Simultaneous object tracking and pedestrian detection using HOGs on contour

This paper presents a novel method for simultaneous pedestrian detection and tracking in image sequences. The motion detection and tracking are addressed in a common framework that employs a geometric active contour model, in which an evolving curve was formulated by the level set method. The pedestrian detection module is started after the curve evolution, which stops the propagating contour on the object boundary. The HOG features are extracted on a set of points located on a narrow band around the zero level set, and serve as cues for pedestrian detection. Experimental results demonstrate that the proposed HOG descriptor provides more information representing pedestrians' distinguishing shape features than the original one.