Abstract
The approach taken in this paper is based on a pattern recognition method that has been successfully applied to face recognition. The method extracts maximal commonality from pairs of patterns to determine their similarity. The measure of commonality is derived from the size of a maximal clique that is matched in both patterns. The cliques consist of nodes that correspond to pixels in both images that possess similar intensity gradient directions and also bear similar angular relationships with all other nodes in the clique. The shift corresponding to matching pixels in the stereo image pair determines the relative distances of objects from the camera. The algorithm does not make use of any other feature measurements and therefore is not dependent on their presence. In addition no prior training is necessary to initialize parameters.
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.
