Human Interaction Recognition plays a key role in identification of usual and unusual human behaviors and facilitates public dealings, violence detection, robots perception, and virtual entertainments. This paper presents a novel human interaction recognition (HIR) system to recognize human interactions in continuous image sequences. The proposed technology segments full body silhouettes and identifies key body points to extract robust spatio-Temporal features having distinct characteristics for each interaction. Our descriptors focus on local descriptions, capture intensity variations, point-To-point distances and time based relations. The system is trained through artificial neural network to recognize six basic interactions taken from UT-Interaction dataset.
|Original language||English (US)|
|Title of host publication||2018 International Conference on Frontiers of Information Technology (FIT)|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Jan 18 2019|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research is supported by the Engineering and Managing information Centers, Saudi Arabia, under the “NVorio 5.5 Software program” (Access No. AFRT-2-04-827502) cooperated with the SNCIS (Saudi National Centre for Innovation Science).