Zhenqiu Xiao1,*, Bin Yang2, Desy Tjahjadi3
CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638
Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a… More >
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