Abstract
Optical flow can be used to segment a moving object from its backgrounds and track it. In this paper, an Enhanced Lucas-Kanade optical flow technique was used to improve human detection in terms of speed and accuracy. We combined object segmentation output with a human detector using an optical flow algorithm. The proposed technique used the optical flow to find the area of interest to complete object segmentation and use those results as an input for the human detector. This technique has been developed to be used in surveillance systems. Our experiments indicated that the proposed method was 37% faster and 118% more accurate than the standard Felzenszwalb PFF detector.
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