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Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models

Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models

Xavier Perez-Sala, Laura Igual, Sergio Escalera, Cecilio Angulo
Copyright: © 2013 |Pages: 20
ISBN13: 9781466626720|ISBN10: 1466626720|EISBN13: 9781466627031
DOI: 10.4018/978-1-4666-2672-0.ch002
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MLA

Perez-Sala, Xavier, et al. "Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models." Robotic Vision: Technologies for Machine Learning and Vision Applications, edited by Jose Garcia-Rodriguez and Miguel A. Cazorla Quevedo, IGI Global, 2013, pp. 23-42. https://doi.org/10.4018/978-1-4666-2672-0.ch002

APA

Perez-Sala, X., Igual, L., Escalera, S., & Angulo, C. (2013). Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models. In J. Garcia-Rodriguez & M. Cazorla Quevedo (Eds.), Robotic Vision: Technologies for Machine Learning and Vision Applications (pp. 23-42). IGI Global. https://doi.org/10.4018/978-1-4666-2672-0.ch002

Chicago

Perez-Sala, Xavier, et al. "Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models." In Robotic Vision: Technologies for Machine Learning and Vision Applications, edited by Jose Garcia-Rodriguez and Miguel A. Cazorla Quevedo, 23-42. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2672-0.ch002

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Abstract

Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis.

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