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Real-time Dense Visual Tracking under Large Lighting Variations

Abstract : This paper proposes a model for large illumination variations to improve direct 3D tracking techniques since they are highly prone to illumination changes. Within this context dense monocular and multi-camera tracking techniques are presented which each perform in real-time (45Hz). The proposed approach exploits the relative advantages of both model-based and visual odometry techniques for tracking. In the case of direct model-based tracking, photometric models are usually acquired under significantly greater lighting differences than those observed by the current camera view, however, model-based approaches avoid drift. Incremental visual odometry, on the other hand, has relatively less lighting variation but integrates drift. To solve this problem a hybrid approach is proposed to simultaneously minimise drift via a 3D model whilst using locally consistent illumination to correct large photometric differences. Direct 6 dof tracking is performed by an accurate method, which directly minimizes dense image measurements iteratively, using non-linear optimisation. A stereo technique for automatically acquiring the 3D photometric model has also been optimised for the purpose of this paper. Real experiments are shown on complex 3D scenes for a hand-held camera undergoing fast 3D movement and various illumination changes including daylight, artificial-lights, significant shadows, non-Lambertian reflections, occlusions and saturations.
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Submitted on : Thursday, March 7, 2019 - 3:46:59 PM
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Maxime Meilland, Andrew I. Comport, Patrick Rives. Real-time Dense Visual Tracking under Large Lighting Variations. British Machine Vision Conference, Aug 2011, Dundee, Scotland, United Kingdom. pp.45.1-45.11, ⟨10.5244/C.25.45⟩. ⟨hal-02060747⟩



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