The corner matching based on improved singular value decomposition for motion detection

This paper proposes a moving object detection algorithm using corner point matching based on singular value decomposition to deal with the problem of the effect because of the changes of light and background. Firstly, the Kalman filtering is used to predict the target center and area; Secondly, corner points are detected in the target area by Harris corner detector; finally, corner matching between the corners of current frame and the corners of target template is based on the improved singular value decomposition algorithm. In this paper, a random sample consistency (RANSAC) algorithm is applied to remove mismatch corner point. And then the moving object is got. At last, experimental results show that the algorithm can more accurately detect moving targets, overcome the effect of the changes of light and background, and have good real-time and robustness.