Infrared (IR) images depict thermal radiation of physical objects. Imaging the building hull with an IR camera allows thermal inspections. Mapping these images as textures on 3D building models, 3D geo-referencing of each pixel can be carried out. This is helpful for large area inspections. In IR images glass reflects the surrounding and shows false results for the temperature measurements. Con...

Roughness is probably the most salient dimension pertaining to the perception of textures by touch and has been widely investigated. There is a controversy on how roughness relates to the texture’s spatial period and which factors influence this relation. Here, roughness during bare finger exploration of coarse textures is studied for different types of textures with elements of low height (0.3...

We are investigating techniques for providing smooth transitions when simplifying large, static geometric models with texture-based representations (or impostors). Traditionally, textures have been used to replace complex geometry, for example the books on a shelf or the complex foliage on a tree. Using textures in a more general manner is a relatively new area of research. The key idea is that...

Image smoothing is a fundamental task in computer vision, which aims to retain salient structures and remove insignificant textures. In this paper, we tackle the natural deficiency of existing methods, that they cannot properly distinguish textures and structures with similar lowlevel appearance. While deep learning approaches have addressed preserving structures, they do not yet properly addre...

In texture analysis the common methods are based on the gray levels of the texture image. However, the use of color information improves the classification accuracy of the colored textures. In the classification of nonhomogenous natural textures, human texture and color perception are important. Therefore, the color space and texture analysis method should be selected to correspond to human vis...