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AI Based Automatic Robbery/Theft Detection using Smart Surveillance in Banks

机译:银行中使用智能监控的基于AI的自动抢劫/盗窃检测

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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.
机译:深度学习是人工智能的一部分,涉及模仿人类用来获取一些不同类型知识的学习方法。分析视频是深度学习的一部分,是至少20年来计算机视觉和多媒体内容分析的最基本问题之一。视频中包含许多差异很大且困难重重的信息,因此这项工作非常具有挑战性。在所有监视系统中仍然需要人工监督。计算机视觉的新进展被视为视频监控的重要趋势,可显着提高效率。我们建议基于CCTV的盗窃检测以及盗贼跟踪。我们使用图像处理来检测CCTV录像中盗贼的盗窃和盗窃行为,而无需使用传感器。该系统专注于物体检测。可以使用CCTV录像中任何人的活动的实时分析,向安全人员通知可疑个人入室盗窃,因此可以避免这种情况发生。

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