CASIA OpenIR  > 智能感知与计算研究中心
Estimating the Number of People in Crowded Scenes by MID Based Foreground Segmentation and Head-shoulder Detection
Min Li; Zhaoxiang Zhang; Kaiqi Huang; Tieniu Tan
2008-12-08
Conference Name19th International Conference on Pattern Recognition
Source Publication Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Pages1-4
Conference Date8-11 December 2008
Conference PlaceTampa, Florida, USA
AbstractThis 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.
KeywordLayout Head Image Segmentation Surveillance Histograms Feature Extraction Shape Detection Algorithms Laboratories Pattern Recognition
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12715
Collection智能感知与计算研究中心
Corresponding AuthorMin Li
Recommended Citation
GB/T 7714
Min Li,Zhaoxiang Zhang,Kaiqi Huang,et al. Estimating the Number of People in Crowded Scenes by MID Based Foreground Segmentation and Head-shoulder Detection[C],2008:1-4.
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