Expert driven semi-supervised elucidation tool for medical endoscopic videos

In this paper, we present a novel application for elucidating all kind of videos that require expert knowledge, e.g., sport videos, medical videos etc., focusing on endoscopic surgery and video capsule endoscopy. In the medical domain, the knowledge of experts for tagging and interpretation of videos is of high value. As a result of the stressful working environment of medical doctors, they often simply do not have time for extensive annotations. We therefore present a semi-supervised method to gather the annotations in a very easy and time saving way for the experts and we show how this information can be used later on

Ontology of a scene based on Java 3D architecture

The present article seeks to make an approach to the class hierarchy of a scene built with the architecture Java 3D, to develop an ontology of a scene as from the semantic essential components for the semantic structuring of the Web3D. Java was selected because the language recommended by the W3C Consortium for the Development of the Web3D oriented applications as from X3D standard is Xj3D which compositionof their Schemas is based the architecture of Java3D In first instance identifies the domain and scope of the ontology, defining classes and subclasses that comprise from Java3D architecture and the essential elements of a scene, as its point of origin, the field of rotation, translation The limitation of the scene and the definition of shaders, then define the slots that are declared in RDF as a framework for describing the properties of the classes established from identifying the domain and range of each class, then develops composition of the OWL ontology on SWOOP Finally, be perform instantiations of the ontology building for a Iconosphere object as from class expressions defined