The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
This paper addresses the problem of applying powerful pattern recognition algorithms based on kernels to efficient visual tracking. Recently Avidan [1] has shown that object recog...
Oliver M. C. Williams, Andrew Blake, Roberto Cipol...
We present a new approach to 3D scene modeling based on geometric constraints. Contrary to the existing methods, we can quickly obtain 3D scene models that respect the given const...
Marta Wilczkowiak, Gilles Trombettoni, Christophe ...
Photometric invariance is used in many computer vision applications. The advantage of photometric invariance is the robustness against shadows, shading, and illumination condition...
Joost van de Weijer, Theo Gevers, Jan-Mark Geusebr...
In this paper we use the cumulative distribution of a random variable to define the information content in it and use it to develop a novel measure of information that parallels S...
This paper proposes a switching hypothesized measurements (SHM) model supporting multimodal probability distributions and presents the application of the model in handling potenti...
We propose a face difference model that decomposes face difference into three components, intrinsic difference, transformation difference, and noise. Using the face difference mod...
Human identification at a distance has recently gained growing interest from computer vision researchers. This paper aims to propose a visual recognition algorithm based upon fusi...
In vision and graphics, there is a sustained interest in capturing accurate 3D shape with various scanning devices. However, the resulting geometric representation is only part of...
This paper presents a novel approach for landmarkbased shape deformation, in which fitting error and shape difference are formulated into a support vector machine (SVM) regression...