Generating believable virtual characters using behavior capture and hidden Markov models

Richard Zhao, Duane Szafron

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We propose a method of generating natural-looking behaviors for virtual characters using a data-driven method called behavior capture. We describe the techniques for capturing trainer-generated traces, for generalizing these traces, and for using the traces to generate behaviors during game-play. Hidden Markov Models (HMMs) are used as one of the generalization techniques for behavior generation. We compared our proposed method to other existing methods by creating a scene with a set of six variations in a computer game, each using a different method for behavior generation, including our proposed method. We conducted a study in which participants watched the variations and ranked them according to a set of criteria for evaluating behaviors. The study showed that behavior capture is a viable alternative to existing manual scripting methods and that HMMs produced the most highly ranked variation with respect to overall believability.

Original languageEnglish (US)
Title of host publicationAdvances in Computer Games - 13th International Conference, ACG 2011, Revised Selected Papers
Pages342-353
Number of pages12
DOIs
StatePublished - Aug 20 2012
Event13th International Conference on Advances in Computer Games, ACG 2011 - Tilburg, Netherlands
Duration: Nov 20 2011Nov 22 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7168 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Advances in Computer Games, ACG 2011
CountryNetherlands
CityTilburg
Period11/20/1111/22/11

Fingerprint

Virtual Characters
Hidden Markov models
Markov Model
Computer games
Trace
Computer Games
Data-driven
Game
Alternatives

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Zhao, R., & Szafron, D. (2012). Generating believable virtual characters using behavior capture and hidden Markov models. In Advances in Computer Games - 13th International Conference, ACG 2011, Revised Selected Papers (pp. 342-353). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7168 LNCS). https://doi.org/10.1007/978-3-642-31866-5_29
Zhao, Richard ; Szafron, Duane. / Generating believable virtual characters using behavior capture and hidden Markov models. Advances in Computer Games - 13th International Conference, ACG 2011, Revised Selected Papers. 2012. pp. 342-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Zhao, R & Szafron, D 2012, Generating believable virtual characters using behavior capture and hidden Markov models. in Advances in Computer Games - 13th International Conference, ACG 2011, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7168 LNCS, pp. 342-353, 13th International Conference on Advances in Computer Games, ACG 2011, Tilburg, Netherlands, 11/20/11. https://doi.org/10.1007/978-3-642-31866-5_29

Generating believable virtual characters using behavior capture and hidden Markov models. / Zhao, Richard; Szafron, Duane.

Advances in Computer Games - 13th International Conference, ACG 2011, Revised Selected Papers. 2012. p. 342-353 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7168 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Zhao R, Szafron D. Generating believable virtual characters using behavior capture and hidden Markov models. In Advances in Computer Games - 13th International Conference, ACG 2011, Revised Selected Papers. 2012. p. 342-353. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-31866-5_29