Abstract:
Abstract — Capturing live motion has gained considerable attention in computer animation as an important motion generation technique. Canned motion data comprise both position and orientation components. Although a great deal of signal processing methods are available for manipulating position data, the majority of these methods cannot be generalized easily to orientation data due to the inherent non-linearity of the orientation space. In this paper, we present a new scheme that enables us to apply a filter mask (or a convolution filter) to orientation data. The key idea is to transform the orientation data into their analogues in a vector space, to apply a filter mask on them, and then to transform the results back to the orientation space. This scheme gives time-domain filters for orientation data that are computationally efficient and satisfy such important properties as coordinate-invariance, time-invariance, and symmetry. Experimental results indicate that our scheme is useful for various purposes including smoothing and sharpening.
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