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논문검색

An Improvement to the Algorithm of Human Body Detection in Video Surveillance

초록

영어

Human body detection in video surveillance is an important research point, which has been devoted for many years by researchers. But it can’t detect human body with the feature of HoG and classifier of SVM. This paper proposes an improvement measure to the traditional algorithm of human body detection in order to detect human body in video surveillance in real time. Through the Integral images to speed up the computation of features of HoG and HoD under the condition of Kinect, It can’t detect human body in video surveillance in real time. As human body detection using HoG features can’t meet the real-time requirement in the current time. This paper abandon the time-consuming processing of computing features of HoG with three line interpolation and Gauss filter in terms of traditional algorithm of human body detection, and This paper introduces the notion of Integral images to speed up the computation of the features of HoG and HoD with the help of Kinect. As a result, Our improved algorithm can get a better time performance than ever, which can get the average detection rate of 30~40 FPS, current performance getting promotion greatly than ever, under the condition of CPU 3.10Ghz, RAM 4 GB, 640*480 detection window.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Algorithm Realization and Comparison
 4. Experiment Results and Analysis
 5. Conclusion
 References

저자정보

  • Jingjing Yang School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China
  • Benzhen Guo School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China
  • Xiao Zhang School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China

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