Graduate Thesis Or Dissertation
 

Behavior graphs for data-driven animation of 3d characters

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3r074x93v

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  • In this dissertation, we present a user-in-the-loop method for the design of an interactive motion data structure that benefits from the advantages of both motion graphs and blend-based techniques. Our novel approach automatically analyzes a traditional motion graph built from labeled motion clips. The result is a more condensed, coarser graph which we call the Behavior Finite State Machine (BFSM). Each node of the BFSM represents a single behavior that may be continuously parameterized. An edge in the BFSM represents a valid transition between two behaviors, with the transition probability indicating the likelihood of such a transition. Our focus is on user-centered, semi-automatic methods for aiding in the construction and editing of such machines. Since the transitions and parameterized behavior spaces are based on constructing time-warps between motion clips, we present an intuitive process that allows the user to construct these data structures necessary for BFSM design. We present the results of our approach using two dynamic interactive examples, locomotion and martial arts. We demonstrate the use of the BFSM to generate controllable motion in real-time, to synthesize motion offline using A* search, and to generate autonomous character navigation with obstacle avoidance in a virtual environment. We conclude with a discussion on the strengths and weaknesses of our approach.
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