Video-based Human Motion Detection And Tracking

The detection and tracking of moving human is a valuable field in computer vision. This paper discusses detection and tracking of moving human target from static background in video sequences. The paper focuses on moving object detection,shadow inhibition and moving object tracking and so on in the single stationary camera environment. The major research contents are as follows.Firstly, on motion detection technology,discuss the algorithms about establishment and update of the background. On the basis of the background subtraction for target detection, realize the real-time shadows suppression algorithm based on YUV color space. Then achieve moving target detection, through binary conversion and using morphological methods and regional analysis.It is the aim that the target foreground objects can be segregated completely from foreground pixels. After segregating, we can gather the characteristics of each foreground object respectively. Based on spatial continuity of target objects, with mathematical morphology and binary connected components analysis, we can reduce noise and smooth gaps. By analyzing characteristics of capturing approximate background image with Single Gaussian Modeling, without losing the objective of reducing noise and keeping target objects complete, the threshold of segregating foreground pixels is determined by analyzing the result of subtracting background, which leads to definitive binary image of target object and background.Then the human object tracking algorithm is investigated. After the analysis of the advantage and disadvantage about Mean Shift, on the basis of detecting and segregating target objects, the paper combines Mean Shift algorithm with Kalman filter taking object moving and space color information into account and enhances the tracking performance.