Many sensing techniques and image processing applications are characterized by noisy, or corrupted, image data. Anisotropic diffusion is a popular, and theoretically well understo...
Hanno Scharr, Michael J. Black, Horst W. Haussecke...
Example-based methods are effective for parameter estimation problems when the underlying system is simple or the dimensionality of the input is low. For complex and high-dimensio...
Gregory Shakhnarovich, Paul A. Viola, Trevor Darre...
We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set...
Visual learning is expected to be a continuous and robust process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which...
Previous studies have demonstrated that the appearance of an object under varying illumination conditions can be represented by a low-dimensional linear subspace. A set of basis i...
We consider the problem of segmentation of images that can be modelled as piecewise continuous signals having unknown, non-stationary statistics. We propose a solution to this pro...
Registration of a preoperative CT (3D) image to one or more X-ray projection (2D) images, a special case of the pose estimation problem, has been attempted in a variety of ways wi...
Daniel B. Russakoff, Torsten Rohlfing, Calvin R. M...
We present a method for shape reconstruction from several images of a moving object. The reconstruction is dense (up to image resolution). The method assumes that the motion is kn...
Most of the work on 3-D object recognition from range data has used an alignment-verification approach in which a specific 3-D object is matched to an exact instance of the same o...
Salvador Ruiz-Correa, Linda G. Shapiro, Marina Mei...