A minimal case solution to the calibrated relative pose problem for the case of two known orientation angles

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Abstract

It this paper we present a novel minimal case solution to the calibrated relative pose problem using 3 point correspondences for the case of two known orientation angles. This case is relevant when a camera is coupled with an inertial measurement unit (IMU) and it recently gained importance with the omnipresence of Smartphones (iPhone, Nokia N900) that are equipped with accelerometers to measure the gravity normal. Similar to the 5-point (6-point), 7-point, and 8-point algorithm for computing the essential matrix in the unconstrained case, we derive a 3-point, 4-point and, 5-point algorithm for the special case of two known orientation angles. We investigate degenerate conditions and show that the new 3-point algorithm can cope with planes and even collinear points. We will show a detailed analysis and comparison on synthetic data and present results on cell phone images. As an additional application we demonstrate the algorithm on relative pose estimation for a micro aerial vehicle's (MAV) camera-IMU system. © 2010 Springer-Verlag.

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APA

Fraundorfer, F., Tanskanen, P., & Pollefeys, M. (2010). A minimal case solution to the calibrated relative pose problem for the case of two known orientation angles. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6314 LNCS, pp. 269–282). Springer Verlag. https://doi.org/10.1007/978-3-642-15561-1_20

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