Computer Science Seminar Series: Friday October 3, 2003
David Van Horn <[email protected]>
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-------- Original Message --------
Subject: Computer Science Seminar Series: Friday October 3, 2003
Date: Mon, 29 Sep 2003 11:46:45 -0400
Title: Video Association Mining for Basketball Video Database Indexing
and Management
Speaker: Xingquan Zhu
Department of Computer Science
University of Vermont
Burlington, VT
05405
xqzhu-UYko1UTVIqz2fBVCVOL8/[email protected]
Date: Friday, October 3, 2003
Time: 11:05 a.m. - 12:15 p.m.
Location: 002 Kalkin
Abstract
Advances in the media and entertainment industries, including streaming
audio and digital TV, present new challenges for managing and accessing
large audio-visual collections. Current content management systems
support retrieval using low-level features, such as motion, color, and
texture. However, low-level features often have little meaning for naive
users, who much prefer to identify content using high-level semantics or
concepts. This creates a gap between systems and their users that must
be bridged for these systems to be used effectively. In this paper, we
present a video association based solution for basketball video indexing
and management. Our approach uses video processing techniques to find
visual and audio cues (e.g. court field, camera motion activities, and
applause), introduces multilevel sequential association mining to
explore associations among the audio and visual cues, classifies the
associations by assigning each of them with a class label, and uses
their appearances in the video to construct video indices.