A People Counting System Based on Face-Detection
Tsong-Yi Chen, Chao-Ho Chen, Da-Jinn Wang, Yi-Li Kuo · 2010
This paper presents an automatic people counting system based on face detection, where the number of people passing through a gate or door is counted by setting a video camera. The basic idea is to first use the frame difference to detect the rough edges of moving people and then use the chromatic feature to locate the people face. Based on NCC (Normalized Color Coordinates) color space, the initial face candidate is obtained by detecting the skin color region and then the face feature of the candidate is analyzed to determine whether the candidate is real face or not. After face detection, a person will be tracked by following the detected face and then this person will counted if its face touches the counting line. Experimental results show that the proposed people counting algorithm can provide a high count accuracy of 80% on average for the crowded pedestrians.