Abstract
The design of data structures is one of the most crucial problems when developing visual information processing systems. A well designed data structure and its processing algorithm should be developed to comply with the required functionality of each application. In this chapter, we present a novel data representation method for 3D video named behavior unit model. Intuitively speaking, a behavior unit is defined as a partial interval of a 3D video data stream in which an object performs a simple action such as stand-up, sit down, etc. Once a 3D video data stream is partitioned into a set of behavior units, we can realize content-based processing methods of 3D video data using the behavior units as atomic data entities: editing, summarization, and semantic description of a given 3D video data. The chapter introduces the topology dictionary, which is a general abstraction method for data stream of geometrical objects, to achieve the behavior unit-based representation of 3D video.
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Notes
- 1.
Raptor model provided courtesy of INRIA by the AIM@SHAPE Shape Repository.
- 2.
A graph branch is a set of successive nodes linked two by two by a single edge. Two branches match together when all the nodes belonging to them match together.
- 3.
A neighbor is a node belonging to an adjacent surface region. Neighboring nodes are connected by a Reeb graph edge at the same resolution level.
References
Arikan, O., Forsyth, D.A.: Interactive motion generation from examples. ACM Trans. Graph. 21(3), 483–490 (2002)
Sharf, A., Lewiner, T., Shamir, A., Kobbelt, L.: On-the-fly curve-skeleton computation for 3D shapes. Comput. Graph. Forum 26(3), 323–328 (2007)
Baran, I., Popovic, J.: Automatic rigging and animation of 3D characters. ACM Trans. Graph. 26(3), 27 (2007)
Cornea, N., Silver, D., Yuan, X., Balasubramanian, R.: Computing hierarchical curveskeletons of 3D objects. Vis. Comput. 21(11), 945–955 (2005)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. Math. 1, 269–271 (1959)
Fulkerson, B., Vedaldi, A., Soatto, S.: Localizing objects with smart dictionaries. In: Proc. of European Conference on Computer Vision, vol. 1, pp. 179–192 (2008)
Gray, R.M., Gersho, A.: Vector Quantization and Signal Compression. Kluwer Academic, Norwell (1992)
Hilaga, M., Shinagawa, Y., Kohmura, T., Kunii, T.L.: Topology matching for fully automatic similarity estimation of 3D shapes. In: Proc. of ACM SIGGRAPH, pp. 203–212 (2001)
Huang, P., Hilton, A., Starck, J.: Shape similarity for 3D video sequences of people. Int. J. Comput. Vis. 89(2–3), 362–381 (2010)
Huang, P., Tung, T., Nobuhara, S., Hilton, A., Matsuyama, T.: Comparison of skeleton and non-skeleton shape descriptors for 3D video. In: Proc. of International Symposium on 3D Data Processing, Visualization and Transmission (2010)
James, D.L., Twigg, C.D.: Skinning mesh animations. ACM Trans. Graph. 24(3) (2005)
Carranza, J., Theobalt, C., Magnor, M., Seidel, H.-P.: Free-viewpoint video of human actors. ACM Trans. Graph. 22(3), 569–577 (2003)
Lee, J., Chai, J., Reitsman, P.S.A., Hodgins, J.K., Pollard, N.S.: Interactive control of avatars animated with human motion data. ACM Trans. Graph. 21(3), 491–500 (2002)
Kho, Y., Garland, M.: Sketching mesh deformations. ACM Trans. Graph. 24(3), 934 (2005)
Koenderink, J.: Solid Shape. MIT Press, Cambridge (1990)
Kovar, L., Gleicher, M., Pighin, F.H.: Motion graphs. ACM Trans. Graph. 21(3), 473–482 (2002)
Palagyi, K., Kuba, A.: A parallel 3D 12-subiteration thinning algorithm. Graph. Models Image Process. 61(4), 199–221 (1999)
Molina-Tanco, L., Hilton, A.: Realistic synthesis of novel human movements from a database of motion capture examples. In: IEEE Workshop on Human Motion (2000)
Mizuguchi, T., Buchanan, J., Calvert, T.: Data driven motion transitions for interactive games. In: Eurographics Short Presentations (2001)
Morse, M.: The Calculus of Variations in the Large. Am. Mathematical Society Colloquium Publication, vol. 18. AMS, New York (1934)
Ngo, C.-W., Ma, Y.-F., Zhang, H.-J.: Video summarization and scene detection by graph modeling. IEEE Trans. Circuits Syst. Video Technol. 15(2), 296–305 (2005)
Paquet, E., Rioux, M.: A content-based search engine for VRML databases. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 541–546 (1998)
Park, S.I., Hodgins, J.K.: Capturing and animating skin deformation in human motion. ACM Trans. Graph. 25(3), 881–889 (2006)
Pascucci, V., Scorzelli, G., Bremer, P.-T., Mascarenhas, A.: Robust on-line computation of Reeb graphs: Simplicity and speed. ACM Trans. Graph. 26(3), 58 (2007)
Pearson, K.: On lines and planes of closest fit to systems of points in space. Philos. Mag. 2(6), 559–572 (1901)
Reeb, G.: On the singular points of a completely integrable Pfaff form or of a numerical function. C. R. Acad. Sci. Paris 222, 847–849 (1946)
Samet, H.: Foundations of Multidimensional Metric Data Structures. Morgan Kaufmann, San Mateo (2006)
Schödl, A., Szeliski, R., Salesin, D., Essa, I.: Video textures. In: Proc. of ACM SIGGRAPH, pp. 489–498 (2000)
Shotton, J., Johnson, M., Cipolla, R.: Semantic texton forests for image categorization and segmentation. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (2008)
Sorkine, O., Alexa, M.: As-rigid-as-possible surface modeling. In: Proc. 5th Eurographics Symposium on Geometry Processing, pp. 109–116 (2007)
Starck, J., Hilton, A.: Surface capture for performance-based animation. IEEE Comput. Graph. Appl. (2007)
Tung, T., Matsuyama, T.: Topology dictionary with Markov model for 3D video content-based skimming and description. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (2009)
Tung, T.: An implementation of the augmented multiresolution Reeb graphs (aMRG) for shape similarity computation of 3D models. http://tonytung.org/
Tung, T., Matsuyama, T.: Topology dictionary for 3D video understanding. IEEE Trans. Pattern Anal. Mach. Intell. (2012)
Tung, T., Schmitt, F.: The augmented multiresolution Reeb graph approach for content-based retrieval of 3D shapes. Int. J. Shape Model. 11(1), 91–120 (2005)
Tung, T., Schmitt, F., Matsuyama, T.: Topology matching for 3D video compression. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (2007)
Winn, J., Criminisi, A., Minka, T.: Object categorization by learned universal visual dictionary. In: Proc. of International Conference on Computer Vision, vol. 2, pp. 1800–1807 (2005)
Yeung, M., Yeo, B.L.: Segmentation of video by clustering and graph analysis. Comput. Vis. Image Underst. 71(1), 94–109 (1998)
Zaharescu, A., Boyer, E., Horaud, R.: Topology-adaptive mesh deformation for surface evolution, morphing, and multi-view reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 823–837 (2011)
Zaharia, T., Prêteux, F.: Indexation de maillages 3D par descripteurs de forme. In: Proc. Reconnaissance des Formes et Intelligence Artificielle (RFIA), pp. 48–57 (2002)
Ziv, J., Lempen, A.: A universal algorithm for sequential data compression. IEEE Trans. Inf. Theory 23(3), 337–343 (1977)
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Matsuyama, T., Nobuhara, S., Takai, T., Tung, T. (2012). Behavior Unit Model for Content-Based Representation and Edition of 3D Video. In: 3D Video and Its Applications. Springer, London. https://doi.org/10.1007/978-1-4471-4120-4_8
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DOI: https://doi.org/10.1007/978-1-4471-4120-4_8
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