Abstract
We address in this paper how to find clusters based on proximity and planar facets based on coplanarity from 3D line segments obtained from stereo. The proposed methods are efficient and have been tested with many real stereo data. These procedures are indispensable in many applications including scene interpretation, object modeling and object recognition. We show their application to 3D motion determination. We have developed an algorithm based on the hypothesize-and-verify paradigm to register two consecutive 3D frames and estimate their transformation/motion. By grouping 3D line segments in each frame into clusters and planes, we can reduce effectively the complexity of the hypothesis generation phase.
This work was supported in part by Esprit project P940.
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© 1992 Springer-Verlag Berlin Heidelberg
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Zhang, Z., Faugeras, O.D. (1992). Finding clusters and planes from 3D line segments with application to 3D motion determination. 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_26
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DOI: https://doi.org/10.1007/3-540-55426-2_26
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