Visualized Sound Retrieval and Categorization Using a Feature-Based Image Serch Engine

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概要

• 論文の詳細を見る

• In this paper, visualized sound retrieval and categorization methods using a feature-based image search engine were evaluated aiming at efficient video scene query. Colorcoded patterns of the sound spectrogram are adopted as the visualized sound index. Sound categorization experiments were conducted using visualized sound databases including speech, bird song, musical sounds, insect chirping, and the sound-track of sports video. The results of the retrieval experiments show that the simple feature-based image search engine can be effectively used for visualized sound retrieval and categorization. The results of categorization experiments involving humans show that after brief training humans can at least do rough categorization. Thses results suggest that using visualized sound can be effective method for an efficient video scene query.

• 一般社団法人電子情報通信学会の論文
• 2000-11-25

著者

• Waki Hideyo

  The Authors Are With Tokyo Waterfront Research Center Telecommunications Advancement Organization Of

• Hiwatari Yoshitsugu

  The Authors Are With Tokyo Waterfront Research Center Telecommunications Advancement Organization Of

• FUSHIKIDA Katsunobu

  The authors are with Tokyo Waterfront Research Center, Telecommunications Advancement Organization o

• Fushikida Katsunobu

  The Authors Are With Tokyo Waterfront Research Center Telecommunications Advancement Organization Of Japan

関連論文

• Visualized Sound Retrieval and Categorization Using a Feature-Based Image Serch Engine
• A Representative-Video-Frame Selection Method for a Content-Based Video-Query-Agent System

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