Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
We describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. By combining a deformation-based method for mea...
Gustavo K. Rohde, Wei Wang, Tao Peng, Robert F. Mu...
Difficulties understanding update paths while understanding code cause developers to waste time and insert bugs. A detailed investigation of these difficulties suggests that a wid...