Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2005
Abstract
In this paper, we present a novel segmentation-insensitive approach for mining common patterns from 2 images. We develop an algorithm using the earth movers distance (EMD) framework, unary and adaptive neighborhood color similarity. We then propose a novel local flow maximization approach to provide the best estimation of location and scale of the common pattern. This is achieved by performing an iterative optimization in search of the most stable flows' centroid. Common pattern discovery is difficult owing to the huge search space and problem domain. We intend to solve this problem by reducing the search space through identifying the location and a reduced spatial space for common pattern discovery. Experimental results justify the effectiveness and the potential of the approach.
Discipline
Computer Sciences | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the10th IEEE International Conference on Computer Vision, ICCV 2005, Beijing, China, October 17-21
First Page
1222
Last Page
1229
ISBN
9780769523347
Identifier
10.1109/ICCV.2005.58
Publisher
IEEE
City or Country
Beijing, China
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.