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Proceedings Paper

Depth quantization for polygonal consolidation from range data
Author(s): Michael J. Meehan; Richard N. Ellson
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Paper Abstract

Computer graphics rendering and the compression of range data with its associated color data impact the quality and speed of reconstructing photo realistic images from range/color scans of real world scenes. A method of consolidating orthographically scanned, quantized range data into polygons was developed with the intent of being both practical and efficient in its processing and storage of only the information required for producing a new photo-realistic image from nearly the same perspective as the original scan. Tests were performed on both actual range data and data extracted from the z-buffer of polygonal computer graphics renderings. In each case, for every range value a 24-bit color was associated with each range value. A polygon was constructed to represent the range and color data. Surface normals were calculated for each polygon, and consolidation of neighboring polygons was performed if their normals occupied the same quantized region of the Gaussian sphere. Results on polygonal consolidation ratios and reconstructed image quality as a function of quantization will be presented.

Paper Details

Date Published: 10 June 1993
PDF: 6 pages
Proc. SPIE 1904, Image Modeling, (10 June 1993); doi: 10.1117/12.146692
Show Author Affiliations
Michael J. Meehan, Purdue Univ. (United States)
Richard N. Ellson, Eastman Kodak Co. (United States)

Published in SPIE Proceedings Vol. 1904:
Image Modeling
Lawrence A. Ray; James R. Sullivan, Editor(s)

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