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Motion Priors Estimation for Robust Matching Initialization in Automotive Applications
Goethe University of Frankfurt, Germany.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Goethe University of Frankfurt, Germany.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Goethe University of Frankfurt, Germany.
2015 (English)In: Advances in Visual Computing: 11th International Symposium, ISVC 2015, Las Vegas, NV, USA, December 14-16, 2015, Proceedings, Part I, SPRINGER INT PUBLISHING AG , 2015, Vol. 9474, 115-126 p.Conference paper (Refereed)Text
Abstract [en]

Tracking keypoints through a video sequence is a crucial first step in the processing chain of many visual SLAM approaches. This paper presents a robust initialization method to provide the initial match for a keypoint tracker, from the 1st frame where a keypoint is detected to the 2nd frame, that is: when no depth information is available. We deal explicitly with the case of long displacements. The starting position is obtained through an optimization that employs a distribution of motion priors based on pyramidal phase correlation, and epipolar geometry constraints. Experiments on the KITTI dataset demonstrate the significant impact of applying a motion prior to the matching. We provide detailed comparisons to the state-of-the-art methods.

Place, publisher, year, edition, pages
SPRINGER INT PUBLISHING AG , 2015. Vol. 9474, 115-126 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9474
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-129182DOI: 10.1007/978-3-319-27857-5_11ISI: 000376400300011ISBN: 9783319278575ISBN: 9783319278568OAI: oai:DiVA.org:liu-129182DiVA: diva2:935987
Conference
11th International Symposium, ISVC 2015, Las Vegas, NV, USA, December 14-16, 2015
Available from: 2016-06-13 Created: 2016-06-13 Last updated: 2016-06-17Bibliographically approved

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Barnada, MarcMester, Rudolf
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Computer VisionFaculty of Science & Engineering
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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