Abstract
In this paper, a new method is proposed for human gait feature extraction from a video. The method consists of seven stages: background/foreground segmentation; noise filtration; extracting of the human silhouette; dividing the human silhouette into eight horizontal segments based on human body proportions; bounding rectangles getting; phase synchronization; features calculation; Fourier transform (optionally). A support vector machine (SVM) algorithm is used for classification. The algorithm was tested on 102 gait samples. Recognition accuracy is 89.2% – 96.5%.
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.
