16. The storage medium of claim 15 , wherein said creating the sequence of synthesized poses comprises: constructing a feature vector for each of a plurality of samples of the query stroke, wherein the feature vector for each of the plurality of samples comprises trajectory data components that are dependent on trajectory data for one or more neighboring samples of the query stroke; comparing the feature vector for each of the plurality of samples of the query stroke to feature vectors for a plurality of samples of one or more reference strokes; identifying a best neighbor feature vector for each of the plurality of samples of the query stroke from among the feature vectors for the plurality of samples of the one or more reference strokes, wherein the best neighbor feature vector for each of the plurality of samples of the query stroke comprises the pose data for a corresponding sample of one of the one or more reference strokes; and assigning the pose data of the best neighbor feature vector for each of the plurality of samples of the query stroke as pose data for the sample of the query stroke.
16. The storage medium of claim 15 , wherein said creating the sequence of synthesized poses comprises: constructing a feature vector for each of a plurality of samples of the query stroke, wherein the feature vector for each of the plurality of samples comprises trajectory data components that are dependent on trajectory data for one or more neighboring samples of the query stroke; comparing the feature vector for each of the plurality of samples of the query stroke to feature vectors for a plurality of samples of one or more reference strokes; identifying a best neighbor feature vector for each of the plurality of samples of the query stroke from among the feature vectors for the plurality of samples of the one or more reference strokes, wherein the best neighbor feature vector for each of the plurality of samples of the query stroke comprises the pose data for a corresponding sample of one of the one or more reference strokes; and assigning the pose data of the best neighbor feature vector for each of the plurality of samples of the query stroke as pose data for the sample of the query stroke. 18. The storage medium of claim 16 , wherein said creating the sequence of synthesized poses further comprises: identifying a collection of nearest neighbor feature vectors for each of the plurality of samples of the query stroke, wherein the collection of nearest neighbor feature vectors for each sample of the query stroke comprises two or more feature vectors for respective samples of one or more reference strokes that are most similar to the feature vector constructed for the sample of the query stroke; and wherein said identifying a best neighbor feature vector for each of the plurality of samples of the query stroke comprises selecting one of the nearest neighbor feature vectors from each of the collections of nearest neighbor feature vectors.