The problem of automatic threshold selection is considered. After a brief review of available techniques, a novel method is proposed. It is based on image statistics which can be computed without histogramming the grey level values of the image. A detailed analysis of the properties of the algorithm is then carried out. The effectiveness of the method is shown on a number of practical examples.

The support for multi-threaded applications in current scene graphs is very limited, if it is supported at all. This work presents an approach for a very general multi-threading framework that allows total separation of threads without total replication of data. It also supports extensions to clusters, both for sort-first and sort-last rendering configurations. The described concepts have been ...

In this paper, we are presenting a novel approach that allows rendering of a dynamic scene in a view-dependent manner. We shall refer to such scene as a view-dependent scene. View-dependence scene is a scene graph which stores the objects of the scene in a hierarchical structure. The objects are stored in the leaves of the graph in a form of viewdependence trees. Our approach does not only allo...

Spectral reflectance is often derived from a sequence of images acquired under different, narrowband, infinitely far away illuminants, which means their intensity is constant throughout the scene. When small LEDs, located close to the target are used the light intensity becomes scene depth dependent. We propose to use an RGB+depth camera which lets us model the spatial light intensity falloff a...

We present a scenegraph-based schema, the ContextMap, to model context information. Locations with hierarchical relations are the skeleton of the ContextMap where nodes of people, objects and activities can be attached. Context information can be collected by traversing the ContextMap. The ContextMap provides a uniform method to represent physical and social semantics for context-aware computin...

The contrast statistics of natural images can be adequately characterized by a two-parameter Weibull distribution. Here we show how distinct regimes of this Weibull distribution lead to various classes of visual content. These regimes can be determined using model selection techniques from information theory. We experimentally explore the occurrence of the content classes, as related to the glo...

In the field of visual recognition such as scene categorization, representing an image based on the local feature (e.g. the bags of visual words (BOW) model and its variants) has become popular and one of the most successful methods. In this paper, we propose a method that uses localized maximum-margin learning to fuse different types of features during the BOW modeling process for eventual sce...