Data-driven Visual Similarity for Cross-domain Image Matching (original) (raw)
http://graphics.cs.cmu.edu/projects/crossDomainMatching/
Presented at SIGGRAPH Asia, 2011
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A data-driven technique to find visual similarity which does not depend on any particular image domain or feature representation. Visit the webpage to see some cool results and applications.
Abstract
The goal of this work is to find visually similar images even if they appear quite different at the raw pixel level. This task is particularly important for matching images across visual domains, such as photos taken over different seasons or lighting conditions, paintings, hand-drawn sketches, etc. We propose a surprisingly simple method that estimates the relative importance of different features in a query image based on the notion of "data-driven uniqueness". We employ standard tools from discriminative object detection in a novel way, yielding a generic approach that does not depend on a particular image representation or a specific visual domain. Our approach shows good performance on a number of difficult cross-domain visual tasks e.g., matching paintings or sketches to real photographs. The method also allows us to demonstrate novel applications such as Internet re-photography, and painting2gps.
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Related Papers
Ensemble of Exemplar-SVMs for Object Detection and Beyond, Tomasz Malisiewicz, Abhinav Gupta, Alexei A. Efros, in International Conference on Computer Vision (ICCV), 2011
Exemplar-SVMs for Visual Object Detection, Label Transfer and Image Retrieval, Tomasz Malisiewicz, Abhinav Shrivastava, Alexei A. Efros, Invited Applications Paper in International Conference on Machine Learning (ICML), 2012 (PDF)
Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships, Tomasz Malisiewicz, Alexei A. Efros, In NIPS, December 2009
BibTeX
@article{shrivastava-sa11, author = {Shrivastava, Abhinav and Malisiewicz, Tomasz and Gupta, Abhinav and Efros, Alexei A.}, title = {Data-driven Visual Similarity for Cross-domain Image Matching}, journal = {ACM Transaction of Graphics (TOG) (Proceedings of ACM SIGGRAPH ASIA)}, year = {2011}, volume = {30}, number = {6}, }
Funding
This research is supported by:
- ONR Grant N000141010766
- MSR-CMU Center for Computational Thinking
Comments, questions to Abhinav Shrivastava