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http://dx.doi.org/10.12673/jkoni.2012.16.3.545

Human Body Tracking and Pose Estimation Using CamShift Based on Kalman Filter and Weighted Search Windows  

Min, Jae-Hong (Korea Aerospace University)
Kim, In-Gyu (Korea Aerospace University)
Hwang, Seung-Jun (Korea Aerospace University)
Baek, Joong-Hwan (Korea Aerospace University)
Abstract
In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.
Keywords
Body Tracking; CAMShift; Pose Estimation; Kalman Filter; Weighted Search Windows;
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