Disparity Estimation for Fisheye Images with an Application to Intermediate View Synthesis

Eichenseer A, Bätz M, Kaup A (2017)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2017

Conference Proceedings Title: IEEE International Workshop on Multimedia Signal Processing (MMSP)

Event location: London-Luton, UK GB

ISBN: 978-1-5090-3649-3

DOI: 10.1109/MMSP.2017.8122251

Abstract

To obtain depth information from a stereo camera setup, a common way is to conduct disparity estimation between the two views; the disparity map thus generated may then also be used to synthesize arbitrary intermediate views. A straightforward approach to disparity estimation is block matching, which performs well with perspective data. When dealing with non-perspective imagery such as obtained from ultra wide-angle fisheye cameras, however, block matching meets its limits. In this paper, an adapted disparity estimation approach for fisheye images is introduced. The proposed method exploits knowledge about the fisheye projection function to transform the fisheye coordinate grid to a corresponding perspective mesh. Offsets between views can thus be determined more accurately, resulting in more reliable disparity maps. By re-projecting the perspective mesh to the fisheye domain, the original fisheye field of view is retained. The benefit of the proposed method is demonstrated in the context of intermediate view synthesis, for which both objectively evaluated as well as visually convincing results are provided.

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How to cite

APA:

Eichenseer, A., Bätz, M., & Kaup, A. (2017). Disparity Estimation for Fisheye Images with an Application to Intermediate View Synthesis. In IEEE International Workshop on Multimedia Signal Processing (MMSP). London-Luton, UK, GB.

MLA:

Eichenseer, Andrea, Michel Bätz, and André Kaup. "Disparity Estimation for Fisheye Images with an Application to Intermediate View Synthesis." Proceedings of the IEEE International Workshop on Multimedia Signal Processing (MMSP), London-Luton, UK 2017.

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