Crowd Density Estimation Using Taylor Expansion and Local Texture Feature
Chih‐Chin Lai, Hsien-Chun Chiu · 2019
Crowd density estimation from images or videos is an important subject for crowd monitoring and safety control. In this paper, we propose a crowd density estimation method based on the Taylor expansion and the local binary count operator. Crowd density classification is performed using a support vector machine. Experiments on the PETS 2009 dataset are provided to demonstrate the feasibility of the proposed approach.