Finding Spatial Associations in Images
In this paper, our focus in data mining is concerned with the discovery of spatial associations within images. Our work concentrates on the problem of fi nding associations between visual content in large image databases. Discovering association rules has been the focus of many studies in the last few years. However, for multimedia data such as images or video frames, the algorithms proposed in the literature are not sufficient since they miss relevant frequent item-sets due to the peculiarity of visual data, like repetition of features, resolution levels, etc. We present in this paper an approach for mining spatial relationships from large visual data repositories. The approach proceeds in three steps: feature localization, spatial relationship abstraction, and spatial association discovery. The mining process considers the issue of scalability and contemplates various feature localization abstactions at different resolution levels.
Citation
O. Zaiane,
J. Han.
"Finding Spatial Associations in Images". Data Mining and Knowledge Discovery: Theory, Tools, and Technology II, pp 138-147, April 2000.
| Keywords: |
Multimedia Mining, Association Rules, Resolution Refi nement, Spatial Relationships |
| Category: |
In Workshop |
BibTeX
@misc{Zaiane+Han:00,
author = {Osmar R. Zaiane and Jiawei Han},
title = {Finding Spatial Associations in Images},
Pages = {138-147},
booktitle = {Data Mining and Knowledge Discovery: Theory, Tools, and
Technology II},
year = 2000,
}Last Updated: February 05, 2020
Submitted by Sabina P 
