DocumentCode :
1565889
Title :
Adaptive Silouette Extraction and Human Tracking in Complex and Dynamic Environments
Author :
Chen, Xia ; He, Zhaoshui ; Anderson, Dave ; Keller, James ; Skubic, Marjorie
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ., Columbia, MO, USA
fYear :
2006
Firstpage :
561
Lastpage :
564
Abstract :
Extracting a human silhouette from an image is the enabling step for many high-level vision processing tasks, such as human tracking and activity analysis. Although there are a number of silhouette extraction and human tracking algorithms proposed in the literature, most approaches work efficiently only in constrained environments where the background is relatively simple and static. In this work, we propose to address the challenges in silhouette extraction and human tracking in a real-world unconstrained environment where the background is complex and dynamic. We extract features from image regions, accumulate the feature information over time, fuse the high-level knowledge with low-level features, and build a time-varying background model. We develop a fuzzy decision process to detach foreground moving objects from the human body. Our experimental results demonstrate that the algorithm is very efficient and robust.
Keywords :
feature extraction; fuzzy logic; tracking; adaptive silhouette extraction; feature extraction; fuzzy decision process; human tracking algorithm; time-varying background model; Biological system modeling; Data mining; Event detection; Feature extraction; Helium; Hidden Markov models; Humans; Image segmentation; Monitoring; Robustness; Image segmentation; fuzzy logic; human tracking; silouette extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1522-4880
Print_ISBN :
1-4244-0480-0
Type :
conf
DOI :
10.1109/ICIP.2006.312487
Filename :
4106591
Link To Document :
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