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Video-based crowd counting with information entropy
The 27th Chinese Control and Decision Conference (2015 CCDC)
As a key indicator of safety, the number of persons in pubic venues is quite important. However, most algorithms require a burdensome training, which is far away from practical application. In this work, we introduce a counting approach with information entropy (IE). Without extracting features or tracking objects, this algorithm greatly simplifies the process of counting. Firstly, the moving objects are segmented by background subtraction. And then interested targets are normalized to avoiddoi:10.1109/ccdc.2015.7161714 fatcat:vakt2yblivbwhjsz4lwpcoqzke