Study Of Methods For Moving Human Detection And Tracking In Image Sequences

The detection and tracking of human motions is key to the visual analysis of human movement, it is also one of important fields to computer visions research. It involves wide application foreground and great economic value in smart security surveillance, advanced user interface, the details analysis of human movement, etc.Image sequences of moving objects can be divided into two types by which background is static or dynamic. We major study detection and tracking algorithms of moving human about the static background in this thesis.This article main launches the research based on the image sequence movement human detection and the movement human tracking two aspects. In the phase of human detection, we establish an adaptive Gaussian model for background, which can handle the illumination variety and small motion in The background,then we obtain the foreground regions .In order to deal with the shadow which is critical for accurate object detection and tracking, we implicitly discuss the feature of shadow in the view of color constancy, and propose a method for shadow detection. The experimental results show that our proposed method can be able to remove shadow and extract the foreground moving objects accurately. On the research of targets tracking,We present an algorithm of tracking moving targets based on Kalman filtering, which accomplishes human tracking by targets detection, motion estimation and targets matching three modules. Finally introduces a image gathering system based on the static camera and the choice of composition of the module and the character of each part.