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Article Dans Une Revue Computer Vision and Image Understanding Année : 2013

Manifold surface reconstruction of an environment from sparse Structure-from-Motion data

Maxime Lhuillier

Résumé

The majority of methods for the automatic surface reconstruction of an environment from an image sequence have two steps: Structure-from-Motion and dense stereo. From the computational standpoint, it would be interesting to avoid dense stereo and to generate a surface directly from the sparse cloud of 3D points and their visibility information provided by Structure-from-Motion. The previous attempts to solve this problem are currently very limited: the surface is non-manifold or has zero genus, the experiments are done on small scenes or objects using a few dozens of images. Our solution does not have these limitations. Furthermore, we experiment with hand-held or helmet-held catadioptric cameras moving in a city and generate 3D models such that the camera trajectory can be longer than one kilometer.
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Dates et versions

hal-01635450 , version 1 (03-06-2020)

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Maxime Lhuillier, Shuda Yu. Manifold surface reconstruction of an environment from sparse Structure-from-Motion data. Computer Vision and Image Understanding, 2013, 117 (11), pp.1628 - 1644. ⟨10.1016/j.cviu.2013.08.002⟩. ⟨hal-01635450⟩
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