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  Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database

Köhler, R., Hirsch, M., Mohler, B., Schoelkopf, B., & Harmeling, S. (2012). Recording and Playback of Camera Shake: Benchmarking Blind Deconvolution with a Real-World Database. In A. Fitzgibbon, S. Lazebnik, P. Perona, Y. Sato, & C. Schmid (Eds.), Computer Vision - ECCV 2012 (pp. 27-40). Berlin, Germany: Springer.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-8B3F-D Version Permalink: http://hdl.handle.net/21.11116/0000-0001-8B40-A
Genre: Conference Paper

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 Creators:
Köhler, R1, Author              
Hirsch, M1, Author              
Mohler, BJ1, 2, 3, Author              
Schoelkopf, B.1, Author              
Harmeling, S1, Author              
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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Free keywords: Abt. Schölkopf
 Abstract: Motion blur due to camera shake is one of the predominant sources of degradation in handheld photography. Single image blind deconvolution (BD) or motion deblurring aims at restoring a sharp latent image from the blurred recorded picture without knowing the camera motion that took place during the exposure. BD is a long-standing problem, but has attracted much attention recently, cumulating in several algorithms able to restore photos degraded by real camera motion in high quality. In this paper, we present a benchmark dataset for motion deblurring that allows quantitative performance evaluation and comparison of recent approaches featuring non-uniform blur models. To this end, we record and analyse real camera motion, which is played back on a robot platform such that we can record a sequence of sharp images sampling the six dimensional camera motion trajectory. The goal of deblurring is to recover one of these sharp images, and our dataset contains all information to assess how closely various algorithms approximate that goal. In a comprehensive comparison, we evaluate state-of-the-art single image BD algorithms incorporating uniform and non-uniform blur models.

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Language(s):
 Dates: 2012-10
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1007/978-3-642-33786-4_3
BibTex Citekey: KohlerHMSHC2012
 Degree: -

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Title: 12th European Conference on Computer Vision (ECCV 2012)
Place of Event: Firenze, Italy
Start-/End Date: 2012-10-07 - 2012-10-13

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Title: Computer Vision - ECCV 2012
Source Genre: Proceedings
 Creator(s):
Fitzgibbon, A, Editor
Lazebnik, S, Editor
Perona, P, Editor
Sato, Y, Editor
Schmid, C, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 27 - 40 Identifier: ISBN: 978-3-642-33785-7

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Publ. Info: -
Pages: - Volume / Issue: 7578 Sequence Number: - Start / End Page: - Identifier: -