44 search results - page 5 / 9 » Computationally Efficient Estimators for Dimension Reduction... |
DAGM
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Approaches to visual navigation, e.g. used in robotics, require computationally efficient, numerically stable, and robust methods for the estimation of ego-motion. One of...
ECCV
2008
Springer
14 years 9 months ago
2008
Springer
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Algorithms such as Least Median of Squares (LMedS) and Random Sample Consensus (RANSAC) have been very successful for low-dimensional robust regression problems. However, the comb...
ACCV
2006
Springer
14 years 1 months ago
2006
Springer
Abstract. To develop statistical models for shapes, we utilize an elastic string representation where curves (denoting shapes) can bend and locally stretch (or compress) to optimal...
BMVC
2010
13 years 5 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...