Authors: Huiyuan Fu Huadong Ma Hongtian Xiao
Publish Date: 2013/08/08
Volume: 73, Issue: 1, Pages: 273-289
Abstract
Reliable and realtime crowd counting is one of the most important tasks in intelligent visual surveillance systems Most previous works only count passing people based on color information Owing to the restrictions of color information influences themselves for multimedia processing they will be affected inevitably by the unpredictable complex environments eg illumination occlusion and shadow To overcome this bottleneck we propose a new algorithm by multimodal joint information processing for crowd counting In our method we use color and depth information together with a ordinary depth camera eg Microsoft Kinect Specifically we first detect each head of the passing or still person in the surveillance region with adaptive modulation ability to varying scenes on depth information Then we track and count each detected head on color information The characteristic advantage of our algorithm is that it is scene adaptive which means the algorithm can be applied into all kinds of different scenes directly without additional conditions Based on the proposed approach we have built a practical system for robust and fast crowd counting facing complicated scenes Extensive experimental results show the effectiveness of our proposed methodThis work was supported by the China National Funds for Distinguished Young Scientists under Grant No60925010 Natural Science Foundation of China under Grant No61272517 The Research Fund for the Doctoral Program of Higher Education of China under Grant No20120005130002 the Cosponsored Project of Beijing Committee of Education the Funds for Creative Research Groups of China under Grant No61121001 and the Program for Changjiang Scholars and Innovative Research Team in University under Grant NoIRT1049
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