Point Feature-based Target Tracking Algorithm And Its Application In Robot Navigation

Object recognition and tracking is an important research sub-field in computer vision, which has attracted great concerns of researchers. In robotics, the visial tracking of robotics has found extensive applications in national defense, industry monitoring, digital medical service, and many other areas. First, the state-of-the-art of the recognition and tracking related technology is discussed, the several popular approaches of tracking are introduced in detail. Then attention is focused on the study of the object tracking algorithm based on point feature. Based on analyzing the feature extraction operators, the SIFT (Scale Invariant Feature Transform) feature point operator is discussed emphatically and used to object tracking. This paper proposes a kind of unifies SIFT and KLT (Kanade-Lucas-Tomasi) object tracking algorithm. Based on OpenCV, DirectShow and the VC++6.0 software development platform, the software of object tracking is developed.In addition, SIFT and KLT (Kanade-Lucas-Tomasi) object tracking algorithm was used for mobile robot. In context of the mobile robot, the problem of single-target tracking is solved by two kinds of control strategies. In the foundation of single-target tracking, the object navigation problem is studied, and the proposed algorithm is used in the robot navigation system.The experimental result indicated that the algorithm proposed in this paper, to be used in the object tracking, has quite superior in the accuracy and real-time, the single-target real-time tracking and the object navigation of autonomous mobile robot are realized well through this algorithm. The tracking algorithm proposed in this paper has good usability, it will have good value to mobile robot vision technology, especially the related navigation system design.