3D model-based tracking for UAV indoor localisation

Céline Teulière 1, 2 Eric Marchand 3 Laurent Eck 2
3 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : This paper proposes a novel model-based tracking approach for 3D localisation. One main difficulty of standard model-based approach lies in the presence of low-level ambigui- ties between different edges. In this work, given a 3D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localisation problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.
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Céline Teulière, Eric Marchand, Laurent Eck. 3D model-based tracking for UAV indoor localisation. IEEE Trans. on Cybernetics, IEEE, 2015, 45 (5), pp.869-879. ⟨10.1109/TCYB.2014.2337652 ⟩. ⟨hal-01020618⟩

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