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A feature-based algorithm for detecting and classifying production effects
Authors:Ramin Zabih  Justin Miller  Kevin Mai
Affiliation:(1) Computer Science Department, Cornell University, Ithaca, NY 14853, USA; e-mail:rdz@cs.cornell.edu , US
Abstract:We describe a new approach to the detection and classification of production effects in video sequences. Our method can detect and classify a variety of effects, including cuts, fades, dissolves, wipes and captions, even in sequences involving significant motion. We detect the appearance of intensity edges that are distant from edges in the previous frame. A global motion computation is used to handle camera or object motion. The algorithm we propose withstands JPEG and MPEG artifacts, even at high compression rates. Experimental evidence demonstrates that our method can detect and classify production effects that are difficult to detect with previous approaches.
Keywords::Content-based indexing and retrieval –   Scene break detection
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