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  • 标题:A Robust Human Detection System
  • 本地全文:下载
  • 作者:Amit Kumar Gautam ; Ajay Kaushik ; Subradeb Choudhary
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2017
  • 卷号:9
  • 期号:07
  • 页码:459-465
  • 出版社:Engg Journals Publications
  • 摘要:In the present scenario, Video Surveillance is receiving tremendous attention. It has a wide range of applications such as it can be used in Border areas of a country, in market areas and also in restricted areas for monitoring objects. Human Detection is a field of Video Surveillance where monitoring of humans take place i.e. the human is detected first and its trajectory is estimated for the purpose of monitoring. In this paper, a robust human detection system is proposed. The Human Detection System consists of two stages. The first stage involves Image Pre-processing where the Motion region is extracted and Image Segmentation is applied to this motion region. The second stage classifies the segmented image as a human or a non-human based on Aspect Ratio of Human. So, we can say that the Motion region is incorporated with the Aspect Ratio feature to propose a Robust Human Detection Method. A Dataset is made where the background colour matches with the Human Skin Colour. In this situation, it is very difficult to track the human. We propose a system where we can track human under such conditions. The system is tested in PETs Database also and an overall Detection Rate of 85% is reported. However, the Detection rate gets reduced drastically when the human is occluded in the scene.
  • 关键词:Frame Differencing; Aspect Ratio; Human Detection; HoG.
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