Example-Based Realistic Terrain Generation

  • Qicheng Li
  • Guoping Wang
  • Feng Zhou
  • Xiaohui Tang
  • Kun Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4282)


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.


Support Vector Machine Digital Elevation Model Geographic Information System Central Moment Terrain Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Qicheng Li
    • 1
  • Guoping Wang
    • 1
  • Feng Zhou
    • 1
  • Xiaohui Tang
    • 1
  • Kun Yang
    • 1
  1. 1.Dep. of Computer Science & TechnologyPeking UniversityBeijingChina

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