The Application of A-CNN in Crowd Counting of Scenic Spots
Wanli Luo and Jialiang Wang
College of Information and Engineering, Sichuan Tourism University
No. 459 Hongling Road, Longquanyi District, Chengdu, Sichuan 610000, China
In places where people are concentrated, such as scenic spots, the statistical accuracy of existing crowd statistics algorithms is not enough. In order to solve this problem, a crowd counting algorithm based on adaptive convolution neural network (A-CNN) is proposed, which is based on video monitoring technology. The process of its pooling is dynamically adjusted according to different feature graphs. Then the pooled weights are adjusted adaptively according to the contents of each pooled domain. Therefore, CNN can extract more accurate features when processing different pooled domains under different iteration times, so as to achieve adaptive effect finally. The experimental results show that the proposed A-CNN algorithm has improved the recognition accuracy.
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