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Estimation of Automotive Pitch, Yaw, and Roll using Enhanced Phase Correlation on Multiple Far-field Windows
Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska fakulteten. Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
Vise andre og tillknytning
2015 (engelsk)Inngår i: 2015 IEEE Intelligent Vehicles Symposium (IV), IEEE , 2015, s. 481-486Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
IEEE , 2015. s. 481-486
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-131234DOI: 10.1109/IVS.2015.7225731ISI: 000380565800079ISBN: 978-1-4673-7266-4 (tryckt)OAI: oai:DiVA.org:liu-131234DiVA, id: diva2:971713
Konferanse
IEEE Intelligent Vehicles Symposium
Tilgjengelig fra: 2016-09-19 Laget: 2016-09-12 Sist oppdatert: 2018-01-10

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