Paper Title
SUSPICIOUS ACTIVITY DETECTION AND ALERT SYSTEM
Article Identifiers
Authors
DINESH BABU K , NATHASHA R
Keywords
Activity detection; segmentation; alert system
Abstract
Video Surveillance plays a pivotal role in today's world. The technologies have been advanced too much when artificial intelligence, machine learning and deep learning pitched into the system. Using above combinations, different systems are in place which helps to differentiate various suspicious behaviours from the live tracking of footages. The most unpredictable one is human behaviour and it is very difficult to find whether it is suspicious or normal. Deep learning approach is used to detect suspicious or normal activity in an academic environment, and which sends an alert message to the corresponding authority, in case of predicting a suspicious activity. Monitoring is often performed through consecutive frames which are extracted from the video. The entire framework is divided into two parts. In the first part, the features are computed from video frames and in second part, based on the obtained features classifier predict the class as suspicious or normal.
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How To Cite (APA)
DINESH BABU K & NATHASHA R (May-2023). SUSPICIOUS ACTIVITY DETECTION AND ALERT SYSTEM. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), e382-e387. https://ijnrd.org/papers/IJNRD2305443.pdf
Issue
Volume 8 Issue 5, May-2023
Pages : e382-e387
Other Publication Details
Paper Reg. ID: IJNRD_195422
Published Paper Id: IJNRD2305443
Downloads: 000121988
Research Area: Engineering
Country: KANCHIPURAM, TAMILNADU, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2305443.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305443
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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