JH2R: Joint Homography Estimation for Highlight Removal

Sungmin Eum, Hyungtae Lee and David Doermann

Abstract

This paper addresses the problem of removing highlight regions caused by the light sources reflecting off glossy surfaces in indoor environments. We devise an efficient method to detect and remove the highlights from the target scene by jointly estimating separate homographies for the target scene and the highlights. Our method is based on the observation that when given two images captured at different viewpoints, the displacement of the target scene is different from that of the highlight regions. We show the effectiveness of our method in removing the highlight reflections by comparing it with the related state-of-the-art methods. Unlike the previous methods, our method has the ability to handle saturated and relatively large highlights which completely obscure the content underneath.

Session

Poster 1

Files

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DOI

10.5244/C.29.49
https://dx.doi.org/10.5244/C.29.49

Citation

Sungmin Eum, Hyungtae Lee and David Doermann. JH2R: Joint Homography Estimation for Highlight Removal. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 49.1-49.12. BMVA Press, September 2015.

Bibtex

@inproceedings{BMVC2015_49,
	title={JH2R: Joint Homography Estimation for Highlight Removal},
	author={Sungmin Eum and Hyungtae Lee and David Doermann},
	year={2015},
	month={September},
	pages={49.1-49.12},
	articleno={49},
	numpages={12},
	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
	publisher={BMVA Press},
	editor={Xianghua Xie, Mark W. Jones, and Gary K. L. Tam},
	doi={10.5244/C.29.49},
	isbn={1-901725-53-7},
	url={https://dx.doi.org/10.5244/C.29.49}
}