Abstract
Most crowd simulation research either focuses on navigating characters through an environment while avoiding collisions or on simulating very large crowds. Functional crowds research focuses on creating populations that inhabit a space as opposed to passing through it. Characters exhibit behaviors that are typical for their setting, including interactions with objects in the environment and each other. A key element of this work is ensuring that these large-scale simulations are easy to create and modify. Automating the inclusion of action and object semantics can increase the level at which instructions are given. To scale to large populations, behavior selection mechanisms must be kept relatively simple and, to demonstrate typical human behavior, must be based on sound psychological models. The creation of roles, groups, and demographics can also facilitate behavior selection. The simulation of functional crowds necessitates research in animation, artificial intelligence, psychology, and human-computer interaction (HCI). This chapter provides a brief introduction to each of these elements and their application to functional crowds.
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References
Allbeck JM (2009) Creating 3D animated human behaviors for virtual worlds. University of Pennsylvania, Philadelphia, PA
Allbeck JM (2010) CAROSA: a tool for authoring NPCs. In: Presented at the international conference on motion in games. Springer, pp 182–193.
Allbeck J, Badler NI (2001) Consistent Communication with Control. In: Workshop on non-verbal and Verbal Communicative Acts to achieve contextual embodied agents at autonomous agents.
Bai Y, Siu K, Liu CK (2012) Synthesis of concurrent object manipulation tasks. ACM Trans Graph 31(6):156
Balint T, Allbeck JM (2014) Is that how everyone really feels? emotional contagion with masking for virtual crowds. In: Presented at the international conference on intelligent virtual agents. Springer, pp 26–35
Balint T, Allbeck JM (2015) Automated generation of plausible agent object interactions. In: Presented at the international conference on intelligent virtual agents. Springer, pp 295–309
Bindiganavale R, Schuler W, Allbeck JM, Badler NI, Joshi AK, Palmer M (2000) Dynamically altering agent behaviors using natural language instructions. In: Proceedings of the fourth international conference on autonomous agents. ACM, New York, pp 293–300. doi:10.1145/336595.337503
Clegg A, Tan J, Turk G, Liu CK (2015) Animating human dressing. ACM Trans Graph 34(4):116
Durupinar F, Gudukbay U, Aman A, Badler N (2016) Psychological parameters for crowd simulation: from audiences to Mobs. IEEE Trans Vis Comput Graph 22(9):2145–2159
Feng A, Casas D, Shapiro A (2015) Avatar reshaping and automatic rigging using a deformable model. In: Presented at the proceedings of the 8th ACM SIGGRAPH conference on motion in games. ACM, pp 57–64
Hyde J, Carter E, Kiesler S, Hodgins J (2016) Evaluating animated characters: facial motion magnitude influences personality perceptions. ACM Trans Appl Percept 13(2):8:1–8:17
IVA (1998) International conference on intelligent virtual humans. Springer, Berlin
Kapadia M, Pelechano N, Allbeck J, Badler N (2015) Virtual crowds: steps toward behavioral realism. Morgan & Claypool Publishers, San Rafael, California
Li W, Allbeck JM (2011) Populations with purpose. In: Motion in games. Springer, Berlin/Heidelberg, pp 132–143
Li W, Allbeck JM (2012) Virtual humans: evolving with common sense. In: Presented at the international conference on motion in games. Springer, pp 182–193
Li W, Di Z, Allbeck JM (2012) Crowd distribution and location preference. Comput Anim Virtual Worlds 23(3–4):343–351
Li WP, Balint T, Allbeck JM (2013). Using a parameterized memory model to modulate NPC AI. In: Presented at the intelligent virtual agents: 13th international conference, IVA 2013, Edinburgh, August 29–31, 2013, Proceedings, vol 8108. Springer, p 1
McDonnell R, Larkin M, Dobbyn S, Collins S, O’Sullivan C (2008) Clone attack! perception of crowd variety. In: Presented at the ACM Transactions on Graphics (TOG), vol 27. ACM, p 26
Pelechano N, Allbeck JM, Badler NI (2008) Virtual crowds: methods, simulation, and control. Synth Lect Comput Graph Animation 3(1):1–176
Pelechano N, Allbeck JM, Kapadia M, Badler NI (eds) (2016) Simulating heterogeneous crowds with interactive behaviors. CRC Press, Boca Raton, FL
Pelkey CD, Allbeck JM (2014) Populating semantic virtual environments. Computer Animation and Virtual Worlds 25(3–4):403–410
Shapiro A (2011) Building a character animation system. In: Presented at the international conference on motion in games. Springer, pp 98–109
Sunshine-Hill B, Badler NI (2010) Perceptually realistic behavior through alibi generation. In Proceedings of the Sixth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE’10), G. Michael Youngblood and Vadim Bulitko (Eds.). AAAI Press 83–88
Thalmann D, Musse SR, Braun A (2007) Crowd simulation, vol 1. Springer, Berlin
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Allbeck, J.M. (2016). Functional Crowds. In: Müller, B., et al. Handbook of Human Motion. Springer, Cham. https://doi.org/10.1007/978-3-319-30808-1_16-1
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DOI: https://doi.org/10.1007/978-3-319-30808-1_16-1
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