Issues in Mining Video Datasets
Shawn Newsam*, Jelena Tesic*, Lei Wang*, and B. S. Manjunath**
* Lawrence Livermore National Laboratory,
7000 East Avenue, Livermore, CA, USA 94551
** Dept. of Elec. and Comp. Eng.,
University of California, Santa Barbara, CA, USA 93106-9560
* Lawrence Livermore National Laboratory,
7000 East Avenue, Livermore, CA, USA 94551
** Dept. of Elec. and Comp. Eng.,
University of California, Santa Barbara, CA, USA 93106-9560
Abstract
This paper presents an overview of our recent work on managing image and video data. The first half of the paper describes a representation for the semantic spatial layout of video frames. In particular, Markov random fields are used to characterize the spatial arrangement of frame tiles that are labeled using support vector machine classifiers. The representation is shown to support similarity retrieval at the semantic level as demonstrated in a prototype video management system. The second half of the paper describes a method for efficiently computing nearest neighbor queries in high-dimensional feature spaces in a relevance feedback framework.
SPIE International Symposium On Electronic Imaging, Storage and Retrieval Methods and Applications for Multimedia, San Jose, California, Jan. 2004.
Node ID: 364 ,
DB ID: 162 ,
VRLID: 127 ,
Lab: VRL ,
Target: Proceedings
Subject: [Multimedia Database Mining] « Look up more