Differential Spatial Resection - Pose Estimation Using a Single Local Image Feature.

Köser, K. and Koch, Reinhard (2008) Differential Spatial Resection - Pose Estimation Using a Single Local Image Feature. Computer Vision - ECCV 2008, Pt IV, Proceedings, 5305 . pp. 312-325. DOI 10.1007/978-3-540-88693-8_23.

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Robust local image features have been used successfully in robot localization and camera pose estimation; region tracking using affine warps is considered state of the art also for many years. Although such correspondences provide a warp of the local image region and are quite powerful, in direct pose estimation they are so far only considered as points and therefore three of them are required to construct a camera pose. In this contribution we show how it is possible to directly compute a pose based upon one such feature, given the plane in space where it lies. This differential correspondence concept exploits the texture warp and has recently gained attention in estimation of conjugate rotations. The approach can also be considered as the limiting case of the well-known spatial resection problem when the three 3D points approach each other infinitesimally close. We show that the differential correspondence is more powerful than conic correspondences while its exploitation requires nothing more complicated than the roots of a third order polynomial. We give a detailed sensitivity analysis, a comparison against state-of-the-art pose estimators and demonstrate real-world applicability of the algorithm based on automatic region recognition.

Document Type: Article
Keywords: Point Correspondence, Epipolar Geometry, Camera Center, Feature Correspondence Omnidirectional Camera
Research affiliation: Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
Kiel University
Refereed: Yes
Open Access Journal?: No
DOI etc.: 10.1007/978-3-540-88693-8_23
Projects: Future Ocean
Date Deposited: 13 Oct 2010 09:04
Last Modified: 29 Aug 2019 08:18
URI: http://oceanrep.geomar.de/id/eprint/9065

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