Pedestrian Detection Using Boosted Features over Many Frames

A scanning window type pedestrian detector is presented that uses both appearance and motion information to find walking people in surveillance video. We extend the work of Viola, Jones and Snow [18] to use many more frames as input to the detector thus allowing a much more detailed analysis of motion. The resulting detector is about an order of magnitude more accurate than the detector of Viola, Jones and Snow. It is also computationally efficient, processing frames at the rate of 5 Hz on a 3 GHz Pentium processor. The detector\'s accuracy and speed make it practical for real applications.