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Edge-based Human Action Recognition for Smart Surveillance Systems

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posted on 07.02.2022, 03:40 authored by Sapdo UtomoSapdo Utomo, Yu-Chien Hsiao, Darmawan Utomo, Pao-Ann HsiungPao-Ann Hsiung
A surveillance system is an important security aid. In most criminal cases, they become crucial evidence. However, traditional surveillance systems are incapable of preventing loss or crime. Because they only record it, unless someone keeps monitoring it. The human action recognition in this paper overcomes the limitation. Wall climbing, punching, kicking, and falling down were all recognized with a good accuracy rate in the experiment. This technology is ready to support whole-size security systems. It will send messages about detected abnormal action and the location to security staff to take action before it’s too late. Furthermore, it can be implemented on an edge-based device at a low cost and does not necessitate a large amount of bandwidth.

Funding

MOST107-2221-E-194-001-MY3

MOST110-2634-F-194-006

History

Email Address of Submitting Author

sapdo.utomo@gmail.com

ORCID of Submitting Author

0000-0001-5623-2183

Submitting Author's Institution

National Chung Cheng University

Submitting Author's Country

Taiwan

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