27 October 2013 Real-time and reliable human detection in clutter scene
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Proceedings Volume 8919, MIPPR 2013: Pattern Recognition and Computer Vision; 891914 (2013) https://doi.org/10.1117/12.2031338
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
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.
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Yumei Tan, Yumei Tan, Xiaoshu Luo, Xiaoshu Luo, Haiying Xia, Haiying Xia, "Real-time and reliable human detection in clutter scene", Proc. SPIE 8919, MIPPR 2013: Pattern Recognition and Computer Vision, 891914 (27 October 2013); doi: 10.1117/12.2031338; https://doi.org/10.1117/12.2031338

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