NDLI: Scene detection in Hollywood movies and TV shows

Content Provider	IEEE Xplore Digital Library
Author	Rasheed, Z. Shah, M.
Copyright Year	2003
Description	Author affiliation: Sch. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA (Rasheed, Z.; Shah, M.)
Abstract	A scene can be defined as one of the subdivisions of a play in which the setting is fixed, or when it presents continuous action in one place. We propose a novel two-pass algorithm for scene boundary detection, which utilizes the motion content, shot length and color properties of shots as the features. In our approach, shots are first clustered by computing Backward Shot Coherence (BSC) - a shot color similarity measure that detects Potential Scene Boundaries (PSBs) in the videos. In the second pass we compute Scene Dynamics (SD), a function of shot length and the motion content in the potential scenes. In this pass, a scene merging criteria has been developed to remove weak PSBs in order to reduce over segmentation. We also propose a method to describe the content of each scene by selecting one representative image. The segmentation of video data into number of scenes facilitates an improved browsing of videos in electronic form, such as video on demand, digital libraries, Internet. The proposed algorithm has been tested on a variety of videos that include five Hollywood movies, one sitcom, and one interview program and promising results have been obtained.
Sponsorship	IEEE Comput. Soc Tech. Committee on Pattern Anal. & Machine Intelligence (TCPAMI)
File Size	543021
File Format	PDF
ISBN	0769519008
ISSN	10636919
DOI	10.1109/CVPR.2003.1211489
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-06-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Layout Motion pictures TV Gunshot detection systems Image segmentation Clustering algorithms Motion detection Merging Video on demand Software libraries
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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