Title :
Pedestrian counting based on spatial and temporal analysis
Author :
Zhongjie Yu ; Chen Gong ; Jie Yang ; Li Bai
Author_Institution :
Instn. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Pedestrian counting is an important component of video processing. Existing works with overhead cameras are mainly based on visual tracking, the robustness of which is rather limited. By proposing the novel spatial-temporal matrix, this paper aims to count pedestrians without tracking. As a result, a more robust and efficient pedestrian counting algorithm can be developed. Extensive experiment reveal that our system achieves satisfying performances in terms of both accuracy and efficiency.
Keywords :
matrix algebra; pedestrians; support vector machines; video surveillance; pedestrian counting algorithm; spatial-and-temporal analysis; spatial-temporal matrix; support vector machine; video camera; video processing; video surveillance; visual tracking; Bandwidth; Cameras; Clustering algorithms; Conferences; Feature extraction; Real-time systems; Support vector machines; Mean-shift Clustering; Pedestrian Counting; Spatial and Temporal Analysis; Support Vector Machine; Video Surveillance;
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
DOI :
10.1109/ICIP.2014.7025492
