liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Estimation of Automotive Pitch, Yaw, and Roll using Enhanced Phase Correlation on Multiple Far-field Windows
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
Show others and affiliations
2015 (English)In: 2015 IEEE Intelligent Vehicles Symposium (IV), IEEE , 2015, 481-486 p.Conference paper (Refereed)
Abstract [en]

The online-estimation of yaw, pitch, and roll of a moving vehicle is an important ingredient for systems which estimate egomotion, and 3D structure of the environment in a moving vehicle from video information. We present an approach to estimate these angular changes from monocular visual data, based on the fact that the motion of far distant points is not dependent on translation, but only on the current rotation of the camera. The presented approach does not require features (corners, edges,...) to be extracted. It allows to estimate in parallel also the illumination changes from frame to frame, and thus allows to largely stabilize the estimation of image correspondences and motion vectors, which are most often central entities needed for computating scene structure, distances, etc. The method is significantly less complex and much faster than a full egomotion computation from features, such as PTAM [6], but it can be used for providing motion priors and reduce search spaces for more complex methods which perform a complete analysis of egomotion and dynamic 3D structure of the scene in which a vehicle moves.

Place, publisher, year, edition, pages
IEEE , 2015. 481-486 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-131234DOI: 10.1109/IVS.2015.7225731ISI: 000380565800079ISBN: 978-1-4673-7266-4OAI: oai:DiVA.org:liu-131234DiVA: diva2:971713
Conference
IEEE Intelligent Vehicles Symposium
Available from: 2016-09-19 Created: 2016-09-12 Last updated: 2016-09-19

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Barnada, MarcMester, Rudolf
By organisation
Computer VisionFaculty of Science & Engineering
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 18 hits
ReferencesLink to record
Permanent link

Direct link