Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12911
Title: A unified shot boundary detection method based on linear prediction with Bayesian cost functions
Authors: Cai, C
Lam, KM 
Tan , Z
Keywords: Bayes methods
Image segmentation
Video signal processing
Issue Date: 2005
Publisher: IEEE
Source: Proceedings of 2005 IEEE International Workshop on VLSI Design and Video Technology, 2005, 28-30 May 2005, p. 101-104 How to cite?
Abstract: The detection of edits in a video sequence is the first step for video analysis, which segments a video into its basic components. In this paper, we propose a novel and efficient approach for shot boundary detection, which can detect cuts and dissolves reliably using a uniform framework. Our approach is based on the temporal linear prediction of the frames. With frames in a video shot, a frame can be predicted from its previous frames. If the prediction error is high, a cut should happen. For dissolves, the gradual transitions can be modeled by temporal linear prediction with constant prediction coefficients. Experimental results show that our algorithm can achieve high precision even if a video contains object motion and camera motion, and is able to detect and classify cuts and dissolves in real time.
URI: http://hdl.handle.net/10397/12911
ISBN: 0-7803-9005-9
DOI: 10.1109/IWVDVT.2005.1504561
Appears in Collections:Conference Paper

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