Construction and optimal search of interpolated motion graphs

Many compelling applications would become feasible if novice users had the ability to synthesize high quality human motion based only on a simple sketch and a few easily specified constraints. We approach this problem by representing the desired motion as an interpolation of two time-scaled paths through a motion graph. The graph is constructed to support interpolation and pruned for efficient search. We use an anytime version of A* search to find a globally optimal solution in this graph that satisfies the user's specification. Our approach retains the natural transitions of motion graphs and the ability to synthesize physically realistic variations provided by interpolation. We demonstrate the power of this approach by synthesizing optimal or near optimal motions that include a variety of behaviors in a single motion.

[1]  Judea Pearl,et al.  Heuristics : intelligent search strategies for computer problem solving , 1984 .

[2]  Andrew P. Witkin,et al.  Spacetime constraints , 1988, SIGGRAPH.

[3]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[4]  Ken Perlin,et al.  Real Time Responsive Animation with Personality , 1995, IEEE Trans. Vis. Comput. Graph..

[5]  Shang Guo,et al.  A high-level control mechanism for human locomotion based on parametric frame space interpolation , 1996 .

[6]  J. Hahn,et al.  Interpolation Synthesis of Articulated Figure Motion , 1997, IEEE Computer Graphics and Applications.

[7]  Michael F. Cohen,et al.  Verbs and Adverbs: Multidimensional Motion Interpolation , 1998, IEEE Computer Graphics and Applications.

[8]  Harry Shum,et al.  Motion texture: a two-level statistical model for character motion synthesis , 2002, ACM Trans. Graph..

[9]  Jessica K. Hodgins,et al.  Interactive control of avatars animated with human motion data , 2002, SIGGRAPH.

[10]  Christoph Bregler,et al.  Motion capture assisted animation: texturing and synthesis , 2002, ACM Trans. Graph..

[11]  Okan Arikan,et al.  Interactive motion generation from examples , 2002, ACM Trans. Graph..

[12]  Sung Yong Shin,et al.  On-line locomotion generation based on motion blending , 2002, SCA '02.

[13]  Nancy S. Pollard,et al.  Efficient synthesis of physically valid human motion , 2003, ACM Trans. Graph..

[14]  David A. Forsyth,et al.  Motion synthesis from annotations , 2003, ACM Trans. Graph..

[15]  Lucas Kovar,et al.  Flexible automatic motion blending with registration curves , 2003, SCA '03.

[16]  Sebastian Thrun,et al.  ARA*: Anytime A* with Provable Bounds on Sub-Optimality , 2003, NIPS.

[17]  Sung Yong Shin,et al.  Planning biped locomotion using motion capture data and probabilistic roadmaps , 2003, TOGS.

[18]  Nancy S. Pollard,et al.  Evaluating motion graphs for character navigation , 2004, SCA '04.

[19]  Jessica K. Hodgins,et al.  Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces , 2004, ACM Trans. Graph..

[20]  C. Karen Liu,et al.  Momentum-based parameterization of dynamic character motion , 2004, SCA '04.

[21]  John Hart,et al.  ACM Transactions on Graphics , 2004, SIGGRAPH 2004.

[22]  Lucas Kovar,et al.  Automated extraction and parameterization of motions in large data sets , 2004, ACM Trans. Graph..

[23]  Jehee Lee,et al.  Precomputing avatar behavior from human motion data , 2004, SCA '04.

[24]  Sung Yong Shin,et al.  On‐line motion blending for real‐time locomotion generation , 2004, Comput. Animat. Virtual Worlds.

[25]  Jessica K. Hodgins,et al.  Analyzing the physical correctness of interpolated human motion , 2005, SCA '05.

[26]  Manfred Lau,et al.  Behavior planning for character animation , 2005, SCA '05.

[27]  Eric N. Mortensen,et al.  Controllable real-time locomotion using mobility maps , 2005, Graphics Interface.

[28]  Lucas Kovar,et al.  Fast and accurate goal-directed motion synthesis for crowds , 2005, SCA '05.

[29]  Taesoo Kwon,et al.  Motion modeling for on-line locomotion synthesis , 2005, SCA '05.

[30]  Jovan Popovic,et al.  Adaptation of performed ballistic motion , 2005, TOGS.

[31]  Hyun Joon Shin,et al.  Fat graphs: constructing an interactive character with continuous controls , 2006, SCA '06.

[32]  Manfred Lau,et al.  Precomputed search trees: planning for interactive goal-driven animation , 2006, SCA '06.

[33]  David A. Forsyth,et al.  Knowing when to put your foot down , 2006, I3D '06.

[34]  Ronan Boulic,et al.  Robust kinematic constraint detection for motion data , 2006, SCA '06.

[35]  David A. Forsyth,et al.  Quick transitions with cached multi-way blends , 2007, SI3D.

[36]  J. Hodgins,et al.  Construction and optimal search of interpolated motion graphs , 2007, SIGGRAPH 2007.

[37]  Michael Gleicher,et al.  Parametric motion graphs , 2007, SI3D.

[38]  Hyun Joon Shin,et al.  Snap-together motion: assembling run-time animations , 2003, SIGGRAPH '08.

[39]  Lucas Kovar,et al.  Motion Graphs , 2002, ACM Trans. Graph..