University of Oulu

J. Mustaniemi, J. Kannala, S. Särkkä, J. Matas and J. Heikkila, "Gyroscope-Aided Motion Deblurring with Deep Networks," 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Village, HI, USA, 2019, pp. 1914-1922. doi: 10.1109/WACV.2019.00208

Gyroscope-aided motion deblurring with deep networks

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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
3Center for Machine Perception, Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 6.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019060618814
Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2019-06-06
Description:

Abstract

We propose a deblurring method that incorporates gyroscope measurements into a convolutional neural network (CNN). With the help of such measurements, it can handle extremely strong and spatially-variant motion blur. At the same time, the image data is used to overcome the limitations of gyro-based blur estimation. To train our network, we also introduce a novel way of generating realistic training data using the gyroscope. The evaluation shows a clear improvement in visual quality over the state-of-the-art while achieving real-time performance. Furthermore, the method is shown to improve the performance of existing feature detectors and descriptors against the motion blur.

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Series: IEEE Winter Conference on Applications of Computer Vision
ISSN: 1550-5790
ISSN-E: 2472-6737
ISSN-L: 1550-5790
ISBN: 978-1-7281-1976-2
ISBN Print: 978-1-72811-975-5
Pages: 1914 - 1922
Article number: 8658406
DOI: 10.1109/WACV.2019.00208
OADOI: https://oadoi.org/10.1109/WACV.2019.00208
Host publication: 19th IEEE Winter Conference on Applications of Computer Vision, WACV 2019
Conference: IEEE Winter Conference on Applications of Computer Vision
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 OP VVV MEYS project CZ.02.1.01/0.0/0.0/16_019/0000765 ”Research Center for Informatics”.
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