AI Based Automatic Robbery/Theft Detection using Smart Surveillance in Banks
Title | AI Based Automatic Robbery/Theft Detection using Smart Surveillance in Banks |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Kakadiya, Rutvik, Lemos, Reuel, Mangalan, Sebin, Pillai, Meghna, Nikam, Sneha |
Conference Name | 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA) |
Date Published | jun |
Publisher | IEEE |
ISBN Number | 978-1-7281-0167-5 |
Keywords | artificial intelligence, artificial-intelligence, Banking, CCTV based theft detection, CCTV footage, closed circuit television, Computer vision, computer-vision, Conferences, Deep Learning, deep video, deeplearning, dramatic efficiency gains, human supervision, learning (artificial intelligence), Metrics, multimedia content analysis, neural nets, object detection, Proposals, pubcrawl, real-time analysis, Real-time Systems, resilience, Resiliency, Scalability, security, smart surveillance, surveillance, surveillance systems, theft-detection, video signal processing, video surveillance, video-analysis, Videos, Weapons |
Abstract | Deep learning is the segment of artificial intelligence which is involved with imitating the learning approach that human beings utilize to get some different types of knowledge. Analyzing videos, a part of deep learning is one of the most basic problems of computer vision and multi-media content analysis for at least 20 years. The job is very challenging as the video contains a lot of information with large differences and difficulties. Human supervision is still required in all surveillance systems. New advancement in computer vision which are observed as an important trend in video surveillance leads to dramatic efficiency gains. We propose a CCTV based theft detection along with tracking of thieves. We use image processing to detect theft and motion of thieves in CCTV footage, without the use of sensors. This system concentrates on object detection. The security personnel can be notified about the suspicious individual committing burglary using Real-time analysis of the movement of any human from CCTV footage and thus gives a chance to avert the same. |
URL | https://ieeexplore.ieee.org/document/8822186 |
DOI | 10.1109/ICECA.2019.8822186 |
Citation Key | kakadiya_ai_2019 |
- smart surveillance
- Proposals
- pubcrawl
- real-time analysis
- real-time systems
- resilience
- Resiliency
- Scalability
- security
- object detection
- surveillance
- surveillance systems
- theft-detection
- video signal processing
- video surveillance
- video-analysis
- Videos
- Weapons
- deep learning
- artificial-intelligence
- Banking
- CCTV based theft detection
- CCTV footage
- closed circuit television
- computer vision
- computer-vision
- Conferences
- Artificial Intelligence
- deep video
- deeplearning
- dramatic efficiency gains
- human supervision
- learning (artificial intelligence)
- Metrics
- multimedia content analysis
- neural nets