Yasuhiko Sakamoto
Shigeru Kuriyama
ABSTRACT
Recent proliferation of motion capture systems enables motion data to be saved as an archive system, and the data are usually extracted by selecting an appropriate file by its name or annotation explaining the content of motions. Such semantic-based retrieval, however, is not suited to unstructured files that include many types of elemental motions, due to the difficulty in giving comprehensible annotations. Moreover, expected motion clips are often included as a part of entire sequences, and the data therefore should be manually clipped using some authoring tools.
This paper proposes an image-based user interface for retrieving motion data using a self-organizing map for supplying recognizable icons of postures. The postures are used as keys for retrieval, and the desirable segments of the motion data can be accurately extracted by specifying and ending postures. The number of possible motion segments is flexibly controlled by changing the scope of postures used as the keys.
Supplemental Material
- {AFO03} Arikan O., Forsyth D. A., O'Brien J. F.: Motion synthesis from annotations. ACM Transactions on Graphics 22, 3 (2003), 402--408. Google Scholar
Digital Library
- {BH00} Brand M., Hertzmann A.: Style machines. In Proceedings of ACM SIGGRAPH 2000 (2000), pp. 183--192. Google ScholarDigital Library
- {CMS99} Card S. K., MacKinlay J. D., Shneiderman B.: Readings in Information Visualization Using Vision to Think. Morgan Kaufmann Publishers, 1999. Google ScholarDigital Library
- {DAC*03} Davis J., Agrawala M., Chuang E., Popovic Z., Salesin D.: A sketching interface for articulated figure animation. In Symposium on Computer Animation 03 (2003), pp. 320--328. Google ScholarDigital Library
- {dOL03} De Olivera M. C. F., Levkowitz H.: From visual data exploration to visual data mining: A survey. IEEE Transaction on Visualization and Computer Graphics 9, 3 (2003), 378--394. Google ScholarDigital Library
- {EP02} Elliman D., Pulido J.: Visualizing ontology components through self-organizing maps. In Proc. of Sixth International Conference on Information Visualization (IV'02) (2002), pp. 434--438.Google ScholarCross Ref
- {HB92} Hummel J. E., Biederman I.: Dynamic binding in a neural network for shape recognition. Psychological Review 99, 3 (1992), 480--517.Google ScholarCross Ref
- {HMM00} Herman I., Melancon G., Marshall M. S.: Graph visualization and navigation in information visualization: A survey. IEEE Transactions on Visualization and Computer Graphics 6, 1 (2000), 24--43. Google ScholarDigital Library
- {ITW01} Irani P., Tingley M., Ware C.: Using perceptual syntax to enhance semantic content in diagrams. IEEE Computer Graphics & Applications 21, 5 (2001), 76--85. Google ScholarDigital Library
- {KG04} Kovar L., Gleicher M.: Automated extraction and parameterization of motions in large data set. ACM Transactions on Graphics (2004). Google ScholarDigital Library
- {KGP02} Kovar L., Gleicher M., Pighin F.: Motion graphs. ACM Transactions on Graphics 21, 3 (2002), 473--482. Google ScholarDigital Library
- {Koh88} Kohonen T.: Self-organized formation of topologically correct feature maps. Biological Cybernetics 43 (1988), 59--69.Google Scholar
- {Koh90} Kohonen T.: The self-organizing map. Proceedings IEEE 78, 9 (1990), 1464--1480.Google Scholar
- {Koh01} Kohonen T.: Self-Organizing Maps. Springer, 2001. Google ScholarDigital Library
- {LCR*02} Lee J., Chai J., Reitsma P. S. A., Hodgins J. K., Pollard N. S.: Interactive control of avatars animated with human motion data. ACM Transactions on Graphics 21, 3 (2002), 491--500. Google ScholarDigital Library
- {Mac67} MacQueen J.: Some methods for classification and analysis of multivariate data. In 5th Berkeley Symposium (1967), vol. 1, pp. 281--297.Google Scholar
- {Mea97} Marks J., et al.: Design galleries: A general approach to setting parameters for computer graphics and animation. In Proceedings of SIGGRAPH 97 (1997), pp. 389--400. Google ScholarDigital Library
- {RCB98} Rose C., Cohen M. F., Bodenheimer B.: Verbs and adverbs: Multidimensional motion interpolation. IEEE Computer Graphics & Applications 18, 5 (1998), 32--40. Google ScholarDigital Library
- {RI96} Rushall D., Ilgen M.: Depict: Documents evaluated as pictures. visualizing information using context vectors and self-organizing maps. In IEEE Symposium on Information Visualization (INFOVIS'96) (1996), pp. 100--107. Google ScholarDigital Library
- {RS00} Roweis S. T., Saul L. K.: Nonlinear dimensionality reduction by locally linear embedding. SCIENCE 290, 22 (2000), 2323--2326.Google ScholarCross Ref
- {Spe01} Spence R.: Information Visualization. Addison-Wesley, 2001.Google Scholar
- {TdSL00} Tenenbaum J. B., De Silva V., Langford J. C.: A global geometric framework for nonlinear dimensionality reduction. SCIENCE 290, 22 (2000), 2319--2322.Google Scholar
- {TH00} Tanco L. M., Hilton A.: Realistic synthesis of novel human movements from a database of motion capture examples. In Workshop on Human Motion (HUMO 2000) (2000), pp. 137--142. Google ScholarDigital Library
- {UAT95} Unuma M., Anjyo K., Takeuchi R.: Fourier principles for emotion-based human figure animation. In Proceedings of SIGGRAPH 95 (1995), pp. 91--96. Google ScholarDigital Library
- {WH97} Wiley D., Hahn J.: Interpolation synthesis of articulated figure motion. IEEE Computer Graphics & Applications 17, 6 (1997), 39--45. Google ScholarDigital Library
Index Terms
- Motion map: image-based retrieval and segmentation of motion data
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