TITLE:
Human Body Tracking and Pose Estimation Using Modified Camshift Algorithm
AUTHORS:
Seung-Jun Hwang, Jae-Hong Min, In-Gyu Kim, Seung-Jae Park, Gwang-Pyo Ahn, Joong-Hwan Baek
KEYWORDS:
Body Tracking; CAMShift; Pose Estimation; Kalman Filter; Weighted Search Windows
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.6 No.5B,
October
12,
2013
ABSTRACT: In this paper, we propose multiple CAMShift Algorithm based on Kalman filter and weighted search windows that extracts skin color area and tracks several human body parts for real-time human tracking system. The CAMShift Algorithm we propose searches the skin color region by detecting the skin color area from background model. Kalman filter stabilizes the floated search area of CAMShift Algorithm. Each occlusion areas are 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 modified Camshaft algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.