Abstract
In this paper, a new approach to terrain generation based on terrain examples is proposed. Existing procedural algorithms for generation of terrain have several shortcomings. The most popular approach, fractal-based terrain generation, is efficient, but is difficult for users to control. In this paper, we provide a semiautomatic method of terrain generation that uses a four-process genetic algorithm approach to produce a variety of terrain types using only intuitive user inputs. We allow users to specify a rough sketch of terrain silhouette map, retrieve terrain examples based on support vector machine (SVM) from the terrain dataset, cut a region from the terrain examples and fill in the terrain silhouette map. We also generate a photorealistic texture based on the aerial or satellite images. Consequently, we generate the terrain which has both geometrical data and texture data and provide a balance between user input and real-world data capture unmatched.
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© 2006 Springer-Verlag Berlin Heidelberg
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Li, Q., Wang, G., Zhou, F., Tang, X., Yang, K. (2006). Example-Based Realistic Terrain Generation. In: Pan, Z., Cheok, A., Haller, M., Lau, R.W.H., Saito, H., Liang, R. (eds) Advances in Artificial Reality and Tele-Existence. ICAT 2006. Lecture Notes in Computer Science, vol 4282. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11941354_84
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DOI: https://doi.org/10.1007/11941354_84
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49776-9
Online ISBN: 978-3-540-49779-0
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