Pedestrian detection by modeling local convex shape features

This paper presents a pedestrian model built collectively on a group of strong local convex shape descriptors. The pedestrian model captures the most important features of a pedestrian: head, body contour, arms, legs and crotch, and is robust to variances in appearances and partial occlusions. For an image set of 2571 pedestrians and 4369 car and background images, the pedestrian recognition system, which was built upon the proposed pedestrian model, gave a recognition rate of 98.8% with a false positive

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Jungme Park, Yun Luo, Haoxing Wang, Yi Lu Murphey
• Keywords: Computer Vision, Convex Shape Descriptors, ICPR 2008, Pedestrian Model, Pedestrian Recognition System