Background subtraction based on pixel clustering
Yanghong Zhang, Qing He, Haibin Wang, Guan Guan, Tao Xu, Chen Haodong · 2016
Nowadays motion detection in video sequences is the basis for the high-level analytics and applications. After ViBe is proposed, the current mainstream detection algorithm is based on pixel level to construct the background model for the foreground / background segmentation. Influenced by this kind of algorithm, this paper proposes a spatiotemporal-based algorithm to construct an approximate precise background model. Difference with most of detection algorithms using the fixed threshold to judge the similarity of the pixel, this paper adopts the property of color clustering to determine the similarity dynamically. The experimental results on the 2012 Change Detection dataset show that the algorithm outperforms most state-of-the-art algorithms.