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Motion graphs have gained popularity in recent years as a means for re-using motion capture data by connecting previously unrelated segments of a recorded library. Current techniques for controlling movement of a character via motion graphs have largely focused on path planning which is difficult due to the density of connections found on the graph. We introduce "state-annotated motion graphs," a novel technique which allows high-level control of character behavior by using a dualdoi:10.1145/1315184.1315195 dblp:conf/vrst/ChiuZW07 fatcat:ksrp5ay6tvgono46higv6ivrta