Um Método Automático de Geração de Terrenos 3D para Jogos Low-poly
Resumo
A criação de mapas 3D tem um papel fundamental no processo de construção de um jogo. Essa etapa costuma levar um tempo considerável para ser executada, pois ajustes no formato do terreno são feitos manualmente pelo designer gráfico, que perde um tempo considerável definindo o melhor formato e estrutura para o mapa criado. Nesse trabalho, nós apresentamos um método para geração automática de terrenos 3D low-poly a partir de imagens, que embora não sejam de propósito geral, pode auxiliar o designer gráfico no desenvolvimento da estrutura de um terreno através de desenhos. A principal contribuição desse trabalho é um método que acelera o processo de construção de mapas 3D.
Palavras-chave:
Computação Gráfica, Processamento Digital de Imagens, Simulação, Visão Computacional
Referências
Alsabti, K., Ranka, S., and Singh, V. (1997). An efcient k-means clustering algorithm.
Amato, A. (2017). Procedural content generation in the game industry. In Game Dynamics, pages 15–25. Springer.
Angel, E., Shreiner, D., et al. (2012). Interactive computer graphics: a top-down appro ach with shader-based OpenGL. Boston: Addison-Wesley,.
Blinn, J. F. (1977). Models of light reection for computer synthesized pictures. In Proceedings of the 4th annual conference on Computer graphics and interactive techniques, pages 192–198.
Brito, A. (2007). Blender 3D. Novatec.
De Carli, D. M., Bevilacqua, F., Pozzer, C. T., and Cordeiro dOrnellas, M. (2011). A survey of procedural content generation techniques suitable to game development. In 2011 Brazilian Symposium on Games and Digital Entertainment, pages 26–35. IEEE.
Fletcher, M. and Liebscher, R. (2005). Pyopengl–the python opengl binding. URL: http://pyopengl.sourceforge. net.
Hung, Y.-P., Chen, C.-S., Hung, K.-C., Chen, Y.-S., and Fuh, C.-S. (1998). Multipass hierarchical stereo matching for generation of digital terrain models from aerial images. Machine Vision and Applications, 10(5-6):280–291.
Lutz, M. (2001). Programming python. ”O’Reilly Media, Inc.”.
Marchand, A. and Hennig-Thurau, T. (2013). Value creation in the video game industry: Industry economics, consumer benets, and research opportunities. Journal of Interactive Marketing, 27(3):141–157.
Parberry, I. (2014). Designer worlds: Procedural generation of innite terrain from real world elevation data. Journal of Computer Graphics Techniques, 3(1).
Perlin, K. (1985). An image synthesizer. ACM Siggraph Computer Graphics, 19(3):287–296.
Radford, A., Metz, L., and Chintala, S. (2015). Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434.
Shreiner, D., Sellers, G., Kessenich, J., and Licea-Kane, B. (2013). OpenGL programming guide: The Ofcial guide to learning OpenGL, version 4.3. Addison-Wesley.
Amato, A. (2017). Procedural content generation in the game industry. In Game Dynamics, pages 15–25. Springer.
Angel, E., Shreiner, D., et al. (2012). Interactive computer graphics: a top-down appro ach with shader-based OpenGL. Boston: Addison-Wesley,.
Blinn, J. F. (1977). Models of light reection for computer synthesized pictures. In Proceedings of the 4th annual conference on Computer graphics and interactive techniques, pages 192–198.
Brito, A. (2007). Blender 3D. Novatec.
De Carli, D. M., Bevilacqua, F., Pozzer, C. T., and Cordeiro dOrnellas, M. (2011). A survey of procedural content generation techniques suitable to game development. In 2011 Brazilian Symposium on Games and Digital Entertainment, pages 26–35. IEEE.
Fletcher, M. and Liebscher, R. (2005). Pyopengl–the python opengl binding. URL: http://pyopengl.sourceforge. net.
Hung, Y.-P., Chen, C.-S., Hung, K.-C., Chen, Y.-S., and Fuh, C.-S. (1998). Multipass hierarchical stereo matching for generation of digital terrain models from aerial images. Machine Vision and Applications, 10(5-6):280–291.
Lutz, M. (2001). Programming python. ”O’Reilly Media, Inc.”.
Marchand, A. and Hennig-Thurau, T. (2013). Value creation in the video game industry: Industry economics, consumer benets, and research opportunities. Journal of Interactive Marketing, 27(3):141–157.
Parberry, I. (2014). Designer worlds: Procedural generation of innite terrain from real world elevation data. Journal of Computer Graphics Techniques, 3(1).
Perlin, K. (1985). An image synthesizer. ACM Siggraph Computer Graphics, 19(3):287–296.
Radford, A., Metz, L., and Chintala, S. (2015). Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434.
Shreiner, D., Sellers, G., Kessenich, J., and Licea-Kane, B. (2013). OpenGL programming guide: The Ofcial guide to learning OpenGL, version 4.3. Addison-Wesley.
Publicado
26/10/2020
Como Citar
DA CONCEIÇÃO, Jam Sávio; DOS SANTOS, Jadson Lúcio; CAVALCANTE, Rodolfo.
Um Método Automático de Geração de Terrenos 3D para Jogos Low-poly. In: ESCOLA REGIONAL DE COMPUTAÇÃO BAHIA, ALAGOAS E SERGIPE (ERBASE), 20. , 2020, Arapiraca-AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 99-108.
