The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Computer vision techniques can estimate 3D shape from images, but usually only up to a scale factor. The scale factor must be obtained by a physical measurement of the scene or the camera motion. Using gauge theory, we show that how this scale factor is determined can significantly affect the accuracy of the estimated shape. And yet these considerations have been ignored in previous works where 3D shape accuracy is optimized. We investigate how scale fixing influences the accuracy of 3D reconstruction and determine what measurement should be made to maximize the shape accuracy.

Keywords

Indeterminacies, stereo, structure from motion, orbits, freedoms

Notes

Associated Project(s): Modeling by Videotape

Text Reference

Daniel D. Morris, Kenichi Kanatani, and Takeo Kanade, "Gauge Fixing for Accurate 3D Estimation," Computer Vision and Pattern Recognition, December, 2001.

BibTeX Reference

@inproceedings{Morris_2001_3811,
   author = "Daniel D. Morris and Kenichi Kanatani and Takeo Kanade",
   title = "Gauge Fixing for Accurate 3D Estimation",
   booktitle = "Computer Vision and Pattern Recognition",
   month = "December",
   year = "2001",
}

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