Abstract. In this paper we present a novel image-based 3D surface reconstruction technique that incorporates reflectance, polarisation, and defocus information into a variational ...
Usually, optical flow computation is based on grayscale images and the brightness conservation assumption. Recently, some authors have investigated in transferring gradient-based ...
Volker Willert, Julian Eggert, Sebastian Clever, E...
Abstract. We consider the classification problem on a finite set of objects. Some of them are labeled, and the task is to predict the labels of the remaining unlabeled ones. Such...
We consider the problem of deblurring images which have been blurred by different reasons during image acquisition. We propose a variational approach admitting spatially variant an...
In this paper, we employ a zero-order local deformation model to model the visual variability of video streams of American sign language (ASL) words. We discuss two possible ways o...
Morteza Zahedi, Daniel Keysers, Thomas Deselaers, ...
The paper addresses the region search problem in three-dimensional (3D) space. The data used is a dynamically growing point cloud as it is typically gathered with a 3D-sensing devi...
A histogram-based method for the interpretation of three-dimensional (3D) point clouds is introduced, where point clouds represent the surface of a scene of multiple objects and ba...
This paper introduces a new operator to characterize a point in an image in a distinctive and invariant way. The robust recognition of points is a key technique in computer vision:...
Abstract: In this paper we introduce a novel method for automatic propagation of foreground objects in image sequences. Our method is based on a combination of the mean-shift opera...
Mario Sormann, Christopher Zach, Joachim Bauer, Ko...
We present a novel variational method for estimating dense disparity maps from stereo images. It integrates the epipolar constraint into the currently most accurate optic flow met...