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Under general assumption, head motion is categorized into three degree of freedom, yaw, pitch, and roll.
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Kshirsagar and Thalmann [16] proposed a syllable-based approach, where captured facial motions are categorized into syllable motions and the new speech animation is achieved by concatenating syllable motions optimally chosen from the syllable motion database.
The mobile terminal positioning problem is categorized into three different types according to the availability of (1) initial accurate location information and (2) motion measurement data.
CFS is categorized aa filter.
The site is categorized.
Andy is categorized as a data archer.
It is categorized as a negative emotion.
The track is categorized as a ballad.
Therefore, it is categorized as ballad.
Motion prediction approaches were categorized based on their degree of abstraction.
Vision-based motion detection methods can be categorized into three major classes, i.e., temporal difference, background modeling and subtraction, and optical flow.
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