This paper presents a novel method for detecting scale
invariant keypoints. It fills a gap in the set of available
methods, as it proposes a scale-selection mechanism for
juncti...
Wolfgang F¨orstner, Timo Dickscheid, Falko Schind...
This paper presents a method for learning artistic portrait lighting template from a dataset of artistic and daily portrait photographs. The learned template can be used for (1) cl...
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
A new model for the multiscale characterization of turbulence and chaotic information in digital images is presented. The model is applied to infrared satellite images for the det...
This paper develops an efficient new method for 3D partial shape retrieval. First, a Monte Carlo sampling strategy is employed to extract local shape signatures from each 3D model...