| Summary: | 碩士 === 中央警察大學 === 刑事警察研究所 === 103 === Closed-Circuit Television (CCTV) surveillance systems play an important role in crime scene investigation. Investigators use recorded video data to find suspects and information to solve crime cases. However, there are usually a lot of unwanted or tedious frames (e.g., background without interested objects) in surveillance videos. It is an exhausting and time-consuming work for investigators to search entire videos for interested information. The most difficult problem of using surveillance videos is how to find useful and meaningful frames from them. In this thesis, we provide a method of utilizing motion vectors to classify video frames based upon moving information (such as orientation). By the proposed method, investigators can reduce the time
of searching objects from surveillance videos, and focus on frames with
moving objects.
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