Many computer vision problems can be considered to consist of two main tasks: the
extraction of image content descriptions and their subsequent matching. The appropriate …

Various applications, ranging from map creation tools to navigation systems, employ
methods introduced by the domain of georeferencing, which investigates techniques for …

Most state-of-the-art action feature extractors involve differential operators, which act as
highpass filters and tend to attenuate low frequency action information. This attenuation …

The linear and nonlinear scale spaces, generated by the inherently real-valued diffusion
equation, are generalized to complex diffusion processes, by incorporating the free …

In this paper we describe a novel technique for detecting salient regions in an image. The
detector is a generalization to affine invariance of the method introduced by Kadir and Brady …

We compared different methods of multi-scale terrain feature construction and their relative
effectiveness for digital soil map** with a Deep Learning algorithm. The most common …

A model of object shape by nets of medial and boundary primitives is justified as richly
capturing multiple aspects of shape and yet requiring representation space and image …

In this paper, we propose a novel Convolutional Neural Network (CNN) architecture for
learning multi-scale feature representations with good tradeoffs between speed and …

Detecting, identifying, and recognizing salient regions or feature points in images is a very
important and fundamental problem to the computer vision and robotics community. Tasks …

Scale is a critical factor when studying patterns and the processes that cause them. A variety
of approaches have been used to define the concept of scale, but confusion and ambiguities …