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		<citationkey>CruzVelh:2015:HiTeLa</citationkey>
		<title>High-Level Techniques for Landscape Creation</title>
		<format>On-line</format>
		<year>2015</year>
		<secondarytype>Doctoral Work</secondarytype>
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		<author>Cruz, Leandro,</author>
		<author>Velho, Luiz,</author>
		<affiliation>VISGRAF Lab - Instituto Nacional de Matemática Pura e Aplicada</affiliation>
		<affiliation>VISGRAF Lab - Instituto Nacional de Matemática Pura e Aplicada</affiliation>
		<editor>Segundo, Maurício Pamplona,</editor>
		<editor>Faria, Fabio Augusto,</editor>
		<e-mailaddress>lcruz@impa.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 28 (SIBGRAPI)</conferencename>
		<conferencelocation>Salvador, BA, Brazil</conferencelocation>
		<date>26-29 Aug. 2015</date>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Master's or Doctoral Work</tertiarytype>
		<transferableflag>1</transferableflag>
		<keywords>Landscape Creation, Terrain Synthesis.</keywords>
		<abstract>A complete solution for creating an entire planet by combining different types of elements from an intuitive specification is still an open problem. High-level techniques are at the core of the solution for this issue. In this context, our work aims to contribute for the development of high-level techniques for landscape creation by the proposal of two approaches. The first deals with the manipulation of the position of landscape elements (according to some criteria), and the second is related to the generation of terrains from two new data-driven methods. In particular, we introduced a flexible method for resizing a landscape specification keeping the overall appearance. It is based on the insertion and removal of objects followed by scene adjustment (enlargement or shrinking). Furthermore, we introduced two data-driven techniques for terrain synthesis. They are developed over the same intuitive control approach, and they take advantage of the geometric nature of the data for improving the synthesis. The first technique is a patch-based algorithm, with new optimization structures for patch choice, and a new patch insertion approach (both based on the geometric nature of the data). The second is a pixel-based method, based on a graph of exemplars in multiresolution.</abstract>
		<language>en</language>
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