Sensing and compressing 3-D models

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Description

The goal of this research project was to create a passive and robust computer vision system for producing 3-D computer models of arbitrary scenes. Although the authors were unsuccessful in achieving the overall goal, several components of this research have shown significant potential. Of particular interest is the application of parametric eigenspace methods for planar pose measurement of partially occluded objects in gray-level images. The techniques presented provide a simple, accurate, and robust solution to the planar pose measurement problem. In addition, the representational efficiency of eigenspace methods used with gray-level features were successfully extended to binary features, which are ... continued below

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23 p.

Creation Information

Krumm, J. February 1, 1998.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this article can be viewed below.

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  • Krumm, J. Sandia National Labs., Albuquerque, NM (United States). Intelligent System Sensors and Controls Dept.

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  • Sandia National Laboratories
    Publisher Info: Sandia National Labs., Albuquerque, NM (United States)
    Place of Publication: Albuquerque, New Mexico

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Description

The goal of this research project was to create a passive and robust computer vision system for producing 3-D computer models of arbitrary scenes. Although the authors were unsuccessful in achieving the overall goal, several components of this research have shown significant potential. Of particular interest is the application of parametric eigenspace methods for planar pose measurement of partially occluded objects in gray-level images. The techniques presented provide a simple, accurate, and robust solution to the planar pose measurement problem. In addition, the representational efficiency of eigenspace methods used with gray-level features were successfully extended to binary features, which are less sensitive to illumination changes. The results of this research are presented in two papers that were written during the course of this project. The papers are included in sections 2 and 3. The first section of this report summarizes the 3-D modeling efforts.

Physical Description

23 p.

Notes

OSTI as DE98002851

Source

  • IEEE Computer Society conference on computer vision pattern recognition, San Francisco, CA (United States); San Juan (Puerto Rico), 16-20 Jun 1996; 17-19 Jun 1997

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  • Other: DE98002851
  • Report No.: SAND--98-0503
  • Report No.: CONF-960672--3;CONF-970679--2
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 573305
  • Archival Resource Key: ark:/67531/metadc697229

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • February 1, 1998

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

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  • April 14, 2016, 6:47 p.m.

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Krumm, J. Sensing and compressing 3-D models, article, February 1, 1998; Albuquerque, New Mexico. (digital.library.unt.edu/ark:/67531/metadc697229/: accessed December 13, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.