Fourier Series Character AnimationAdapting and Generating Actions
نویسنده
چکیده
In this paper, we present a method for synthesizing and analysing rhythmic character motions using signal processing methodologies, such as, the Fourier transform. While the Fourier transform has proven itself in many fields of engineering and computing for providing an uncumbersome and efficient method of representing signal or functional information in the frequency domain. As we show in this paper, applying this concept of converting character joint signals to the frequency domain, allows us to categorise different motion elements. For example, walking styles, such as, stylistic qualities that include happy or tired, that we are able to identify and either filter or amplify. Additionally, the data from the transform provides a set of ground control parameters for recreating animations with similar characteristics. We show how the Fourier transform proposes a novel alternative to pure data-driven methods and how a hybrid system in combination with an adaptable physics-based model can be used to synthesize aesthetically pleasing motions that are controllable and physically-correct. We focus on demonstrating the enormous rewards of using the Fourier transform for motion analysis and in particular its application in extracting and generating unique motions that possess personal qualities.
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