Dense disparity maps from sparse disparity measurements

Simon Hawe, Martin Kleinsteuber, Klaus Diepold

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

89 Zitate (Scopus)

Abstract

In this work we propose a method for estimating disparity maps from very few measurements. Based on the theory of Compressive Sensing, our algorithm accurately reconstructs disparity maps only using about 5% of the entire map. We propose a conjugate subgradient method for the arising optimization problem that is applicable to large scale systems and recovers the disparity map efficiently. Experiments are provided that show the effectiveness of the proposed approach and robust behavior under noisy conditions.

OriginalspracheEnglisch
Titel2011 International Conference on Computer Vision, ICCV 2011
Seiten2126-2133
Seitenumfang8
DOIs
PublikationsstatusVeröffentlicht - 2011
Veranstaltung2011 IEEE International Conference on Computer Vision, ICCV 2011 - Barcelona, Spanien
Dauer: 6 Nov. 201113 Nov. 2011

Publikationsreihe

NameProceedings of the IEEE International Conference on Computer Vision

Konferenz

Konferenz2011 IEEE International Conference on Computer Vision, ICCV 2011
Land/GebietSpanien
OrtBarcelona
Zeitraum6/11/1113/11/11

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