Human Pose Estimation in Videos Using K-NN and LBP
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 6
Abstract
The main aim of this paper is to estimate the pose of a human in a video. The input videos are preprocessed and converted into frames. At the recognition stage, segmentation of the scene is performed and the objects and their poses are recognized by searching the k-nearest neighbors in the database. Spatio-temporal local binary patterns are used as features. The distance of the nearest neighbors in the k-nn classifier is calculated by the Euclidean distance. During tracking process, human regions are detected in each frame by foreground detection and are used to track the person in the video.
Authors and Affiliations
Rashmi M S , Dr. M. B. Meenavathi, Dr. H. N. Suresh
Keywords
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