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020 _a9783031792427
_9978-3-031-79242-7
024 7 _a10.1007/978-3-031-79242-7
_2doi
050 4 _aQA1-939
072 7 _aPB
_2bicssc
072 7 _aMAT000000
_2bisacsh
072 7 _aPB
_2thema
082 0 4 _a510
_223
100 1 _aPalechano, Nuria.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981678
245 1 0 _aVirtual Crowds
_h[electronic resource] :
_bMethods, Simulation, and Control /
_cby Nuria Palechano, Norman Badler, Jan Allbeck.
250 _a1st ed. 2008.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2008.
300 _aXII, 176 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Computer Graphics and Animation,
_x1933-9003
505 0 _aIntroduction -- Crowd Simulation Methodology Survey -- Individual Differences in Crowds -- Framework (HiDAC + MACES + CAROSA) -- HiDAC: Local Motion -- MACES: Wayfinding with Communication and Roles -- CAROSA: Functional Crowds -- Initializing a Scenario -- Evaluating Crowds.
520 _aThere are many applications of computer animation and simulation where it is necessary to model virtual crowds of autonomous agents. Some of these applications include site planning, education, entertainment, training, and human factors analysis for building evacuation. Other applications include simulations of scenarios where masses of people gather, flow, and disperse, such as transportation centers, sporting events, and concerts. Most crowd simulations include only basic locomotive behaviors possibly coupled with a few stochastic actions. Our goal in this survey is to establish a baseline of techniques and requirements for simulating large-scale virtual human populations. Sometimes, these populations might be mutually engaged in a common activity such as evacuation from a building or area; other times they may be going about their individual and personal agenda of work, play, leisure, travel, or spectator. Computational methods to model one set of requirements may not mesh well withgood approaches to another. By including both crowd and individual goals and constraints into a comprehensive computational model, we expect to simulate the visual texture and contextual behaviors of groups of seemingly sentient beings. Table of Contents: Introduction / Crowd Simulation Methodology Survey / Individual Differences in Crowds / Framework (HiDAC + MACES + CAROSA) / HiDAC: Local Motion / MACES: Wayfinding with Communication and Roles / CAROSA: Functional Crowds / Initializing a Scenario / Evaluating Crowds.
650 0 _aMathematics.
_911584
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_981679
650 1 4 _aMathematics.
_911584
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
700 1 _aBadler, Norman.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981680
700 1 _aAllbeck, Jan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981681
710 2 _aSpringerLink (Online service)
_981682
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031792410
776 0 8 _iPrinted edition:
_z9783031792434
830 0 _aSynthesis Lectures on Computer Graphics and Animation,
_x1933-9003
_981683
856 4 0 _uhttps://doi.org/10.1007/978-3-031-79242-7
912 _aZDB-2-SXSC
942 _cEBK
999 _c85222
_d85222