A People Counting Method Based on Multiple Cameras Information Fusion

As people counting is becoming a research hotspot, a method for people counting based on multiple cameras information fusion is proposed. First, an adaptive sliding window algorithm is designed for people counting in single camera. Second, based on the homography theory, the common area between mult...

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Bibliographic Details
Published in:	2015 IEEE International Conference on Systems, Man, and Cybernetics pp. 2180 - 2185
Main Authors:	Qinglong Chang, Zhijun Song, Rongrong Shi, Jiayao Xu
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-10-2015
Subjects:	adaptive sliding window Algorithm design and analysis Cameras Filtering theory homography matrix Matrix decomposition multiple camera information fusion Noise measurement people counting Real-time systems Video surveillance
Online Access:	Get full text
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Summary:	As people counting is becoming a research hotspot, a method for people counting based on multiple cameras information fusion is proposed. First, an adaptive sliding window algorithm is designed for people counting in single camera. Second, based on the homography theory, the common area between multiple cameras is calculated. Finally, the object matching strategy considering the factor of occlusion, is designed for improving the people counting results of single camera and achieving the overall people counting of multiple cameras. Experiments results have shown that, this method can perform well in complex scenes.
DOI:	10.1109/SMC.2015.381