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Data Driven Interactive Virtual Characters

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This work is about using data from peoples movements to learn AI methods for controlling the bahaviour of animated characters. It pioneered the use of machine learning for virtual characters, particularly for AI aspects (as opposed to animation, where it was already quite common).

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One of the key aspects of this work was the development of two person capture techniques which allowed us to capture both the behaviour of the character, but also the behaviour of the person the character was interacting with. By synchronising the two data sets, we were able to learn a model that could generate responses from the character. We now call this technique “Interactive Performance Capture”.