Abstract
AbstractThis paper introduces a new approach for gait-based gender classification in which some key biomechanical poses of a gait pattern are represented by partial Gait Energy Images (GEIs). These pose-based GEIs can more accurately represent the shape of the body parts and some dynamic features with respect to the usually blurred depiction provided by a general GEI comprising all poses. Gait-based gender classification is based on the weighted decision fusion of the pose-based GEIs. Results of experiments on two large gait databases prove that this method performs significantly better than clasiffiers based on the original GEI.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.