Abstract #301457

This is the preliminary program for the 2003 Joint Statistical Meetings in San Francisco, California. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 2-5, 2003); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2003 Program page
JSM 2003 Abstract #301457
Activity Number: 3
Type: Invited
Date/Time: Sunday, August 3, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract - #301457
Title: Multimedia Mining
Author(s): Jelena Tesic*+ and Bangalore S. Manjunath
Companies: University of California, Santa Barbara and University of California
Address: PO Box 13745, Santa Barbara, CA, 93106-9560,
Keywords: image mining ; large datasets ; thesaurus ; video mining ; scientific mining ; texture features
Abstract:

Supporting efficient access and analysis of huge amount of media data anticipated from scientific experiments is beyond the realm of current technologies. The size of these datasets makes manual analysis challenging. We explore the problem in the context of mining video data with little or no domain knowledge. Also, we extensively investigate the homogeneous texture use to annotate and classify aerial images. The spatial arrangement of these classes can be summarized by spatial data structures, such as Spatial Event Cubes (SEC). These summaries support the mining of spatial associations to help establish connections between the strustructure of the video frames and semantic events. SECs also support the extension of the Association Rule approach to multimedia databases to identify frequently ococcurring item sets. a multi-terabyte collection of aerial videos of Amazonia. The combination of presented tools enables object detection by facilitating data analysis to discover information that is not perceived by human inspection, as well as data mining and efficient searches in databases for relevant phenomena.

  • The address information is for the authors that have a + after their name.
  • Authors who are presenting talks have a * after their name.

Back to the full JSM 2003 program

JSM 2003 For information, contact meetings@amstat.org or phone (703) 684-1221. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2003