Pedestrian Segmentation from Uncalibrated Monocular Videos Using a Projection Map

Abstract

We present a new method for segmenting the foreground region of the image of multiple pedestrians from monocular surveillance videos. This method requires neither camera calibration nor planar ground assumption. The size and orientation of a pedestrian projection are estimated at each image point and registered in a pedestrian projection map. Individual pedestrians are segmented from the foreground region of input images using an expectation maximization (EM) algorithm and the constructed map.