Abstract
In this paper we present an algorithm which recovers the rigid transformation that describes the displacement of a binocular stereo rig in a scene, and uses
this to include a third image to perform dense trinocular stereo matching and reduce some of the ambiguities inherent to binocular stereo. The core idea of the proposed algorithm is the assumption that the binocular baseline is projected to the third view, and thus can be used to constrain the transformation estimation of the stereo rig. Our approach shows improved performance over binocular stereo, and the accuracy of the recovered motion allows to compute optical ow from a
single disparity map. These claims are validated with the KITTI 2012 data set.
this to include a third image to perform dense trinocular stereo matching and reduce some of the ambiguities inherent to binocular stereo. The core idea of the proposed algorithm is the assumption that the binocular baseline is projected to the third view, and thus can be used to constrain the transformation estimation of the stereo rig. Our approach shows improved performance over binocular stereo, and the accuracy of the recovered motion allows to compute optical ow from a
single disparity map. These claims are validated with the KITTI 2012 data set.
Original language | English |
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Title of host publication | 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 17-20 |
Number of pages | 4 |
ISBN (Electronic) | 978-4-9011-2216-0 |
DOIs | |
Publication status | Published - 20 Jul 2017 |
Event | 2017 Fifteenth IAPR International Conference on Machine Vision Applications - Nagoya, Japan Duration: 8 May 2017 → 12 May 2017 http://www.mva-org.jp/mva2017/ |
Conference
Conference | 2017 Fifteenth IAPR International Conference on Machine Vision Applications |
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Abbreviated title | IAPR MVA 2017 |
Country/Territory | Japan |
City | Nagoya |
Period | 8/05/17 → 12/05/17 |
Internet address |