Human body motion segmentation in a complex scene
Pattern Recognition
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
BUILD-IT: a planning tool for construction and design
CHI 98 Cconference Summary on Human Factors in Computing Systems
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
A new foreground extraction scheme for video streams
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Video segmentation using fast marching and region growing algorithms
EURASIP Journal on Applied Signal Processing - Image analysis for multimedia interactive services - part I
Adaptive Color- and Edge-Based Image Segmentation Using Fuzzy Techniques
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
A framework for heading-guided recognition of human activity
Computer Vision and Image Understanding
Hardware-accelerated jaggy-free visual hulls with silhouette maps
Proceedings of the ACM symposium on Virtual reality software and technology
Video segmentation using fast marching and region growing algorithms
EURASIP Journal on Applied Signal Processing
Visual hull with silhouette maps
ICVR'07 Proceedings of the 2nd international conference on Virtual reality
An edge-based approach to motion detection
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
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A new segmentation algorithm is derived, based on an object-background probability estimate exploiting the experimental fact that the statistics of local image derivatives show a Laplacian distribution. The objects' simple connectedness is included directly into the probability estimate and leads to an iterative optimization approach that can be implemented efficiently. This new approach avoids early thresholding, explicit edge detection, motion analysis, and grouping.