Research of Human Body Detection and Tracking Algorithm

Abstract:

In this paper, the proposed algorithm regards the human body object character symbol using Support Vector Machine (SVM) classifier to train and classify Histogram of Oriented Gradient (HOG) features, which improve the accuracy of human body detection. We use optical flow tracking algorithm based on corner points of the contour for tracking. Kalman filter is regarded as the predictor to predict the size and location of the searching object. Also, the size and location of track window is real-time updated. In this paper, we present an object tracking algorithm for multi-media teaching video shoot. Target tracking technology is used for the video image processing analysis. By extracting moving object, we can get information in the subsequent frames to determine the trajectory and size of moving objects. After analysis of a large number of experiments, we can draw the conclusion that the algorithm is effective.

• Periodical: Advanced Materials Research (Volumes 791-793)
• Pages: 1023-1027
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.791-793.1023
• Online since: September 2013
• Authors: Gang Zhang, Bin Ouyang, Lu Ming Yu, Lei Zhang
• Keywords: Histograms of Oriented Gradient (HOG), Human Detection, Optical Flow Tracking, SVM Classifier

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