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Pedestrian detection system based on stereo vision for mobile robot

Bodam Nam, Sung-il Kang, Hyunki Hong
Dept. of Image, Graduate School of Advanced Imaging and Film, Chung-ang University, Seoul, Korea
17th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV), 2011

@inproceedings{nam2011pedestrian,

   title={Pedestrian detection system based on stereo vision for mobile robot},

   author={Nam, B. and Kang, S. and Hong, H.},

   booktitle={Frontiers of Computer Vision (FCV), 2011 17th Korea-Japan Joint Workshop on},

   pages={1–7},

   organization={IEEE},

   year={2011}

}

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This paper presents a novel Graphics Processing Unit (GPU)-based system for pedestrian detection with stereo vision in real images on mobile robot. The process of obtaining a dense disparity map on a GPU for real-time applications and the edge property of the scene to extract a region of interest (ROI) is designed. After extracting the histograms of the oriented gradients on the ROIs, a support vector machine (SVM) classifies them as pedestrian and non-pedestrian types. The system employs the recognition by components method, which compensates for the pose and articulation changes of pedestrians. In order to effectively track spatial pedestrian estimates over sequences, sub-windows in distinctive parts of human beings are used as measurements of the Kalman filter.
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