The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...
Matrix decomposition methods provide representations of an object-variable data matrix by a product of two different matrices, one describing relationship between objects and hidd...
Linear and multi-linear models of object shape/appearance (PCA, 3DMM, AAM/ASM, multilinear tensors) have been very popular in computer vision. In this paper, we analyze the validi...
In this paper we report on a study in which genetic algorithms are applied to the analysis of noisy time-series signals, which is related to the problem of analyzing the motion ch...
This paper presents a hybrid 1D motion estimation algorithm which combines pixel-based and region-based approaches that can give depth images from translational video sequences wi...