Abstract
Conventional surveillance systems for preventing accidents and incidents do not identify 95% thereof after 22 min when one person monitors a plurality of closed circuit televisions (CCTV). To address this issue, while computer-based intelligent video surveillance systems have been studied to notify users of abnormal situations when they happen, it is not commonly used in real environment because of weakness of personal information leaks and high power consumption. To address this issue, intelligent video surveillance systems based on small devices have been studied. This paper suggests implement an intelligent video surveillance system based on embedded modules for intruder detection based on information learning, fire detection based on color and motion information, and loitering and fall detection based on human body motion. Moreover, an algorithm and an embedded module optimization method are applied for real-time processing. The implemented algorithm showed performance of 88.51% for intruder detection, 92.63% for fire detection, 80% for loitering detection and 93.54% for fall detection. The result of comparison before and after optimization about the algorithm processing time showed 50.53% of decrease, implying potential real-time driving of the intelligent image monitoring system based on embedded modules.
Highlights
As incidents and accidents are increasing, for example, murders and domestic fires and fall accidents of elderly people happening indoors and outdoors, people are increasingly interested in their safety
With respect to 456 dongs where crimes occurred in Seoul, 113 dongs show high crime rate, and investigation shows 113 dongs have installed a smaller number of circuit televisions (CCTV)
It was shown that the algorithm for detecting abnormal situations by the intelligent video surveillance system reduced 50.53% of processing time before and after optimization
Summary
As incidents and accidents are increasing, for example, murders and domestic fires and fall accidents of elderly people happening indoors and outdoors, people are increasingly interested in their safety. A library is configured in order to use embedded modules, and conducts 5-algorithm optimization and 3-embedded module optimization to reduce processing time for the intelligent surveillance system.
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