Adaptive Silhouette Extraction In Dynamic Environments Using Fuzzy Logic
He, Zhihai, 1973-
Keller, James M.
Anderson, Derek T., 1979-
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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. In a previous paper, we addressed some of the challenges in silhouette extraction and human tracking in a real-world unconstrained environment where the background is complex and dynamic. We extracted features from image regions, accumulated the feature information over time, fused high-level knowledge with low-level features, and built a time-varying background model. A problem with our system is that by adapting the background model, objects moved by a human are difficult to handle. In order to reinsert them into the background, we run the risk of cutting off part of the human silhouette, such as in a quick arm movement. In this paper, we develop a fuzzy logic inference system to detach the silhouette of a moving object from the human body. Our experimental results demonstrate that the fuzzy inference system is very efficient and robust.
Electrical and Computer Engineering Publications (MU)
Chen X, He Z, Keller J, Anderson D & Skubic M, "Adaptive Silhouette Extraction In Dynamic Environments Using Fuzzy Logic," Proceedings, IEEE International Conference on Fuzzy Systems, Vancouver, British Columbia, Canada, July 16-21, 2006, p 236-243.