A computational approach to edge detection
Readings in computer vision: issues, problems, principles, and paradigms
Equal-distance sampling of superellipse models
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
Three-Dimensional Human Body Model Acquisition from Multiple Views
International Journal of Computer Vision
Segmentation and recovery of superquadrics: computational imaging and vision
Segmentation and recovery of superquadrics: computational imaging and vision
Human Body Model Acquisition and Tracking Using Voxel Data
International Journal of Computer Vision
Hybrid Monte Carlo Filtering: Edge-Based People Tracking
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Consistency and Coupling in Human Model Likelihoods
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Articulated Soft Objects for Multiview Shape and Motion Capture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Multiple View Reconstruction of People
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Improved Adaptive Gaussian Mixture Model for Background Subtraction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
Shape-From-Silhouette Across Time Part I: Theory and Algorithms
International Journal of Computer Vision
SCAPE: shape completion and animation of people
ACM SIGGRAPH 2005 Papers
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
Tracking People by Learning Their Appearance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast stochastic optimization for articulated structure tracking
Image and Vision Computing
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Markerless tracking of complex human motions from multiple views
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
A system for articulated tracking incorporating a clothing model
Machine Vision and Applications
Articulated mesh animation from multi-view silhouettes
ACM SIGGRAPH 2008 papers
Real-Time Shape Analysis of a Human Body in Clothing Using Time-Series Part-Labeled Volumes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
The Naked Truth: Estimating Body Shape Under Clothing
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Markerless Motion Capture through Visual Hull, Articulated ICP and Subject Specific Model Generation
International Journal of Computer Vision
International Journal of Computer Vision
Coupled Visual and Kinematic Manifold Models for Tracking
International Journal of Computer Vision
Optimization and Filtering for Human Motion Capture
International Journal of Computer Vision
A Study on Smoothing for Particle-Filtered 3D Human Body Tracking
International Journal of Computer Vision
Physics-Based Person Tracking Using the Anthropomorphic Walker
International Journal of Computer Vision
A bayesian approach to image-based visual hull reconstruction
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Simultaneous shape and pose adaption of articulated models using linear optimization
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
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We present a novel approach for 3D human body shape model adaptation to a sequence of multi-view images, given an initial shape model and initial pose sequence. In a first step, the most informative frames are determined by optimization of an objective function that maximizes a shape-texture likelihood function and a pose diversity criterion (i.e. the model surface area that lies close to the occluding contours), in the selected frames. Thereafter, a batch-mode optimization is performed of the underlying shape- and pose-parameters, by means of an objective function that includes both contour and texture cues over the selected multi-view frames. Using above approach, we implement automatic pose and shape estimation using a three-step procedure: first, we recover initial poses over a sequence using an initial (generic) body model. Both model and poses then serve as input to the above mentioned adaptation process. Finally, a more accurate pose recovery is obtained by means of the adapted model. We demonstrate the effectiveness of our frame selection, model adaptation and integrated pose and shape recovery procedure in experiments using both challenging outdoor data and the HumanEva data set.