CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
We present a closed form solution to the problem of segmenting multiple 2-D motion models of the same type directly from the partial derivatives of an image sequence. We introduce...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
Dynamic programming on a scanline is one of the oldest and still popular methods for stereo correspondence. While efficient, its performance is far from the state of the art becau...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
Independent Components Analysis (ICA) maximizes the statistical independence of the representational components of a training image ensemble, but it cannot distinguish between the...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
In this paper we focus on high dimensional data sets for which the number of dimensions is an order of magnitude higher than the number of objects. From a classifier design standp...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
In this paper we present coupled partial differential equations (PDEs) for the problem of joint segmentation and registration. The registration component of the method estimates a...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
We propose a camera that measures static gradients instead of static intensities. Quantizing sensed intensity differences between adjacent pixel values permits an ordinary A/D con...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
CVPR
2005
IEEE
14 years 11 months ago
2005
IEEE
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...