<title>Temporal multiresolution analysis for video segmentation</title>
Author(s) -
Yi Lin,
Mohan Kankanhalli,
TatSeng Chua
Publication year - 1999
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.373582
Subject(s) - artificial intelligence , computer science , computer vision , segmentation , histogram , feature (linguistics) , pattern recognition (psychology) , image segmentation , video denoising , wavelet , video tracking , video processing , multiview video coding , image (mathematics) , philosophy , linguistics
Video segmentation is an important step in many of the video applications. We observe that the video shot boundary is a multi-resolution edge phenomenon in the feature space. Based on this observation, we have developed a novel temporal multi-resolution analysis (TMRA) based algorithm using Canny wavelets to perform temporal video segmentation. Information across multiple resolution is used to help detect as well as locate abrupt and gradual transitions. We present the theoretical basis of the algorithm followed by the implementation as well as the result. In this paper the TMRA technique has been implemented using color histogram in the raw domain and DCT coefficients in the compressed video streams as the feature space. Experimental result shows that this method can detect as well as characterize both the abrupt and gradual shot boundaries. The technique also shows good noise tolerance characteristics.
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