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Authors: Kazuki Matsumoto ; Francois de Sorbier and Hideo Saito

Affiliation: Keio University, Japan

ISBN: 978-989-758-077-2

Keyword(s): Depth map, ToF depth sensor, GPU, Plane Fitting, Upsampling, denoising.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Health Engineering and Technology Applications ; Image-Based Modeling ; Pattern Recognition ; Shape Representation ; Signal Processing ; Software Engineering

Abstract: Recent advances of ToF depth sensor devices enables us to easily retrieve scene depth data with high frame rates. However, the resolution of the depth map captured from these devices is much lower than that of color images and the depth data suffers from the optical noise effects. In this paper, we propose an efficient algorithm that upsamples depth map captured by ToF depth cameras and reduces noise. The upsampling is carried out by applying plane based interpolation to the groups of points similar to planar structures and depth variance based joint bilateral upsampling to curved or bumpy surface points. For dividing the depth map into piecewise planar areas, we apply superpixel segmentation and graph component labeling. In order to distinguish planar areas and curved areas, we evaluate the reliability of detected plane structures. Compared with other state-of-the- art algorithms, our method is observed to produce an upsampled depth map that is smoothed and closer to the ground truth depth map both visually and numerically. Since the algorithm is parallelizable, it can work in real-time by utilizing highly parallel processing capabilities of modern commodity GPUs. (More)

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Paper citation in several formats:
Matsumoto, K.; de Sorbier, F. and Saito, H. (2015). Plane Fitting and Depth Variance Based Upsampling for Noisy Depth Map from 3D-ToF Cameras in Real-time.In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-758-077-2, pages 150-157. DOI: 10.5220/0005184801500157

@conference{icpram15,
author={Kazuki Matsumoto. and Francois de Sorbier. and Hideo Saito.},
title={Plane Fitting and Depth Variance Based Upsampling for Noisy Depth Map from 3D-ToF Cameras in Real-time},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2015},
pages={150-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005184801500157},
isbn={978-989-758-077-2},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - Plane Fitting and Depth Variance Based Upsampling for Noisy Depth Map from 3D-ToF Cameras in Real-time
SN - 978-989-758-077-2
AU - Matsumoto, K.
AU - de Sorbier, F.
AU - Saito, H.
PY - 2015
SP - 150
EP - 157
DO - 10.5220/0005184801500157

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