The research of video tracking based on improved SIFT algorithm

In order to effectively solve the problem on the moving object tracking in the complex environment, a method that adopts the Scale Invariant Feature Transform (SIFT) is presented in this paper. Firstly, a searching window of narrow size is set. Secondly, extreme points are detected in scale space and the main direction of the feature points is calculated. Thirdly, in order to find the matched keypoint descriptors, we set a threshold, if the ratios of the nearest distance to the second nearest distance in current frame are below the threshold, the keypoints will be kept. It is a better solution to the shortcoming of rather time-consuming for traditional SIFT algorithm in determining descriptions of the large number of keypoints. The experimental results verified the SIFT superiority properties of the scale-invariant, rotation-invariant and other image transformations, and the good tracking results are demonstrated for the moving car in spite of the background is changing as well.