Detection phase

Pedestrian Detection and Tracking

Prof. Ju-jang Lee, KAIST, Jan 2011 - Dec 2011

Pedestrian detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected pedestrian because of their dynamic and unpredictable behavior.

In this project, we proposed a Simultaneous Detection and Tracking (SDAT) method using Gaussian Particle Swarm Optimization (Gaussian-PSO) for pedestrian detection with the Histograms of Oriented Gradients (HOG) features to achieve a fast and accurate performance. Keeping the robustness of HOG features on human detection, we raise the process speed in detection and tracking so that it can be used for real-time applications. These advantages are given by a simple process which needs just one linear-SVM classifier with HOG features and Gaussian-PSO procedure for the both of detection and tracking.


. Fast human detection using Gaussian Particle Swarm Optimization. In IEEE DEST, 2011.

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