The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
We propose a method for estimating camera response functions using a probabilistic intensity similarity measure. The similarity measure represents the likelihood of two intensity ...
Jun Takamatsu, Yasuyuki Matsushita, Katsushi Ikeuc...
Tensor based dimensionality reduction has recently been extensively studied for computer vision applications. To our knowledge, however, there exist no rigorous error analysis on ...
We present a novel approach to learn distance metric for information retrieval. Learning distance metric from a number of queries with side information, i.e., relevance judgements...
In this paper, we propose a novel robust retrieval and classification system for video and motion events based on null space representation. In order to analyze the robustness of ...
In this work we aim to capitalize on the availability of Internet image search engines to automatically create image training sets from user provided queries. This problem is part...
This paper presents a new photometric stereo method aiming to efficiently estimate BRDF and reconstruct glossy surfaces. Rough specular surfaces exhibit wide specular lobes under ...
Region based features are getting popular due to their higher descriptive power relative to other features. However, real world images exhibit changes in image segments capturing ...
In this paper, we present an approach we refer to as "least squares congealing" which provides a solution to the problem of aligning an ensemble of images in an unsuperv...
Mark Cox, Sridha Sridharan, Simon Lucey, Jeffrey F...