Inverse kinematics positioning using nonlinear programming for highly articulated figures
ACM Transactions on Graphics (TOG)
Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Stochastic Tracking of 3D Human Figures Using 2D Image Motion
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Generative modeling for continuous non-linearly embedded visual inference
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Physics-based Animation (Graphics Series)
Physics-based Animation (Graphics Series)
Priors for People Tracking from Small Training Sets
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
3D People Tracking with Gaussian Process Dynamical Models
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
Gaussian Process Dynamical Models for Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accurate Human Motion Capture Using an Ergonomics-Based Anthropometric Human Model
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Physics-Based Person Tracking Using the Anthropomorphic Walker
International Journal of Computer Vision
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Stick it articulated tracking using spatial rigid object priors
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Predicting Articulated Human Motion from Spatial Processes
International Journal of Computer Vision
Unscented kalman filtering for articulated human tracking
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Data-driven importance distributions for articulated tracking
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
Simultaneous partitioned sampling for articulated object tracking
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Group-Valued regularization framework for motion segmentation of dynamic non-rigid shapes
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Motion-based mesh segmentation using augmented silhouettes
Graphical Models
Natural metrics and least-committed priors for articulated tracking
Image and Vision Computing
Spatial measures between human poses for classification and understanding
AMDO'12 Proceedings of the 7th international conference on Articulated Motion and Deformable Objects
GPU accelerated likelihoods for stereo-based articulated tracking
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part II
Unscented Kalman Filtering on Riemannian Manifolds
Journal of Mathematical Imaging and Vision
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We present an analysis of the spatial covariance structure of an articulated motion prior in which joint angles have a known covariance structure. From this, a well-known, but often ignored, deficiency of the kinematic skeleton representation becomes clear: spatial variance not only depends on limb lengths, but also increases as the kinematic chains are traversed. We then present two similar Gaussian-like motion priors that are explicitly expressed spatially and as such avoids any variance coming from the representation. The resulting priors are both simple and easy to implement, yet they provide superior predictions.