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Proceedings Paper

Rule-based system to reconstruct 3-D tree structure from two views
Author(s): Iching Liu; Ying Sun
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Paper Abstract

We propose a fully automatic system that reconstructs a 3-D tree structure based on two images taken from mutually orthogonal directions. The system comprises two major components, the high-level knowledge base and the low-level signal processing algorithms. Computational algorithms are responsible for tracking segments in each image, representing 2- D segments with directed graphs, and reconstructing 3-D segments from matching 2-D segment pairs. Knowledge of epipolar constraint, segments geometry, and connectivity are used to resolve the problem of matching segments between two views. Interaction between segmentation and matching is facilitated by uncertain reasoning. The knowledge base is represented by production rules which are implemented in the CLIPS shell. The computational algorithms are coded in the C language. The performance of the system is evaluated with images of a tree-like model. The total processing time for reconstruction of this tree-like model with 2563 resolution is 14 seconds on a workstation. The results show that the system is capable of correctly delineating an object's 3-D tree structure. This study demonstrates a non model-based approach to two-view reconstruction of tree-like structures.

Paper Details

Date Published: 1 November 1991
PDF: 11 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50315
Show Author Affiliations
Iching Liu, Univ. of Rhode Island (United States)
Ying Sun, Univ. of Rhode Island (United States)

Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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