A general framework for smoothing a finite sequential set of two-dimensional frames is proposed in this paper. It is intuitive that the more the number of frames is, the smoother the frames will be. However, the storage space required for handling the frames will also be increased. Given the desired size of the frames, finding an optimal frame set is facilitated by the notion of smoothness. The smoothness of a frame set is measured in terms of the energy embedded in the frame set, on the analogy of measuring the smoothness of motion data. A frame set with lower energy value is considered to be smoother. Then, the problem of finding a frame set of given frame size which gives the smoothest measure is formulated as an optimization problem that seeks to minimize the weighted sum of the frame energy and the sum of the squared distance errors.
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