DocumentCode :
1081846
Title :
Determining pose of 3D objects with curved surfaces
Author :
Chen, Jin-Long ; Stockman, George C.
Author_Institution :
Pattern Recognition & Imaging Process. Lab., Michigan State Univ., East Lansing, MI, USA
Volume :
18
Issue :
1
fYear :
1996
fDate :
1/1/1996 12:00:00 AM
Firstpage :
52
Lastpage :
57
Abstract :
A method is presented for computing the pose of rigid 3D objects with arbitrary curved surfaces. Given an input image and a candidate object model and aspect, the method will verify whether or not the object is present and if so, report pose parameters. The curvature method of Bash and Ullman is used to model points on the object rim, while stereo matching is used for internal edge points. The model allows an object edge-map to be predicted from pose parameters. Pose is computed via an iterative search for the best pose parameters. Heuristics are used so that matching can succeed in the presence of occlusion and artifact and without resetting to use of corresponding salient feature points. Bench tests and simulations show that the method almost always converges to ground truth pose parameters for a variety of objects and for a broad set of starting parameters in the same aspect
Keywords :
edge detection; feature extraction; image matching; object detection; stereo image processing; 3D object pose recognition; curvature method; curved surfaces; edge-map prediction; heuristics; image matching; internal edge points; iterative search; object tracking; stereo matching; Computational modeling; Image converters; Image matching; Image processing; Image recognition; Image segmentation; Object recognition; Parametric statistics; Predictive models; Testing;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.476010
Filename :
476010
Link To Document :
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