Estimating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection

This paper proposes a novel method to address the problem of estimating the number of people in surveillance scenes with people gathering and waiting. The proposed method combines a MID (Mosaic Image Difference) based foreground segmentation algorithm and a HOG (Histograms of Oriented Gradients) based head-shoulder detection algorithm to provide an accurate estimation of people counts in the observed area. In our framework, the MID-based foreground segmentation module provides active areas for the head-shoulder detection module to detect heads and count the number of people. Numerous experiments are conducted and convincing results demonstrate the effectiveness of our method.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Min Li, Zhaoxiang Zhang, Kaiqi Huang, Tieniu Tan
• Keywords: Computer Vision, Foreground Segmentation, Foreground Segmentation Module, Head-shoulder Detection Algorithm, ICPR 2008