Abstract
We have developed a fast generation system for personalized 3D face model and plan to apply it in network 3D games. This system uses one video camera to capture player’s frontal face image for 3D modeling and dose not need calibration and plentiful manual tuning. The 3D face model in games is represented by a 3D geometry mesh and a 2D texture image. The personalized geometry mesh is obtained by deforming an original mesh with the relative positions of the player’s facial features, which are automatically detected from the frontal image. The relevant texture image is also obtained from the same image. In order to save storage space and network bandwidth, only the feature data and texture data from each player are sent to the game server and then to other clients. Finally, players can see their own faces in multiplayer games.
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References
Abrantes, G.A., Pereira, F.: MPEG-4 Facial Animation Technology: Survey, Implementation, and Results. IEEE Trans. on Circuits and Systems for Video Technology 9(2), 290–305 (1999)
Sun, W., Hilton, A., Smith, R., Illingworth, J.: Building Layered Animation Models from Captured Data. In: Eurographics Workshop on Computer Animation, pp. 145–154 (1999)
Hilton, A., Inningworth, J.: Geometric Fusion for a Hand-held 3-D Sensor. Machine Vision Applications 12(1), 44–51 (2000)
Parke, F.I., Waters, K.: Computer Facial Animation. A.K. Peters, Wellesley (1996)
Akimoto, T., Suenaga, Y., Wallace, R.S.: Automatic Creation of 3-D Facial Models. IEEE Computer Graphics & App., 16–22 (1993)
Liu, Z., Zhang, Z., Jacobs, C., Cohen, M.: Rapid modeling of animated faces from video. Journal of Visualization and Computer Animation 12(4), 227–240 (2001)
Lavagetto, F., Pockaj, R.: The Facial Animation Engine: Toward A High-Level Interface for the Design of MPEG-4 Compliant Animated Faces. IEEE Transactions on Circuits and Systems for Video Technology 9(2), 277–289 (1999)
Escher, M., Thalmann, N.M.: Automatic 3-D Cloning and Real-Time Animation of a Human Face. In: Proceedings of Computer Animation, Geneva, Switzerland (1997)
Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models: Their training and application. CVGIP: Image Understanding 61, 38–59 (1995)
Schapire, R.E., Singer, Y.: Improved boosting algorithms using confidence-rated predictions. In: Proceedings of the Eleventh Annual Conference on Computational Learning Theory, pp. 80–91 (1998)
Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: a statistical view of boosting. Technical report, Department of Statistics, Sequoia Hall, Stanford Univerity (1998)
Xiangsheng, H., Bin, X., Yangsheng, W.: Shape Localization by Statistical Learning in the Gabor Feature Space. In: ICSP 2004, Beijing, China (2004)
Pighin, F., Hecker, J., Lischinski, D., Szeliski, R., Salesin, D.H.: Synthesizing Realistic Facial Expressions from Photographs. Siggraph proceedings, 75–84 (1998)
Ruprecht, D., Nagel, R., Müller, H.: Spatial Free-Form Deformation with Scattered Data Interpolation Methods. Computers & Graphics 19(1), 63–71 (1995)
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© 2005 IFIP International Federation for Information Processing
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Zeng, X., Yao, J., Zhang, M., Wang, Y. (2005). A Video Based Personalized Face Model Generation Approach for Network 3D Games. In: Kishino, F., Kitamura, Y., Kato, H., Nagata, N. (eds) Entertainment Computing - ICEC 2005. ICEC 2005. Lecture Notes in Computer Science, vol 3711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558651_23
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DOI: https://doi.org/10.1007/11558651_23
Publisher Name: Springer, Berlin, Heidelberg
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