Human Irregularity Detection Based on Posture and Behavioral Analysis (original) (raw)

2021 Innovations in Power and Advanced Computing Technologies (i-PACT), 2021

Abstract

Surveillance or monitoring is always a major concern and challenge for security endpoints and nowadays with advancement of AI technology, the security surveillance can be achieved. Monitoring is the starting process of any security challenges. Public places like Restaurants and certain more viable places like banks, market, ATMs are in need of such system. However, constant manual monitoring using security cameras may miss abnormal cues. This paper illustrates the semi-automize system that is used for security monitoring. It processes various classes and CNN techniques that are used for implementation of Human Irregular Activity Detection Based on Posture and Behavioral Analysis (HIADPBA). The proposed methodology overcomes the uncertainty of the problems during the detection of activity. The knowledge base of this system contains real time data in conjunction with real life security. Surveillance data thereby increase the efficiency and accuracy of the detection of abnormal behavior.

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