Example-based learning of codes that statistically encode general image classes is of vital importance for computational vision. Recently, non-negative matrix factorization (NMF) ...
Recently there has been a lot of interest in geometrically motivated approaches to data analysis in high dimensional spaces. We consider the case where data is drawn from sampling...
Xiaofei He, Deng Cai, Shuicheng Yan, HongJiang Zha...
We introduce an algorithm for a non-negative 3D tensor factorization for the purpose of establishing a local parts feature decomposition from an object class of images. In the pas...
We propose a method of simultaneously calibrating the radialdistortionfunctionofacameraalongwith theotherinternal calibration parameters. The method relies on the use of a planar ...
In this paper, we propose a new method for simultaneously estimating the illumination of the scene and the reflectance property of the object from a single image. We assume that t...
In this paper, we present an attribute graph grammar for image parsing on scenes with man-made objects, such as buildings, hallways, kitchens, and living rooms. We choose one clas...
Object tracking is a challenging problems in real-time computer vision due to variations of lighting condition, pose, scale, and view-point over time. However, it is exceptionally...
Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...
This paper describes a photometric stereo method designed for surfaces with spatially-varying BRDFs, including surfaces with both varying diffuse and specular properties. Our meth...
Dan B. Goldman, Brian Curless, Aaron Hertzmann, St...
We discuss calibration and removal of "vignetting" (radial falloff) and exposure (gain) variations from sequences of images. Unique solutions for vignetting, exposure an...