University of Oulu

J. Mustaniemi, J. Kannala, S. Särkkä, J. Matas and J. Heikkilä, "Fast Motion Deblurring for Feature Detection and Matching Using Inertial Measurements," 2018 24th International Conference on Pattern Recognition (ICPR), Beijing, 2018, pp. 3068-3073. doi: 10.1109/ICPR.2018.8546041

Fast motion deblurring for feature detection and matching using inertial measurements

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Author: Mustaniemi, Janne1; Kannala, Juho2; Särkkä, Simo2;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Finland
2Aalto University, Finland
3Centre for Machine Perception Department of Cybernetics, Czech Technical University, Prague, Czech Republic
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019061019654
Language: English
Published: IEEE Computer Society, 2018
Publish Date: 2019-06-10
Description:

Abstract

Many computer vision and image processing applications rely on local features. It is well-known that motion blur decreases the performance of traditional feature detectors and descriptors. We propose an inertial-based deblurring method for improving the robustness of existing feature detectors and descriptors against the motion blur. Unlike most deblurring algorithms, the method can handle spatially-variant blur and rolling shutter distortion. Furthermore, it is capable of running in real-time contrary to state-of-the-art algorithms. The limitations of inertial-based blur estimation are taken into account by validating the blur estimates using image data. The evaluation shows that when the method is used with traditional feature detector and descriptor, it increases the number of detected keypoints, provides higher repeatability and improves the localization accuracy. We also demonstrate that such features will lead to more accurate and complete reconstructions when used in the application of 3D visual reconstruction.

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Series: International Conference on Pattern Recognition
ISSN: 1051-4651
ISSN-L: 1051-4651
ISBN: 978-1-5386-3788-3
ISBN Print: 978-1-5386-3789-0
Pages: 3068 - 3073
DOI: 10.1109/ICPR.2018.8546041
OADOI: https://oadoi.org/10.1109/ICPR.2018.8546041
Host publication: 2018 24th International Conference on Pattern Recognition (ICPR)
Conference: International Conference on Pattern Recognition
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: The work has been financially supported by the FiDiPro programme of Business Finland and J. Matas was supported by Czech Science Foundation Project GACR P103/12/G084.
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