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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