Abstract
Face Tracking is one of the most challenging topics in computer vision. Various face tracking methods have been proposed. However most of them have not ability to correct error and divergence in face tracking process. In this paper we propose a new method for face tracking using face detection and object tracking simultaneously to utilize their advantages at once. For minimizing error and divergence from target, we propose a feedback system based on Local Binary Pattern (LBP) and several rules to provide this opportunity that detection and tracking systems can cooperate with each other, so that ability of one system cover disability of another one. We demonstrate the performance and effectiveness of the proposed method on a number of challenging videos. These test video sequences show that proposed method is robust to pose variations, illumination changes and occlusions. Quantitatively, proposed method achieves the average root mean square error at 6.78 on the well-known Dudek video sequence. Experimental results show reliability of the proposed method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
