Enhanced Depth Estimation using a Combination of Structured Light Sensing and Stereo Reconstruction

Andreas Wittmann, Anas Al-Nuaimi, Eckehard Steinbach, Georg Schroth

Abstract

We present a novel approach for depth sensing that combines structured light scanning and stereo reconstruc- tion. High-resolution disparity maps are derived in an iterative-upsampling process that jointly optimizes measurements from graph cuts based stereo reconstruction and structured light sensing using an accelerated α-expansion algorithm. Different from previously proposed fusion approaches, the disparity estimation is initialized using the low-resolution structured light prior. This results in a dense disparity map that can be computed very efficiently and which serves as an improved prior for subsequent iterations at higher resolu- tions. The advantages of the proposed fusion approach over the sole use of stereo are threefold. First, for pixels that exhibit prior knowledge from structured lighting, a reduction of the disparity search range to the uncertainty interval of the prior allows for a significant reduction of ambiguities. Second, the resulting limited search range greatly reduces the runtime of the algorithm. Third, the structured light prior enables a dynamic tuning of the smoothness constraint to allow for a better depth estimation for inclined surfaces.

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Paper Citation


in Harvard Style

Wittmann A., Al-Nuaimi A., Steinbach E. and Schroth G. (2016). Enhanced Depth Estimation using a Combination of Structured Light Sensing and Stereo Reconstruction . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 510-521. DOI: 10.5220/0005724605100521


in Bibtex Style

@conference{visapp16,
author={Andreas Wittmann and Anas Al-Nuaimi and Eckehard Steinbach and Georg Schroth},
title={Enhanced Depth Estimation using a Combination of Structured Light Sensing and Stereo Reconstruction},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={510-521},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005724605100521},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Enhanced Depth Estimation using a Combination of Structured Light Sensing and Stereo Reconstruction
SN - 978-989-758-175-5
AU - Wittmann A.
AU - Al-Nuaimi A.
AU - Steinbach E.
AU - Schroth G.
PY - 2016
SP - 510
EP - 521
DO - 10.5220/0005724605100521