ABSTRACT
The widespread availability of high-quality motion capture data and the maturity of solutions to animate virtual characters has paved the way for the next generation of interactive virtual worlds exhibiting intricate interactions between characters and the environments they inhabit. However, current motion synthesis techniques have not been designed to scale with complex environments and contact-rich motions, requiring environment designers to manually embed motion semantics in the environment geometry in order to address online motion synthesis. This paper presents an automated approach for analyzing both motions and environments in order to represent the different ways in which an environment can afford a character to move. We extract the salient features that characterize the contact-rich motion repertoire of a character and detect valid transitions in the environment where each of these motions may be possible, along with additional semantics that inform which surfaces of the environment the character may use for support during the motion. The precomputed motion semantics can be easily integrated into standard navigation and animation pipelines in order to greatly enhance the motion capabilities of virtual characters. The computational efficiency of our approach enables two additional applications. Environment designers can interactively design new environments and get instant feedback on how characters may potentially interact, which can be used for iterative modeling and refinement. End users can dynamically edit virtual worlds and characters will automatically accommodate the changes in the environment in their movement strategies.
Supplemental Material
- Al-Asqhar, R. A., Komura, T., and Choi, M. G. 2013. Relationship descriptors for interactive motion adaptation. In ACM SIGGRAPH/EG SCA, ACM, 45--53. Google ScholarDigital Library
- Arikan, O., and Forsyth, D. A. 2002. Interactive motion generation from examples. ACM Trans. Graph. 21, 3 (July), 483--490. Google ScholarDigital Library
- Berseth, G., Usman, M., Haworth, B., Kapadia, M., and Faloutsos, P. 2015. Environment optimization for crowd evacuation. CAVW 26, 3-4, 377--386. Google ScholarDigital Library
- Choi, M. G., Lee, J., and Shin, S. Y. 2003. Planning biped locomotion using motion capture data and probabilistic roadmaps. ACM Trans. Graph. 22, 2 (Apr.), 182--203. Google ScholarDigital Library
- Choi, M. G., Kim, M., Hyun, K., and Lee, J. 2011. Deformable Motion: Squeezing into Cluttered Environments. Comput. Graph. Forum 30, 2, 445--453.Google ScholarCross Ref
- Coros, S., Beaudoin, P., and van de Panne, M. 2009. Robust task-based control policies for physics-based characters. ACM Trans. Graph. 28, 5 (Dec.), 170:1--170:9. Google ScholarDigital Library
- Fang, A. C., and Pollard, N. S. 2003. Efficient synthesis of physically valid human motion. In ACM SIGGRAPH, ACM, 417--426. Google ScholarDigital Library
- Hart, P., Nilsson, N., and Raphael, B. 1968. A formal basis for the heuristic determination of minimum cost paths. Systems Science and Cybernetics, IEEE Transactions on 4, 2 (July), 100--107.Google Scholar
- Hauser, K., Bretl, T., and Latombe, J.-C. 2005. Non-gaited humanoid locomotion planning. In Humanoid Robots, 2005 5th IEEE-RAS International Conference on, 7--12.Google Scholar
- Heck, R., and Gleicher, M. 2007. Parametric motion graphs. In ACM SIGGRAPH I3D, 129--136. Google ScholarDigital Library
- Ho, E. S. L., and Komura, T. 2009. Character motion synthesis by topology coordinates. In CGF, vol. 28.Google Scholar
- Hudson, T. C., Lin, M. C., Cohen, J., Gottschalk, S., and Manocha, D. 1997. V-collide: Accelerated collision detection for vrml. In VRML, ACM, 117--ff. Google ScholarDigital Library
- Johansen, R. 2009. Automated semi-procedural animation for character locomotion. PhD thesis.Google Scholar
- Kalisiak, M., and van de Panne, M. 2001. A grasp-based motion planning algorithm for character animation. Journal of Visualization and Computer Animation 12, 3, 117--129.Google ScholarCross Ref
- Kallmann, M., and Kapadia, M. 2014. Navigation meshes and real-time dynamic planning for virtual worlds. In ACM SIGGRAPH 2014 Courses, ACM, New York, NY, USA, SIGGRAPH '14, 3:1--3:81. Google ScholarDigital Library
- Kang, C., and Lee, S.-H. 2014. Environment-adaptive contact poses for virtual characters. Computer Graphics Forum 33, 7, 1--10. Google ScholarDigital Library
- Kapadia, M., Chiang, I.-k., Thomas, T., Badler, N. I., and Kider, Jr., J. T. 2013. Efficient motion retrieval in large motion databases. In ACM SIGGRAPH I3D, ACM, 19--28. Google ScholarDigital Library
- Kim, M., Hwang, Y., Hyun, K., and Lee, J. 2012. Tiling motion patches. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation, Eurographics Association, Aire-la-Ville, Switzerland, Switzerland, SCA '12, 117--126. Google ScholarDigital Library
- Kim, V. G., Chaudhuri, S., Guibas, L., and Funkhouser, T. 2014. Shape2pose: Human-centric shape analysis. ACM Trans. Graph. 33, 4 (July), 120:1--120:12. Google ScholarDigital Library
- Kovar, L., Gleicher, M., and Pighin, F. 2002. Motion graphs. In ACM SIGGRAPH, ACM, 473--482. Google ScholarDigital Library
- Lau, M., and Kuffner, J. J. 2005. Behavior planning for character animation. In ACM SIGGRAPH/EG SCA, ACM, 271--280. Google ScholarDigital Library
- Lau, M., and Kuffner, J. J. 2006. Precomputed search trees: Planning for interactive goal-driven animation. In ACM SIGGRAPH/Eurographics SCA, 299--308. Google ScholarDigital Library
- Lau, M., and Kuffner, J. 2010. Scalable precomputed search trees. In MIG, 70--81. Google ScholarDigital Library
- Lee, J., and Lee, K. H. 2004. Precomputing avatar behavior from human motion data. In ACM SIGGRAPH/EG SCA, Eurographics Association, 79--87. Google ScholarDigital Library
- Lee, J., Chai, J., Reitsma, P. S. A., Hodgins, J. K., and Pollard, N. S. 2002. Interactive control of avatars animated with human motion data. In ACM SIGGRAPH, ACM, 491--500. Google ScholarDigital Library
- Lee, Y., Lee, S. J., and Popović, Z. 2009. Compact character controllers. ACM Trans. Graph. 28, 5 (Dec.), 169:1--169:8. Google ScholarDigital Library
- Levine, S., Lee, Y., Koltun, V., and Popović, Z. 2011. Space-time planning with parameterized locomotion controllers. ACM Trans. Graph. 30, 3 (May), 23:1--23:11. Google ScholarDigital Library
- Liu, L., Yin, K., van de Panne, M., Shao, T., and Xu, W. 2010. Sampling-based contact-rich motion control. ACM Trans. Graph. 29, 4 (July), 128:1--128:10. Google ScholarDigital Library
- Liu, L., Yin, K., van de Panne, M., and Guo, B. 2012. Terrain runner: control, parameterization, composition, and planning for highly dynamic motions. ACM Trans. Graph. 31, 6 (Nov.), 154:1--154:10. Google ScholarDigital Library
- Lo, W.-Y., and Zwicker, M. 2008. Real-time planning for parameterized human motion. In ACM SIGGRAPH/Eurographics SCA, 29--38. Google ScholarDigital Library
- McCann, J., and Pollard, N. 2007. Responsive characters from motion fragments. ACM Trans. Graph. 26, 3 (July). Google ScholarDigital Library
- Memononen, M. 2014. Recast: Navigation-mesh toolset for games.Google Scholar
- Min, J., and Chai, J. 2012. Motion graphs++: A compact generative model for semantic motion analysis and synthesis. ACM Trans. Graph. 31, 6 (Nov.), 153:1--153:12. Google ScholarDigital Library
- Mordatch, I., Todorov, E., and Popović, Z. 2012. Discovery of complex behaviors through contact-invariant optimization. ACM Trans. Graph. 31, 4 (July), 43:1--43:8. Google ScholarDigital Library
- Safonova, A., and Hodgins, J. K. 2007. Construction and optimal search of interpolated motion graphs. In ACM SIGGRAPH. Google ScholarDigital Library
- Shoulson, A., Marshak, N., Kapadia, M., and Badler, N. I. 2013. ADAPT: the agent development and prototyping testbed. In ACM SIGGRAPH I3D, ACM, 9--18. Google ScholarDigital Library
- Shoulson, A., Marshak, N., Kapadia, M., and Badler, N. I. 2014. Adapt: The agent development and prototyping testbed. IEEE TVCG 20, 7 (July), 1035--1047. Google ScholarDigital Library
- Singh, S., Kapadia, M., Reinman, G., and Faloutsos, P. 2011. Footstep navigation for dynamic crowds. CAVW 22, 2-3, 151--158. Google ScholarDigital Library
- Tonneau, S., Pettré, J., and Multon, F. 2014. Task efficient contact configurations for arbitrary virtual creatures. In Graphics Interface, 9--16. Google ScholarDigital Library
- Ubisoft. 2014. Assassins creed.Google Scholar
- Xiao, J., Zhuang, Y., Yang, T., and Wu, F. 2006. An efficient keyframe extraction from motion capture data. In Advances in Computer Graphics, vol. 4035 of LNCS. Springer Berlin Heidelberg, 494--501. Google ScholarDigital Library
- Zhao, L., Normoyle, A., Khanna, S., and Safonova, A. 2009. Automatic construction of a minimum size motion graph. In ACM SIGGRAPH/EG SCA, ACM, 27--35. Google ScholarDigital Library
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