Paper
8 March 2002 3D imaging for automated manufacturing assembly applications
Songtao Li, Dongming Zhao
Author Affiliations +
Proceedings Volume 4661, Three-Dimensional Image Capture and Applications V; (2002) https://doi.org/10.1117/12.460164
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Object pose estimation is an important application in 3D recognition. A 3D object pose estimating method is developed for an automated manufacturing assembly application. The target parts are extracted from the original range images using the traditional edge detection and segmentation methods. The center position is then computed through the circle Hough transform algorithm. For the 3D orientation estimation, a 3D geometrical feature descriptor, Angle Distance Map (ADM), is proposed to describe the 3D local surface feature. A triangular mesh model of 3D object is used for reducing the computational complexity. The principal component analysis (PCA) method is applied on the ADM descriptions for efficient comparison. The orientation information is computed according to the extracted 3D feature points. The proposed method is tested in an application for flexible robot assembly. The experimental results show that accurate 3D pose estimation can be obtained.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Songtao Li and Dongming Zhao "3D imaging for automated manufacturing assembly applications", Proc. SPIE 4661, Three-Dimensional Image Capture and Applications V, (8 March 2002); https://doi.org/10.1117/12.460164
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KEYWORDS
3D image processing

3D modeling

3D acquisition

Image segmentation

Principal component analysis

Error analysis

Feature extraction

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