A Study on Moving Object Tracking Algorithm Using SURF Algorithm and Depth Information

摘要

This paper is a study on real-time object tracking algorithm using depth information of the Kinect and fast speeded up robust feature(SURF) algorithm. Depth information of the Kinect is used to overcome the disadvantage which continuously adaptive meanshift(Camshift) and Meanshift have of illumination and noise. Because processing time of SURF algorithm is faster than that of scale invariant feature transform(SIFT), Interest point detection of SURF algorithm is used for real-time processing. In this paper, depth information using background modeling and SURF algorithm generates interest point detection, interest point detection can create search window and we present object tracking method using Camshift and interest point detection.The experimental results show that the proposed method using depth information and SURF algorithm is more effective than conventional methods at processing time and accuracy.