Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hyperplane Approximation for Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Estimating Human Body Configurations Using Shape Context Matching
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Inferring 3D Structure with a Statistical Image-Based Shape Model
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Sparse Probabilistic Learning Algorithm for Real-Time Tracking
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Filtering Using a Tree-Based Estimator
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Fast Pose Estimation with Parameter-Sensitive Hashing
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
3D human pose from silhouettes by relevance vector regression
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Kinematic jump processes for monocular 3D human tracking
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
Human body pose detection using Bayesian spatio-temporal templates
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Temporal motion models for monocular and multiview 3D human body tracking
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
3D Periodic Human Motion Reconstruction from 2D Motion Sequences
Neural Computation
Human animation from 2D correspondence based on motion trend prediction
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Pose estimation and tracking using multivariate regression
Pattern Recognition Letters
Detecting Humans in 2D Thermal Images by Generating 3D Models
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
Non-rigid object tracking in complex scenes
Pattern Recognition Letters
Action recognition feedback-based framework for human pose reconstruction from monocular images
Pattern Recognition Letters
Leveraging the talent of hand animators to create three-dimensional animation
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Hierarchical space-time model enabling efficient search for human actions
IEEE Transactions on Circuits and Systems for Video Technology
International Journal of Computer Vision
Patch-based pose inference with a mixture of density estimators
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Layer-based mannequin reconstruction and parameterization from 3D range data
GMP'08 Proceedings of the 5th international conference on Advances in geometric modeling and processing
Learning local models for 2D human motion tracking
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Articulated-body tracking through anisotropic edge detection
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Predicting 3d people from 2d pictures
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Human animation from 2d correspondence based on motion trend prediction
CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
Tracking with the kinematics of extremal contours
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Multivariate relevance vector machines for tracking
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Dynamic kernel-based progressive particle filter for 3d human motion tracking
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Robust decentralized multi-model adaptive template tracking
Pattern Recognition
Analyzing and evaluating markerless motion tracking using inertial sensors
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
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We describe a sparse Bayesian regression method for recovering 3D human body motion directly from silhouettes extracted from monocular video sequences. No detailed body shape model is needed, and realism is ensured by training on real human motion capture data. The tracker estimates 3D body pose by using Relevance Vector Machine regression to combine a learned autoregressive dynamical model with robust shape descriptors extracted automatically from image silhouettes. We studied several different combination methods, the most effective being to learn a nonlinear observation-update correction based on joint regression with respect to the predicted state and the observations. We demonstrate the method on a 54-parameter full body pose model, both quantitatively using motion capture based test sequences, and qualitatively on a test video sequence.