University of Oulu

Ylimäki M., Kannala J., Heikkilä J. (2017) Robust and Practical Depth Map Fusion for Time-of-Flight Cameras. In: Sharma P., Bianchi F. (eds) Image Analysis. SCIA 2017. Lecture Notes in Computer Science, vol 10269. Springer, Cham.

Robust and practical depth map fusion for time-of-flight cameras

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Author: Ylimäki, Markus1; Kannala, Juho2; Heikkilä, Janne1
Organizations: 1Center for Machine Vision Research, University of Oulu, Finland
2Department of Computer Science, Aalto University, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 10.1 MB)
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Language: English
Published: Springer Nature, 2017
Publish Date: 2019-09-06


Fusion of overlapping depth maps is an important part in many 3D reconstruction pipelines. Ideally fusion produces an accurate and nonredundant point cloud robustly even from noisy and partially poorly registered depth maps. In this paper, we improve an existing fusion algorithm towards a more ideal solution. Our method builds a nonredundant point cloud from a sequence of depth maps so that the new measurements are either added to the existing point cloud if they are in an area which is not yet covered or used to refine the existing points. The method is robust to outliers and erroneous depth measurements as well as small depth map registration errors due to inaccurate camera poses. The results show that the method overcomes its predecessor both in accuracy and robustness.

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Series: Lecture notes in computer science
ISSN: 0302-9743
ISSN-E: 1611-3349
ISSN-L: 0302-9743
ISBN Print: 9783319591254
Pages: 122 - 134
DOI: 10.1007/978-3-319-59126-1_11
Host publication: Proceedings of the 20th Scandinavian Conference on Image Analysis, SCIA 2017; Tromso; Norway; 12 -14 June 2017
Conference: Scandinavian Conference on Image Analysis
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Copyright information: © Springer International Publishing AG 2017.