Authors:
Andreas Wittmann
1
;
Anas Al-Nuaimi
1
;
Eckehard Steinbach
1
and
Georg Schroth
2
Affiliations:
1
Technische Universität München, Germany
;
2
NavVis GmbH, Germany
Keyword(s):
Stereo Vision, Google Project Tango, Structured Light, 3D Scanning.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Computer Vision, Visualization and Computer Graphics
;
Early and Biologically-Inspired Vision
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Stereo Vision and Structure from Motion
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 grea
tly 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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