Technical Program

Paper Detail

Paper:MMSA-L5.3
Session:Multimedia Coding and Segmentation
Time:Tuesday, May 25, 10:06 - 10:24
Presentation: Lecture
Topic: Multimedia Systems and Applications: Multimedia Coding and Segmentation
Title: AN AUDIO-SCENE CUT DETECTION METHOD USING FUZZY C-MEANS ALGORITHM FOR AUDIO-VISUAL INDEXING
Authors: Naoki Nitanda; Hokkaido University 
 Miki Haseyama; Hokkaido University 
 Hideo Kitajima; Hokkaido University 
Abstract: This paper proposes an accurate audio-scene cut detection method. The audio-scene denotes a segment which is constructed of semantically correlated audio-shots, where the audio-shot is a smaller segment than the audio-scene; and the boundary between two audio-scenes and that between two audio-shots are called the audio-scene cut and the audio-shot cut, respectively. Recently, high performance of the audio-scene cut detection methods is required for the audio-visual indexing; and several detection methods have been proposed. However, since most of the methods segment the audio signal in a fixed time interval before indexing, the users cannot obtain the exact time of the audio scene cuts. Therefore, we propose an accurate audio-scene cut detection method. We utilize the fuzzy c-means algorithm so that the reliability of the audio-shot cut is represented by the fuzzy number. Afterwards, the semantically correlated audio shots are merged into the same audio-scene, and thereby the audio-scene cuts are obtained.
 
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