An adaptive appearance model approach for model-based articulated object tracking
2006
Conference Paper
ps
The detection and tracking of three-dimensional human body models has progressed rapidly but successful approaches typically rely on accurate foreground silhouettes obtained using background segmentation. There are many practical applications where such information is imprecise. Here we develop a new image likelihood function based on the visual appearance of the subject being tracked. We propose a robust, adaptive, appearance model based on the Wandering-Stable-Lost framework extended to the case of articulated body parts. The method models appearance using a mixture model that includes an adaptive template, frame-to-frame matching and an outlier process. We employ an annealed particle filtering algorithm for inference and take advantage of the 3D body model to predict self occlusion and improve pose estimation accuracy. Quantitative tracking results are presented for a walking sequence with a 180 degree turn, captured with four synchronized and calibrated cameras and containing significant appearance changes and self-occlusion in each view.
Author(s): | Balan, A. and Black, M. J. |
Book Title: | Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR |
Volume: | 1 |
Pages: | 758--765 |
Year: | 2006 |
Month: | June |
Department(s): | Perzeptive Systeme |
Bibtex Type: | Conference Paper (inproceedings) |
Paper Type: | Conference |
Address: | New York, NY |
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BibTex @inproceedings{Balan:CVPR:2006, title = {An adaptive appearance model approach for model-based articulated object tracking}, author = {Balan, A. and Black, M. J.}, booktitle = {Proc. IEEE Conf. on Computer Vision and Pattern Recognition, CVPR}, volume = {1}, pages = {758--765}, address = {New York, NY}, month = jun, year = {2006}, doi = {}, month_numeric = {6} } |