DREAM - data driven ReActive modelling

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In a world where both virtual and digital objects reside, it is important that not just the appearance but the behaviour of a digital model should be able to imitate real objects, react realistically to its surroundings or be programmable to behave as we desire. In this project we will develop a modelling paradigm capable of delivering such a goal. At the core of any virtual environment are the geometric models that represent real objects. In this research project, the first step is to develop a modelling paradigm to produce a reactive model; not a mere visual representation of the object in the scene, but one whose behaviour takes account of its behavioral structure, as well as the world in which it exists. Not only should a model be able to react and actively participate with other virtual elements in an organic and physically realistic fashion but it should also be able to answer self-queries. In the same way a smart-phone is aware of its position, status and is fully connected to the internet, our models could be instrumented with meta-information that would further enrich their interaction capability with the augmented environment. For example, a human brain meta-model could be equipped with short range sensors capable of exactly identifying surgery tools positions during virtual brain biopsy. Our approach is to build upon concepts from implicit modelling, in which models of generic topology and geometry can be represented as iso-surfaces of scalar fields. By designing suitable functions the combination of fields and their gradients can yield complex, reactive models. While retaining the power to represent generic geometry, these volumetric models allow for efficient and scalable tracking.