Abstract
As the number of social insecurity in regard to social crimes is on its rise, it requires a CCTV camera a higher accuracy in detecting the objects including pedestrians for efficient work of catching criminals. As the importance of the function of pedestrian detection is socially agreed upon, more studies on image and video based pedestrian detection have been conducted. In terms of that, the goal of this study is classification of pedestrian in two categories as a child and an adult. In this study, Haar cascade classifiers are used. This method first detects a full body and a head. Then, it measures the biometry given the relative proportioning length of a full body and a head. Moving average algorithm is used to obtain threshold ratio. Experimental results show the accuracy 100% for children and 64.5% for adults.
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