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26 September 1997 3D-MBA: a novel multiresolution 3D object recognition system
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Abstract
An innovative model based object recognition system exploiting a priori knowledge called three dimensional model based approach (3D-MBA) is proposed in this paper. The idea behind 3D-MBA is to use virtual images to model the world and to utilize conventional vision to extract relevant clues in order to perform robust object recognition. By taking advantage of the different available sensors (range scanner, CCD camera) the system will combine top-down and bottom-up approaches by exploiting intensity, range and virtual images. Segmenting range images performs the feature extraction. These features are then combined to search in a geometrical constraint graph enabling object hypothesis generation, thus starting a prediction-verification process. We show that correlation techniques on range and intensity images can be used to validate the hypothesis. It is possible to refine those hypotheses to converge to the final recognition. Another technique to achieve 3-D mesh matching is ICP (iterative closest point). This iterative algorithm is used to find the best match between two sets of points. Each point of the first set is associated with the closest point in the second set. The best translation and rotation are evaluated in order to minimize point to point distance.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Emerico Natonek, R. Noll, and A. Vicario "3D-MBA: a novel multiresolution 3D object recognition system", Proc. SPIE 3208, Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling, (26 September 1997); https://doi.org/10.1117/12.290297
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