A GENERAL FRAMEWORK FOR VIDEO SEGMENTATION BASED ON TEMPORAL MULTI-RESOLUTION ANALYSIS

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概要

• 論文の詳細を見る

• Video segmentation is an important step in many video processing applications. By observing that the video shot boundary is a multi-(temporal)-resolution edge phenomenon in the feature space, we develop a general framework to handle all types of transitions in a consistent manner. We employ the Wavelet technique to transform the video signals into their first order derivatives in the frequency domain, and utilize this information across multiple temporal resolutions to detect, classify, and locate both the CUT and GT transitions. We test our method using the MPEG7 video data set consisting of about 13 hours of video. The results demonstrate that our framework is effective, and it possesses good noise tolerance characteristics. As part of this work, we are proposing the use of MPEG7 data set together with the ground truth data as the standard test set for video segmentation research.

• 社団法人映像情報メディア学会の論文
• 2000-01-14

著者

• CHUA Tat-Seng

  Department of Information Systems and Computer Science National University of Singapore

• Chua Tat-seng

  School Of Computing National University Of Singapore

• KANKANHALLI Mohan

  School of Computing, National University of Singapore

• LIN Yi

  School of Computing, National University of Singapore

• Lin Yi

  School Of Computing National University Of Singapore

• Kankanhalli Mohan

  School Of Computing National University Of Singapore

関連論文

• Visual Information Retrieval
• Visual Information Retrieval (〔画像電子〕学会創立25周年記念号) -- (特別寄書「私の描く画像の未来」)
• A GENERAL FRAMEWORK FOR VIDEO SEGMENTATION BASED ON TEMPORAL MULTI-RESOLUTION ANALYSIS

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