Many approaches have been proposed to solve the problem of finding the optic flow field of
an image sequence. Three major classes of optic flow computation techniques can …

Not all interest points are equally interesting. The most valuable interest points lead to
optimal performance of the computer vision method in which they are employed. But a …

Recently, there has been a great deal of interest in modeling the non-Gaussian structures of
natural images. However, despite the many advances in the direction of sparse coding and …

This dissertation contributes to an in-depth analysis of the SIFT method. SIFT is the most
popular and the first efficient image comparison model. SIFT is also the first method to …

Local scale information extracted from visual data in a bottom-up manner constitutes an
important cue for a large number of visual tasks. This article presents a framework for how …

This paper presents a novel method for addressing the problem of finding more good feature
pairs between images, which is one of the most fundamental tasks in computer vision and …

According to Marr's paradigm of computational vision the first process is an extraction of
relevant features. The goal of this paper is to quantify and characterize the information …

Visual motion carries information about the dynamics of a scene. Automatic interpretation of
this information is important when designing computer systems for visual navigation …

For remote sensing image registration, we find that affine transformation is suitable to
describe the mapping between images. Based on the scale-invariant feature transform …

Image reconstruction from a fiducial collection of scale space interest points and attributes
(eg in terms of image derivatives) can be used to make the amount of information contained …