This paper proposes a new way to achieve feature point tracking using the entropy of the image. Sum of Squared Differences (SSD) is widely considered in differential trackers such ...
Most of the state-of-the-art tracking algorithms are prone to error when dealing with occlusions, especially when the involved moving objects are hardly discernible in appearance....
In recent years, many principled probabilistic definitions for the determination of visual saliency have been proposed. Moreover, there has been increased focus on the role of con...
Compressive Sensing (CS) is a new paradigm in signal acquisition and compression. In compressive sensing, a compressible signal is acquired using much less measurements than the o...
In this paper, we aim to provide the further evaluation on the recently proposed visualization technique known as Virtual Fly-Over for virtual colonoscopy by using clinical CT col...
It is a common practice to model an object for detection tasks as a boosted ensemble of many models built on features of the object. In this context, features are defined as subre...
We design a family of non-local image smoothing algorithms which approximate the application of diffusion PDE's on a specific Euclidean space of image patches. We first map a...
This paper presents a novel non-local iterative backprojection (NLIBP) algorithm for image enlargement. The iterative back-projection (IBP) technique iteratively reconstructs a hi...
A novel approach is proposed to estimate the parameters of a diffeomorphism that aligns two binary images. Classical approaches usually define a cost function based on a similarit...
Patch based denoising methods, such as the NL-Means, have emerged recently as simple and efficient denoising methods. This paper provides a new insight on those methods by showing...