Abstract
This paper presents a new method for evaluating the spatial attitude (position-orientation) of a 3D object by matching a 3D static model of this object with sensorial data describing the scene (2D projections or 3D sparse coordinates). This method is based on the pre-computation of a force field derived from 3D distance maps designed to attract any 3D point toward the surface of the model. The attitude of the object is infered by minimizing the energy necessary to bring all of the 3D points (or projection lines) in contact with the surface (geometric configuration of the scene). To quickly and accurately compute the 3D distance maps, a precomputed distance map is represented using an octree spline whose resolution increases near the surface.
The research described in this paper is supported by DEC and Safir-Groupe Sem companies.
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Keywords
- Projection Line
- Iterative Minimization
- Match Line
- Signed Euclidean Distance
- Iterative Minimization Procedure
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
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© 1992 Springer-Verlag Berlin Heidelberg
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Brunie, L., Lavallée, S., Szeliski, R. (1992). Using force fields derived from 3D distance maps for inferring the attitude of a 3D rigid object. In: Sandini, G. (eds) Computer Vision — ECCV'92. ECCV 1992. Lecture Notes in Computer Science, vol 588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55426-2_72
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DOI: https://doi.org/10.1007/3-540-55426-2_72
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