| Summary: | 碩士 === 淡江大學 === 電機工程學系碩士班 === 101 === With the development of surveillance, digital and high resolution surveillance become more and more popular, impacting security system. It is reported that in the UK alone there are 4.2 million security cameras covering city streets. More and more digital surveillances are placed in everywhere for safety and security. Therefore digital surveillance system plays indispensable role in security today. However, the great amount of video captured form digital surveillance is difficult to manage and retrieve.
In this study, we propose an efficient video retrieval technique. With the system, the Region of Interest (ROI) could be extracted in long video effectively and user could browse it with quick and easy way. According to the characteristic of the object in foreground distribution for the real-world video sequence, this work employs Gaussian Mixture Model (GMM) is used for object detection. In order to let users, a new video synopsis search approach, low-complexity rang tree algorithm, is proposed to improve the search the objects matching the conditions effectively in this work. With the time and space redundancy-reducing technique of video synopsis, the objects searched by users could be display in very short time. Therefore wanted objects and events could be found out and displayed quickly without wasting time watching the part without ROI. For the test video sequences, it can have an accuracy rate of 95% and achieve 32 Frame Per Second (FPS) of online phase in processing speed and time complexity of searching decrease from O(N) to O(logD-1N).
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