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Chapter

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Title

Depth estimation based on Maximization of A posteriori Probability

Authors

[ 1 ] Katedra Telekomunikacji Multimedialnej i Mikroelektroniki, Wydział Elektroniki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Year of publication

2016

Chapter type

paper

Publication language

english

Abstract

EN This paper presents a proposal of depth estimation method which employs empirical modeling of cost function based on Maximization of A posteriori Probability (MAP) rule. The proposed method allows for unsupervised depth estimation without a need for usage of arbitrary settings or control parameters, like Smoothing Coefficient in Depth Estimation Reference Software (DERS), which was used as a reference. The attained quality of generated depth maps is comparable to a case when supervised depth estimation is used, and such parameters are manually optimized. In the case when sub-optimal settings of control parameters in supervised depth estimation with DERS is used, the proposed method provides gains of about 2.8dB measured in average PSNR quality of virtual views synthesized with the use of estimated depth maps in the tested sequence set.

Pages (from - to)

253 - 265

DOI

10.1007/978-3-319-46418-3_23

URL

https://link.springer.com/chapter/10.1007/978-3-319-46418-3_23

Book

Computer Vision and Graphics. International Conference, ICCVG 2016, Warsaw, Poland, September 19-21, 2016, Proceedings

Presented on

International Conference on Computer Vision and Graphics, ICCVG 2016, 19-21.08.2016, Warsaw, Poland

Publication indexed in

WoS (15)

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