1-Point-based Monocular Motion Estimation for Computationally-Limited Micro Aerial Vehicles

Chiara Troiani 1, * Agostino Martinelli 1, * Christian Laugier 1, * Davide Scaramuzza 2
* Auteur correspondant
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : We propose a novel method to estimate the relative motion between two consecutive camera views, which only requires the observation of a single feature in the scene and the knowledge of the angular rates from an inertial measurement unit, under the assumption that the local camera motion lies in a plane perpendicular to the gravity vector. Using this 1- point motion parametrization, we provide two very efficient algorithms to remove the outliers of the feature-matching process. Thanks to their inherent efficiency, the proposed algorithms are very suitable for computationally-limited robots. We test the proposed approaches on both synthetic and real data, using video footage from a small flying quadrotor. We show that our methods outperform standard RANSAC-based implementations by up to two orders of magnitude in speed, while being able to identify the majority of the inliers.
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Communication dans un congrès
6th European Conference on Mobile Robots, Sep 2013, Barcelona, Spain. 2013
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Dernière modification le : jeudi 11 octobre 2018 - 08:48:02
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Chiara Troiani, Agostino Martinelli, Christian Laugier, Davide Scaramuzza. 1-Point-based Monocular Motion Estimation for Computationally-Limited Micro Aerial Vehicles. 6th European Conference on Mobile Robots, Sep 2013, Barcelona, Spain. 2013. 〈hal-00909626〉

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