Error Analysis of 3-D Motion Estimation Algorithms in the Differential Case

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http://doi.ieeecomputersociety.org/10.1109/CVPR.2003.1211377

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	Tao Xiang, Loong-Fah Cheong, "Error Analysis of 3-D Motion Estimation Algorithms in the Differential Case," Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, vol. 1, pp. 369, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 1, 2003.

	BibTex	x
	@article{ 10.1109/CVPR.2003.1211377, author = {Tao Xiang and Loong-Fah Cheong}, title = {Error Analysis of 3-D Motion Estimation Algorithms in the Differential Case}, journal ={Computer Vision and Pattern Recognition, IEEE Computer Society Conference on}, volume = {1}, year = {2003}, issn = {1063-6919}, pages = {369}, doi = {http://doi.ieeecomputersociety.org/10.1109/CVPR.2003.1211377}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on TI - Error Analysis of 3-D Motion Estimation Algorithms in the Differential Case SN - 1063-6919 SP EP A1 - Tao Xiang, A1 - Loong-Fah Cheong, PY - 2003 KW - null VL - 1 JA - Computer Vision and Pattern Recognition, IEEE Computer Society Conference on ER -

Tao Xiang, University of London

Loong-Fah Cheong, National University of Singapore

We put forth in this paper a geometrically motivated 3-D motion error analysis which is capable of supporting investigation of global effect such as inherent ambiguities. The error expression that we derive allows us to predict the exact conditions likely to cause ambiguities and how these ambiguities vary with motion types such as lateral or forward motion. Our formulation, though geometrically motivated, is employed to model the effect of noise.

Citation:

Tao Xiang, Loong-Fah Cheong, "Error Analysis of 3-D Motion Estimation Algorithms in the Differential Case," cvpr, vol. 1, pp.369, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 1, 2003

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