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Proceedings Paper

Comparative analysis of local binocular and trinocular depth estimation approaches
Author(s): Sergey Smirnov; Atanas P. Gotchev; Miska Hannuksela
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Paper Abstract

In this paper, we present a comparative analysis of local trinocular and binocular depth estimation techniques. Local techniques are chosen because of their higher computational efficiency compared to global approaches. Our aim is to quantify the benefits of the third camera with respect to performance and computational burden. We have adopted the color-weighted local-window approach in stereo matching, where pixels within local spatial window around the pixel being processed are penalized by their colors in order to ensure better adaptivity to local structures. Thus, the window size becomes the main parameter which influences the quality and determines the execution time. Extensive experiments on large set of data have been carried out to test trinocular versus binocular setting in terms of quality of estimated depth and execution time. Both natural and artificial scenes have been tested. A set of quality measures has been used to support the comparisons. MPEG Depth Estimation Reference Software has been used as a reference benchmark as well. Results show that from some window size on, the trinocular setting outperforms the binocular in general: providing higher quality for less computational time. While comparisons were done for 'pure' depth estimation, we also run post-processing on depth estimates in order to analyze the potential of estimated depths to be further improved.

Paper Details

Date Published: 4 May 2010
PDF: 12 pages
Proc. SPIE 7724, Real-Time Image and Video Processing 2010, 77240H (4 May 2010); doi: 10.1117/12.854765
Show Author Affiliations
Sergey Smirnov, Tampere Univ. of Technology (Finland)
Atanas P. Gotchev, Tampere Univ. of Technology (Finland)
Miska Hannuksela, Nokia Research Ctr. (Finland)

Published in SPIE Proceedings Vol. 7724:
Real-Time Image and Video Processing 2010
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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