Resolution Enhancement of PMD Range Maps

Authors:
A. N. Rajagopalan;Arnav Bhavsar;Frank Wallhoff;Gerhard Rigoll
Affiliations:
Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India 600 036;Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India 600 036;Lehrstuhl für Mensch-Maschine-Kommunikation, Technische Universität München, München, Germany 80333;Lehrstuhl für Mensch-Maschine-Kommunikation, Technische Universität München, München, Germany 80333
Venue:
Proceedings of the 30th DAGM symposium on Pattern Recognition
Year:
2008

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Abstract

Photonic mixer device (PMD) range cameras are becoming popular as an alternative to algorithmic 3D reconstruction but their main drawbacks are low-resolution (LR) and noise. Recently, some interesting works have stressed on resolution enhancement of PMD range data. These works use high-resolution (HR) CCD images or stereo pairs. But such a system requires complex setup and camera calibration. In contrast, we propose a super-resolution method through induced camera motion to create a HR range image from multiple LR range images. We follow a Bayesian framework by modeling the original HR range as a Markov random field (MRF). To handle discontinuities, we propose the use of an edge-adaptive MRF prior. Since such a prior renders the energy function non-convex, we minimize it by graduated non-convexity.