Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Human motion analysis: a review
Computer Vision and Image Understanding
The theory of evolution strategies
The theory of evolution strategies
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Shape Matching and Object Recognition Using Shape Contexts
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
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Tracking Articulated Body by Dynamic Markov Network
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
Discriminative Density Propagation for 3D Human Motion Estimation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Monocular 3-D Tracking of the Golf Swing
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering 3D Human Body Configurations Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimum tracking with evolution strategies
Evolutionary Computation
3D human model and joint parameter estimation from monocular image
Pattern Recognition Letters
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Silhouette representation and matching for 3D pose discrimination - A comparative study
Image and Vision Computing
Computer Vision and Image Understanding
3D human pose recovery from image by efficient visual feature selection
Computer Vision and Image Understanding
Quantifying human reconstruction accuracy for voxelcarving in a sporting environment
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Estimating pose of articulated objects using low-level motion
Computer Vision and Image Understanding
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
State of the Art Report on Video-Based Graphics and Video Visualization
Computer Graphics Forum
Differential evolution based human body pose estimation from point clouds
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Comparing evolutionary algorithms and particle filters for Markerless Human Motion Capture
Applied Soft Computing
Generative tracking of 3D human motion in latent space by sequential clonal selection algorithm
Multimedia Tools and Applications
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We present a generative method for reconstructing 3D human motion from single images and monocular image sequences. Inadequate observation information in monocular images and the complicated nature of human motion make the 3D human pose reconstruction challenging. In order to mine more prior knowledge about human motion, we extract the motion subspace by performing conventional principle component analysis (PCA) on small sample set of motion capture data. In doing so, we also reduce the problem dimensionality so that the generative pose recovering can be performed more effectively. And, the extracted subspace is naturally hierarchical. This allows us to explore the solution space efficiently. We design an annealed genetic algorithm (AGA) and hierarchical annealed genetic algorithm (HAGA) for human motion analysis that searches the optimal solutions by utilizing the hierarchical characteristics of state space. In tracking scenario, we embed the evolutionary mechanism of AGA into the framework of evolution strategy for adapting the local characteristics of fitness function. We adopt the robust shape contexts descriptor to construct the matching function. Our methods are demonstrated in different motion types and different image sequences. Results of human motion estimation show that our novel generative method can achieve viewpoint invariant 3D pose reconstruction.