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Proceedings Paper

Real-time and reliable human detection in clutter scene
Author(s): Yumei Tan; Xiaoshu Luo; Haiying Xia
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Paper Abstract

To solve the problem that traditional HOG approach for human detection can not achieve real-time detection due to its time-consuming detection, an efficient algorithm based on first segmentation then identify method for real-time human detection is proposed to achieve real-time human detection in clutter scene. Firstly, the ViBe algorithm is used to segment all possible human target regions quickly, and more accurate moving objects is obtained by using the YUV color space to eliminate the shadow; secondly, using the body geometry knowledge can help to found the valid human areas by screening the regions of interest; finally, linear support vector machine (SVM) classifier and HOG are applied to train for human body classifier, to achieve accurate positioning of human body’s locations. The results of our comparative experiments demonstrated that the approach proposed can obtain high accuracy, good real-time performance and strong robustness.

Paper Details

Date Published: 27 October 2013
PDF: 8 pages
Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 891914 (27 October 2013); doi: 10.1117/12.2031338
Show Author Affiliations
Yumei Tan, Guangxi Normal Univ. (China)
Xiaoshu Luo, Guangxi Normal Univ. (China)
Haiying Xia, Guangxi Normal Univ. (China)


Published in SPIE Proceedings Vol. 8919:
MIPPR 2013: Pattern Recognition and Computer Vision
Zhiguo Cao, Editor(s)

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