AVDT - Automatic Visualization of Descriptive Texts

Abstract

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Expressing mental images visually as 3D scenes is a time-consuming challenge. Therefore, we employ natural language to facilitate the creation of virtual environments. In this paper, we present a framework, which automatically converts an arbitrary descriptive text into a representative 3D scene. Our system parses a user-written input text, extracts information using techniques from Natural Language Processing (NLP) and identifies relevant units. Based on derived object-to-object relations, our system associates every object with an appropriate 3D model and evaluates spatial dependencies of the entities. The resulting locations are combined based on adequate heuristics in order to create natural looking virtual environments. Finally, a physics engine is used to render a realistic and interactive 3D scene which enables the user to actively manipulate the stage setup.