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Feature-Based Algorithms for Detecting and Classifying Scene Breaks

Author
Zabih, Ramin; Miller, Justin; Mai, Kevin
Abstract
We describe a new approach to the detection and classification of scene breaks
in video sequences. Our method can detect and classify a variety of scene
breaks, including cuts, fades, dissolves and wipes, 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 algorithms we
propose withstand compression artifacts such as those introduced by JPEG and
MPEG, even at very high compression rates. Experimental evidence demonstrates
that our method can detect and classify scene breaks that are difficult to
detect with previous approaches. An initial implementation runs at
approximately 2 frames per second on a Sun workstation.
Date Issued
1995-07Publisher
Cornell University
Subject
computer science; technical report
Previously Published As
http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR95-1530
Type
technical report