistive Technology (CWUAAT 2002) , 2002 .

[72]  David J. Fleet,et al.  Learning parameterized models of image motion , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[73]  William Harwin,et al.  GENTLE/S project: design and ergonomics of a stroke rehabilitation system , 2002 .

[74]  Eric L. Huber,et al.  3-D real-time gesture recognition using proximity spaces , 1996, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96.

[75]  Huosheng Hu,et al.  Integration of Vision and Inertial Sensors for 3D Arm Motion Tracking in Home-based Rehabilitation , 2007, Int. J. Robotics Res..

[76]  Joan Lasenby,et al.  Modelling and Tracking Articulated Motion from Multiple Camera Views , 2000, BMVC.

[77]  Ian D. Reid,et al.  Uncalibrated and unsynchronized human motion capture: a stereo factorization approach , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[78]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[79]  A. Chiuso,et al.  Integration of shape constraints in data association filters , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[80]  Takeo Kanade,et al.  A real time system for robust 3D voxel reconstruction of human motions , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[81]  G. Wnek,et al.  Encyclopedia of biomaterials and biomedical engineering , 2008 .

[82]  M. Hallett,et al.  Virtual Reality–Induced Cortical Reorganization and Associated Locomotor Recovery in Chronic Stroke: An Experimenter-Blind Randomized Study , 2005, Stroke.

[83]  James W. Davis.  Hierarchical motion history images for recognizing human motion , 2001, Proceedings IEEE Workshop on Detection and Recognition of Events in Video.

[84]  T. M. Owings,et al.  Foot displacement but not velocity predicts the outcome of a slip induced in young subjects while walking. , 2000, Journal of biomechanics.

[85]  David J. Fleet,et al.  Stochastic Tracking of 3D Human Figures Using 2D Image Motion , 2000, ECCV.

[86]  Noomi Katz,et al.  Video capture virtual reality as a flexible and effective rehabilitation tool , 2004, Journal of NeuroEngineering and Rehabilitation.

[87]  J. D. Janssen,et al.  A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity , 1997, IEEE Transactions on Biomedical Engineering.

[88]  M. E. Austin,et al.  Development of a physiotherapy robot , 1999 .

[89]  Alex Pentland,et al.  Pfinder: real-time tracking of the human body , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[90]  A. Chiuso,et al.  Learning and exploiting invariants for multi-target tracking and data association , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[91]  M A Chamberlain,et al.  Home-based rehabilitation for people with stroke: a comparative study of six community services providing co-ordinated, multidisciplinary treatment , 2001, Clinical rehabilitation.

[92]  E Delahunt,et al.  Ankle function during hopping in subjects with functional instability of the ankle joint , 2007, Scandinavian journal of medicine & science in sports.

[93]  Bernt Schiele,et al.  Model-free tracking of cars and people based on color regions , 2006, Image Vis. Comput..

[94]  Larry S. Davis,et al.  Real-time 3D Motion Capture , 1998 .

[95]  M. Holden,et al.  Virtual Environment Training: A New Tool for Neurorehabilitation , 2002 .

[96]  M. Betke,et al.  The Camera Mouse: visual tracking of body features to provide computer access for people with severe disabilities , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[97]  Ian F. Akyildiz,et al.  Wireless sensor networks , 2007 .

[98]  Norman I. Badler,et al.  Inverse kinematics positioning using nonlinear programming for highly articulated figures , 1994, TOGS.

[99]  N. Hogan,et al.  Effects of robotic therapy on motor impairment and recovery in chronic stroke. , 2003, Archives of physical medicine and rehabilitation.

[100]  Hironobu Fujiyoshi,et al.  Real-time human motion analysis by image skeletonization , 1998, Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201).

[101]  Ronald Azuma,et al.  Hybrid inertial and vision tracking for augmented reality registration , 1999, Proceedings IEEE Virtual Reality (Cat. No. 99CB36316).

[102]  Noboru Ohnishi,et al.  The recovery of object shape and camera motion using a sensing system with a video camera and a gyro sensor , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[103]  S. Hesse,et al.  A mechanized gait trainer for restoration of gait. , 2000, Journal of rehabilitation research and development.

[104]  Diane J. Cook,et al.  Smart environments - technology, protocols and applications , 2004 .

[105]  Pat P. Banerjee,et al.  Extended-range hybrid tracker and applications to motion and camera tracking in manufacturing systems , 2000, IEEE Trans. Robotics Autom..

[106]  Huosheng Hu,et al.  Building A Visual Tracking System for Home-Based Rehabilitation , 2003 .

[107]  Nicola J. Ferrier,et al.  A digital video system for the automated measurement of repetitive joint motion , 2004, IEEE Transactions on Information Technology in Biomedicine.

[108]  Kenneth J Ottenbacher,et al.  A virtual reality environment for evaluation of a daily living skill in brain injury rehabilitation: reliability and validity. , 2003, Archives of physical medicine and rehabilitation.

[109]  Tieniu Tan,et al.  A survey on visual surveillance of object motion and behaviors , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[110]  David M. Bevly,et al.  A split-crank, servomotor-controlled bicycle ergometer design for studies in human biomechanics , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[111]  N.D. Georganas,et al.  Real-time 2 1/2 D head pose recovery for model-based video-coding , 2000, Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066].

[112]  Alex Mihailidis,et al.  The use of computer vision in an intelligent environment to support aging-in-place, safety, and independence in the home , 2004, IEEE Transactions on Information Technology in Biomedicine.

[113]  Takeo Kanade,et al.  Model-based tracking of self-occluding articulated objects , 1995, Proceedings of IEEE International Conference on Computer Vision.

[114]  Olivier D. Faugeras,et al.  3D Articulated Models and Multiview Tracking with Physical Forces , 2001, Comput. Vis. Image Underst..

[115]  J. Lenz.  A review of magnetic sensors , 1990, Proc. IEEE.

[116]  David Zeltzer,et al.  A survey of glove-based input , 1994, IEEE Computer Graphics and Applications.

[117]  Fay B. Horak,et al.  Head and Body Center of Gravity Control Strategies: Adaptations Following Vestibular Rehabilitation , 2003, Acta oto-laryngologica.

[118]  Hans-Peter Seidel,et al.  Combining 2d Feature Tracking And Volume Reconstruction For Online Video-Based Human Motion Capture , 2004, Int. J. Image Graph..

[119]  Yi Zhang,et al.  Study on adaptive Kalman filtering algorithms in human movement tracking , 2005, 2005 IEEE International Conference on Information Acquisition.

[120]  T Rahman,et al.  Performance statistics of a head-operated force-reflecting rehabilitation robot system. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[121]  Lisa K Simone,et al.  Design considerations for a wearable monitor to measure finger posture , 2005, Journal of NeuroEngineering and Rehabilitation.

[122]  David C. Hogg,et al.  Learning Behaviour Models of Human Activities , 1999, BMVC.

[123]  Cristian Sminchisescu,et al.  Covariance scaled sampling for monocular 3D body tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[124]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[125]  Heidi Sveistrup,et al.  Motor rehabilitation using virtual reality , 2004, Journal of NeuroEngineering and Rehabilitation.

[126]  G.C. Burdea,et al.  Virtual reality-enhanced stroke rehabilitation , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[127]  Constantinos Mavroidis,et al.  Smart Portable Rehabilitation Devices , 2005 .

[128]  D. Marr,et al.  Representation and recognition of the spatial organization of three-dimensional shapes , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[129]  Farshid Amirabdollahian,et al.  A case study on the effects of a haptic interface on human arm movements with implications for rehabilitation robotics , 2002 .

[130]  Patrick Richard Scheeper,et al.  A piezoelectric triaxial accelerometer , 1996 .

[131]  Patrice L. Weiss,et al.  Adapting an immersive virtual reality system for rehabilitation , 2003, Comput. Animat. Virtual Worlds.

[132]  Mohan M. Trivedi,et al.  Human Body Model Acquisition and Tracking Using Voxel Data , 2003, International Journal of Computer Vision.

[133]  Stefan Carlsson,et al.  Uncalibrated Motion Capture Exploiting Articulated Structure Constraints , 2004, International Journal of Computer Vision.

[134]  Greg Welch,et al.  Motion Tracking: No Silver Bullet, but a Respectable Arsenal , 2002, IEEE Computer Graphics and Applications.

[135]  N. Hogan,et al.  Assessing the Motor Status Score: A Scale for the Evaluation of Upper Limb Motor Outcomes in Patients after Stroke , 2002, Neurorehabilitation and neural repair.

[136]  M. Chamberlain,et al.  Improving community rehabilitation teams for people with stroke , 2001 .

[137]  Edward H. Adelson,et al.  Analyzing and recognizing walking figures in XYT , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[138]  Daniel Thalmann,et al.  A real time anatomical converter for human motion capture , 1996 .

[139]  I. Reid,et al.  Uncalibrated and unsynchronized human motion capture: a stereo factorization approach , 2004, CVPR 2004.

[140]  David C. Hogg,et al.  Generating Spatiotemporal Models from Examples , 1995, BMVC.

[141]  Thomas Picht,et al.  Study on the clinical application of pulsed DC magnetic technology for tracking of intraoperative head motion during frameless stereotaxy , 2006, Head & face medicine.

[142]  Huosheng Hu,et al.  Inertial motion tracking of human arm movements in stroke rehabilitation , 2005, IEEE International Conference Mechatronics and Automation, 2005.

[143]  Huosheng Hu,et al.  CSM-420 A Survey - Human Movement Tracking and Stroke Rehabilitation , 2004 .

[144]  Huosheng Hu,et al.  Applications of wearable inertial sensors in estimation of upper limb movements , 2006, Biomed. Signal Process. Control..

[145]  Kazuo Kyuma,et al.  Computer vision for computer games , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[146]  Mike Topping,et al.  Handy 1, a robotic aid to independence for severely disabled people , 1996 .

[147]  R. F. Boian,et al.  Dual Stewart-Platform Gait Rehabilitation System for Individuals Post-Stroke , 2003 .

[148]  H. Feys,et al.  Effect of a therapeutic intervention for the hemiplegic upper limb in the acute phase after stroke: a single-blind, randomized, controlled multicenter trial. , 1998, Stroke.

[149]  Huosheng Hu,et al.  Inertial sensors for motion detection of human upper limbs , 2007 .

[150]  N. Hogan,et al.  Increasing productivity and quality of care: robot-aided neuro-rehabilitation. , 2000, Journal of rehabilitation research and development.

[151]  Miguel Cazorla,et al.  Deformable Templates for Tracking and Analysis of Intravascular Ultrasound Sequences , 1997, EMMCVPR.

[152]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[153]  J. Cozens.  Robotic assistance of an active upper limb exercise in neurologically impaired patients. , 1999, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[154]  Ruggero Frezza,et al.  Integrating shape and dynamic probabilistic models for data association and tracking , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[155]  E. Jovanov,et al.  A WBAN System for Ambulatory Monitoring of Physical Activity and Health Status: Applications and Challenges , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[156]  Michael J. Black,et al.  Cardboard people: a parameterized model of articulated image motion , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[157]  V Popescu,et al.  Virtual reality-based orthopedic telerehabilitation. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[158]  Hans-Hellmut Nagel,et al.  Tracking Persons in Monocular Image Sequences , 1999, Comput. Vis. Image Underst..

[159]  A. Murat Tekalp,et al.  Stochastic kinematic modeling and feature extraction for gait analysis , 2003, IEEE Trans. Image Process..

[160]  R. V. van Lummel,et al.  The accuracy of measuring the kinematics of rising from a chair with accelerometers and gyroscopes. , 2006, Journal of biomechanics.

[161]  R. Plankers,et al.  Articulated soft objects for video-based body modeling , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[162]  Sf Wong,et al.  Reliable and fast human body tracking under information deficiency , 2003 .

[163]  Ali M. Malkawi,et al.  Building Performance Visualization Using Augmented Reality , 2004 .

[164]  Larry S. Davis,et al.  Learned Models for Estimation of Rigid and Articulated Human Motion from Stationary or Moving Camera , 2004, International Journal of Computer Vision.

[165]  Giulio Sandini,et al.  Visuo-inertial stabilization in space-variant binocular systems , 2000, Robotics Auton. Syst..

[166]  Thomas Beth,et al.  Characteristics in human motion - from acquisition to analysis , 2003 .