View-invariant action recognition

• URL: http://arxiv.org/abs/2009.00638v1
• Date: Tue, 1 Sep 2020 18:08:46 GMT
• Title: View-invariant action recognition
• Authors: Yogesh S Rawat, Shruti Vyas
• Abstract summary: The varying pattern of a lot-temporal appearance generated by human action is key for identifying action performed. The research in view-invariant action recognition addresses this problem on recognizing human actions from unseen viewpoints.
• Score: 3.553493344868414
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Human action recognition is an important problem in computer vision. It has a wide range of applications in surveillance, human-computer interaction, augmented reality, video indexing, and retrieval. The varying pattern of spatio-temporal appearance generated by human action is key for identifying the performed action. We have seen a lot of research exploring this dynamics of spatio-temporal appearance for learning a visual representation of human actions. However, most of the research in action recognition is focused on some common viewpoints, and these approaches do not perform well when there is a change in viewpoint. Human actions are performed in a 3-dimensional environment and are projected to a 2-dimensional space when captured as a video from a given viewpoint. Therefore, an action will have a different spatio-temporal appearance from different viewpoints. The research in view-invariant action recognition addresses this problem and focuses on recognizing human actions from unseen viewpoints.

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