PHACT: Parallel HOG and Correlation Tracking

Waqas Hassan; Philip Birch; Rupert Young; Chris Chatwin

doi:10.1117/12.2039181

5 March 2014 PHACT: Parallel HOG and Correlation Tracking

Waqas Hassan, Philip Birch, Rupert Young, Chris Chatwin

Proceedings Volume 9026, Video Surveillance and Transportation Imaging Applications 2014; 902602 (2014) https://doi.org/10.1117/12.2039181
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

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.

Citation Download Citation

Waqas Hassan, Philip Birch, Rupert Young, and Chris Chatwin "PHACT: Parallel HOG and Correlation Tracking", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 902602 (5 March 2014); https://doi.org/10.1117/12.2039181

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