PHACT: Parallel HOG and Correlation Tracking

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Waqas Hassan, Philip Birch, Rupert C. D. Young, Chris R. Chatwin

Published: 01 Jan 2014, Last Modified: 13 Nov 2024Video Surveillance and Transportation Imaging Applications 2014EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Histogram of Oriented Gradients (HOG) based methods for the detection of humans have become one of the most reliable methods of detecting pedestrians with a single passive imaging camera. However, they are not 100 percent reliable. This paper presents an improved tracker for the monitoring of pedestrians within images. The Parallel HOG and Correlation Tracking (PHACT) algorithm utilises self learning to overcome the drifting problem. A detection algorithm that utilises HOG features runs in parallel to an adaptive and stateful correlator. The combination of both acting in a cascade provides a much more robust tracker than the two components separately could produce.