s of the LIX Fall Colloquium 2008: Emerging Trends in Visual Computing Frank Nielsen Ecole Polytechnique, Palaiseau, France Sony CSL, Tokyo, Japan Abstract. We list the abstracts o...
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...