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		<doi>10.1109/SIBGRAPI51738.2020.00013</doi>
		<citationkey>AntonitschMussFigu:2020:StBeOr</citationkey>
		<title>Towards a Legion of Virtual Humans: Steering Behaviors and Organic Visualization</title>
		<format>On-line</format>
		<year>2020</year>
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		<author>Antonitsch, André da Silva,</author>
		<author>Musse, Soraia Raupp,</author>
		<author>Figueiredo, Luiz Henrique de,</author>
		<affiliation>Pontifícia Universidade Católica do Rio Grande do Sul</affiliation>
		<affiliation>Pontifícia Universidade Católica do Rio Grande do Sul</affiliation>
		<affiliation>Instituto de Matemática Pura e Aplicada</affiliation>
		<editor>Musse, Soraia Raupp,</editor>
		<editor>Cesar Junior, Roberto Marcondes,</editor>
		<editor>Pelechano, Nuria,</editor>
		<editor>Wang, Zhangyang (Atlas),</editor>
		<e-mailaddress>andre.antonitsch@acad.pucrs.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 33 (SIBGRAPI)</conferencename>
		<conferencelocation>Porto de Galinhas (virtual)</conferencelocation>
		<date>7-10 Nov. 2020</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
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		<keywords>virtual human crowds, blobby models.</keywords>
		<abstract>Many studies have been done to control virtual humans and crowds. Navigation, split, merge, and collision avoidance are examples of what has been done in such areas when simulating crowds of individuals. This paper explores the macroscopic crowds' concept and seeks to solve two main issues: macroscopic crowd control and visualization. In particular, we are interested in providing steering behaviors applied to macroscopic models of crowds, in this case, called Legions of people, which are an abstraction for a vast amount of people. To provide the steering behaviors, we propose a multi-level control of such structures that can represent less or more people, in an emergent way. We also propose a new organic visualization of macroscopic and huge crowds based on blobby models.</abstract>
		<language>en</language>
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