A Comprehensive Survey on Human Action Recognition
Mallikarjun Aralimarad1, Meena S M2, Jayashree D Mallapur3

1Mallikarjun Aralimarad, Assistant Professor of Electronics and Communication Engineering, Basaveshwara Engineering College (Autonomous), Bagalkot, Karnataka, India.
2Dr. Meena S. M., HOD and Professor School of Computer Science and Engineering, KLETECH, Hubli. India.
3Dr. Jayashree D. Mallapur, Professor Department of Electrictronics and Communication Engineering department at Basaveshwar Engineering College (Autonomous), Bagalkot. India.

Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 902-908 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3933079220/2020©BEIESP | DOI: 10.35940/ijrte.B3933.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The present The present situation is having many challenges in security and surveillance of Human Action recognition (HAR). HAR has many fields and many techniques to provide modern and technical action implementation. We have studied multiple parameters and techniques used in HAR. We have come out with a list of outcomes and drawbacks of each technique present in different researches. This paper presents the survey on the complete process of recognition of human activity and provides survey on different Motion History Imaging (MHI) methods, model based, multiview and multiple feature extraction based recognition methods. 
Keywords: Computer Vision, HAR, , Histogram of Oriented Gradients(HOG), MHI.