IEEE Kansai Section第29回技術講演会

IEEE Kansai Section第29回技術講演会
The 29th IEEE Kansai Section Lecture Meeting

その第29回目として、大阪大学大学院工学研究科との共催により、アメリカテキサス大学の Prof. J .K. Aggarwalをお招きし、以下の要領で講演会を開催致します。


IEEE Kansai Section will have the 29th IEEE Kansai Section Lecture Meeting as follows. Anyone can attend it even if you are not a member.



Content-based Image Retrieval in Digital Image Databases
           using Structure, Color and Texture


Prof. J. K. Aggarwal
              Department of Electrical and Computer Engineering,
              The University of Texas at Austin
              IEEE Fellow

日時(Time & Date)

12月10日(金) 午後1時30分~午後3時00分
Friday, December 10, 2004 13:30~15:00


大阪大学大学院工学研究科通信工学専攻(吹田キャンパス) E3-112室(電気系E3棟1階)
           Osaka University Graduate School of Engineering, Suita Campus
           〒565-0871 大阪府吹田市山田丘2-1
           tel 06-6879-7746 / fax 06-6879-7684
            大阪大学大学院工学研究科通信工学専攻 E3棟 アクセスマップ




Modern data systems - in diverse areas as surveillance, medical imaging and publishing - accrue and store massive numbers of images for futureuse. The accumulated images, however significant, are of little value if they cannot be quickly retrieved. Efficient query systems are needed to quickly locate images with particular properties within large collections.
"A picture is worth a 1,000 words," says the old adage. However,retrieving images based on textual labels is time consuming and labor intensive since the images must be labeled in the first place. Content-based image retrieval systems analyze image features to identify image content. Color and texture are two of the features that have traditionally been used to approach this challenging problem.
At The University of Texas at Austin, we have found that structure, derived by perceptual grouping, is a valuable tool in our quest for more efficient content-based image retrieval. This presentation focuses on the use of structure, derived via perceptual grouping, for image classification and retrieval. Our use of structure does not require image segmentation. A hands-on comparison of results using color, texture and structure to retrieve images containing both natural and manmade objects will demonstrate that collectively structure, color and texture form an excellent feature set for image retrieval. Our system, available on the web, incorporates relevance feedback from the user to refine further the search. Future uses of our system in surveillance and video summarization will also be discussed.


Prof. J.K. Aggarwal has served on the faculty of The University of Texas at Austin College of Engineering in the Department of Electrical and Computer Engineering since 1964. He is currently one of the Cullen Professors of Electrical and Computer Engineering and the Director of the Computer and Vision Research Center. His research interests include computer vision and pattern recognition. Professor Aggarwal earned his B.Sc. from University of Bombay, India in 1957, B. Eng.; University of Liverpool, Liverpool, England, 1960; M.S., University of Illinois, Urbana, Illinois, 1961; and Ph.D., University of Illinois, Urbana, Illinois, in 1964.
A fellow of IEEE (1976) and IAPR (1998), Prof. Aggarwal received the Senior Research Award of the American Society of Engineering Education in 1992. In 1996, he received the IEEE Computer Society Technical Achievement Award for"pioneering contributions towards establishing fundamentals of structure extraction and computational motion from image sequences". He is the author or editor of 7 books and 52 book chapters, author of over 200 journal papers, as well as numerous proceeding papers and technical reports.

参加費 (Fee)

無料 Free
   Anyone can attend it even if you are not a member.

参加申込み先 (Contact for registration)

   ATR音声言語コミュニケーション研究所 柴田 葉子
   Yoko Shibata (ATR)
      Tel: (0774) 95 1347 / Fax: (0774) 95 1308
  会場準備の都合上、参加ご希望の方は、所属、お名前(ふりがな)および IEEE会員番号を上記参加申し込み先までEmail (Faxでも結構です)にて 12月7日(火)までにお知らせください。
  Please register in advance. E-mail or fax IEEE member ID, your name and affiliation by December 7 (tue).

本件連絡先 (For further information)

     IEEE Kansai Section Technical Program Committee Secretary


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