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Robust Three-View T...
Robust Three-View Triangulation Done Fast
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- Hedborg, Johan (author)
- Linköpings universitet,Datorseende,Tekniska högskolan
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- Robinson, Andreas (author)
- Linköpings universitet,Datorseende,Tekniska högskolan
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- Felsberg, Michael (author)
- Linköpings universitet,Datorseende,Tekniska högskolan
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(creator_code:org_t)
- IEEE, 2014
- 2014
- English.
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In: Proceedings: 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2014. - : IEEE. - 9781479943098 ; , s. 152-157
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Abstract
Subject headings
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- Estimating the position of a 3-dimensional world point given its 2-dimensional projections in a set of images is a key component in numerous computer vision systems. There are several methods dealing with this problem, ranging from sub-optimal, linear least square triangulation in two views, to finding the world point that minimized the L2-reprojection error in three views. This leads to the statistically optimal estimate under the assumption of Gaussian noise. In this paper we present a solution to the optimal triangulation in three views. The standard approach for solving the three-view triangulation problem is to find a closed-form solution. In contrast to this, we propose a new method based on an iterative scheme. The method is rigorously tested on both synthetic and real image data with corresponding ground truth, on a midrange desktop PC and a Raspberry Pi, a low-end mobile platform. We are able to improve the precision achieved by the closed-form solvers and reach a speed-up of two orders of magnitude compared to the current state-of-the-art solver. In numbers, this amounts to around 300K triangulations per second on the PC and 30K triangulations per second on Raspberry Pi.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Keyword
- Nonlinear optimization; Structure from motion; Three-view Triangulation; Cameras; Computer vision; Conferences; Noise; Polynomials; Robustness; Three-dimensional displays
Publication and Content Type
- ref (subject category)
- kon (subject category)
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