Simultaneous reconstruction and tracking of non-planar templates

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Abstract

In this paper, we address the problem of simultaneous tracking and reconstruction of non-planar templates in real-time. Classical approaches to template tracking assume planarity and do not attempt to recover the shape of an object. Structure from motion approaches use feature points to recover camera pose and reconstruct the scene from those features, but do not produce dense 3D surface models. Finally, deformable surface tracking approaches assume a static camera and impose strong deformation priors to recover dense 3D shapes. The proposed method simultaneously recovers the camera motion and deforms the template such that an approximation of the underlying 3D structure is recovered. Spatial smoothing is not explicitly imposed, thus templates of smooth and non-smooth objects can be equally handled. The problem is formalized as an energy minimization based on image intensity differences. Quantitative and qualitative evaluation on both real and synthetic data is presented, we compare the proposed approach to related methods and demonstrate that the recovered camera pose is close to the ground truth even in presence of strong blur and low texture. © 2011 Springer-Verlag.

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Lieberknecht, S., Benhimane, S., & Ilic, S. (2011). Simultaneous reconstruction and tracking of non-planar templates. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6835 LNCS, pp. 396–405). https://doi.org/10.1007/978-3-642-23123-0_40

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