The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
Finding the largest consensus set is one of the key ideas used by the original RANSAC for removing outliers in robust-estimation. However, because of its random and non-determinis...
In this paper, we present an analytical method for computing the globally optimal estimates of orthogonal vanishing points in a “Manhattan world” with a calibrated camera. We ...
In this paper, we first develop a direct Bayesian based Support Vector Machine by combining the Bayesian analysis with the SVM. Unlike traditional SVM-based face recognition metho...
Rendering photorealistic virtual objects from their real images is one of the main research issues in mixed reality systems. We previously proposed the Eigen-Texture method, a new...