PCA-Based Personal Favorite Scene Selection from Broadcast Soccer Video(Internationa Session 8)

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概要

• 論文の詳細を見る

• In this paper, we propose a novel method for selecting personal favorite scenes using Principle Component Analysis (PCA) based approach from broadcast soccer videos. In our method, we use physical parameters extracted from videos, such as image space frequency and time space frequency. We use these physical parameters as feature vectors, make an eigenspace of these vectors extracted from image slices of broadcasted soccer videos, and select the image slices that the distance from prior selected image slices as a personal favorite scene in the eigenspace is small. Personal favorite scenes are characterized as the feature vectors which are selected from physical parameters extracted from videos. The experimental results show the ability of our proposed method.

• 社団法人電子情報通信学会の論文
• 2007-10-18

著者

• Izumi Masao

  Graduate School Of Engineering Osaka Prefecture University

関連論文

• PCA-Based Personal Favorite Scene Selection from Broadcast Soccer Video(Internationa Session 8)

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