research-article

Perceptual effects of scene context and viewpoint for virtual pedestrian crowds

Authors:

Christopher Peters,

Carol O'SullivanAuthors Info & Claims

ACM Transactions on Applied Perception (TAP), Volume 8, Issue 2

Article No.: 10, Pages 1 - 22

https://doi.org/10.1145/1870076.1870078

Published: 02 February 2011 Publication History

Abstract

In this article, we evaluate the effects of position, orientation, and camera viewpoint on the plausibility of pedestrian formations. In a set of three perceptual studies, we investigated how humans perceive characteristics of virtual crowds in static scenes reconstructed from annotated still images, where the orientations and positions of the individuals have been modified. We found that by applying rules based on the contextual information of the scene, we improved the perceived realism of the crowd formations when compared to random formations. We also examined the effect of camera viewpoint on the plausibility of virtual pedestrian scenes, and we found that an eye-level viewpoint is more effective for disguising random behaviors, while a canonical viewpoint results in these behaviors being perceived as less realistic than an isometric or top-down viewpoint. Results from these studies can help in the creation of virtual crowds, such as computer graphics pedestrian models or architectural scenes, and identify situations when users' perception is less accurate.

References

[1]

Blanz, V., Tarr, M. J., Bulthoff, H. H., and Vetter, T. 1999. What object attributes determine canonical views&quest; Perception 28, 575--600.

[2]

Bulthoff, H. H., Edelman, S. Y., and Tarr, M. J. 1995. How are three-dimensional objects represented in the brain&quest; Cerebral Cortex 5, 3, 247--260.

[3]

Chenney, S. 2004. Flow tiles. In Proceedings of the Eurographics Symposium on Computer Animation (SCA'04). ACM, New York, 233--242.

Digital Library

[4]

Ennis, C., Peters, C., and O'Sullivan, C. 2008. Perceptual evaluation of position and orientation context rules for pedestrian formations. In Proceedings of the 5th Symposium on Applied Perception in Graphics and Visualization (APGV'08). ACM, New York, 75--82.

Digital Library

[5]

Gallese, V., Fadiga, L., Fogassi, L., and Rizzolatti, G. 1996. Action recognition in the premotor cortex. Brain 119, 593--609.

[6]

Gomez, P. and Shutter, J. 2008. Memory for objects in canonical and non canonical viewpoints. Psychonomic Bull. Rev. 15, 5, 990--944.

[7]

Helbing, D. and Molnár, P. 1995. Social force model for pedestrian dynamics. Phys. Rev. E 51, 5, 4282--4286.

[8]

Henry, D. and Furness, T. 1993. Spatial perception in virtual environments: Evaluating an architectural application. In Proceedings of the Annual International Virtual Reality Symposium. IEEE, Los Alamitos, CA, 33--40.

[9]

Lamarche, F. and Donikian, S. 2004. Crowd of virtual humans: a new approach for real time navigation in complex and structured environments. Comput. Graphics Forum 51, 3, 509--518.

[10]

Lee, K. H., Choi, M. G., Hong, Q., and Lee, J. 2007. Group behavior from video: A data-driven approach to crowd simulation. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation (SCA'07). ACM, New York, 109--118.

Digital Library

[11]

Lerner, A., Chrysanthou, Y., and Dani, L. 2007. Crowds by example. Comput. Graphics Forum 26, 3, 655--664.

[12]

Lyons, M. J., Campbell, R., Plante, A., Coleman, M., Kamachi, M., and Akamatsu, S. 2000. The noh mask effect: vertical viewpoint dependence of facial expression perception. Proc. Biol. Sci. 267, 1459, 2239--2245.

[13]

McDonnell, R., Newell, F., and O'Sullivan, C. 2007. Smooth movers: Perceptually guided human motion simulation. In Proceedings of the Eurographics Symposium on Computer Animation (SCA'07). ACM, New York, 259--269.

Digital Library

[14]

Musse, S. R. and Thalmann, D. 1997. A model of human crowd behavior: Group interrelationship and collision detection analysis. In Proceedings of the Eurographics Workshop on Animation and Simulation. Springer-Verlag, Berlin, 39--52.

[15]

Palmer, S. E. and Rosch, P. C. 1981. Canonical perspective and the perception of objects. In Proceedings of the 9th International Symposium on Attention and Performance. 135--151.

[16]

Pelechano, N., Allbeck, J. M., and Badler, N. I. 2007. Controlling individual agents in high-density crowd simulation. In Proceedings of the Eurographics Symposium on Computer animation (SCA'07). ACM, New York, 99--108.

Digital Library

[17]

Peters, C., Ennis, C., McDonnell, R., and O'Sullivan, C. 2008. Crowds in context: Evaluating the perceptual plausibility of pedestrian orientations. In Proceedings of Eurographics Short Papers. Springer-Verlag, Berlin.

[18]

Premack, D. and Woodruff, G. 1978. Does the chimpanzee have a theory of mind&quest; Behav. Brain Sci. 1, 515--526.

[19]

Reitsma, P. S. A. and Pollard, N. S. 2003. Perceptual metrics for character animation: sensitivity to errors in ballistic motion. ACM Trans. Graph. 22, 3, 537--542.

Digital Library

[20]

Reynolds, C. W. 1987. Flocks, herds, and schools: A distributed behavioral model. Comput. Graphics 21, 4, 25--34.

Digital Library

[21]

Schilbach, L., Wohlschlaeger, A., Kraemer, N., Newen, A., Shah, N., Fink, G., and Vogeley, K. 2006. Being with virtual others: Neural correlates of social interaction. Neuropsychologia 44, 5, 718--730.

[22]

Shao, W. and Terzopoulos, D. 2005. Autonomous pedestrians. In Proceedings of the Eurographics Symposium on Computer Animation (SCA'05). ACM, New York, 19--28.

Digital Library

[23]

Tarr, M. J. 1995. Rotating objects to recognize them: A case study on the role of viewpoint dependency in the recognition of three-dimensional objects. Psychonomic Bull. Rev. 2, 1, 5582.

[24]

Yarbus, A. L. and Haigh, B. 1973. Eye Movements and Vision. Plenum Press, New York.

Cited By

Talukdar BZhang YWeiss T(2024)Learning Crowd Motion Dynamics with CrowdsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36513027:1(1-17)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3651302
Rekik RWuhrer SHoyet LZibrek KOlivier A(2024)A Survey on Realistic Virtual Human Animations: Definitions, Features and EvaluationsComputer Graphics Forum10.1111/cgf.1506443:2Online publication date: 30-Apr-2024
https://doi.org/10.1111/cgf.15064
Mogra SKhamidi MFadli F(2023)Insight into vegetation inclusion along urban roads: A pilot study on the preferences of expatriate roadside users in downtown Doha, QatarLandscape Online10.3097/LO.2023.1108(1108)Online publication date: 20-May-2023
https://doi.org/10.3097/LO.2023.1108
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Index Terms

Perceptual effects of scene context and viewpoint for virtual pedestrian crowds
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation

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Published In

cover image ACM Transactions on Applied Perception

ACM Transactions on Applied Perception Volume 8, Issue 2

January 2011

125 pages

ISSN:1544-3558

EISSN:1544-3965

DOI:10.1145/1870076

Issue’s Table of Contents

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 February 2011

Accepted: 01 March 2010

Revised: 01 February 2010

Received: 01 February 2009

Published in TAP Volume 8, Issue 2

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Cited By

Talukdar BZhang YWeiss T(2024)Learning Crowd Motion Dynamics with CrowdsProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36513027:1(1-17)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3651302
Rekik RWuhrer SHoyet LZibrek KOlivier A(2024)A Survey on Realistic Virtual Human Animations: Definitions, Features and EvaluationsComputer Graphics Forum10.1111/cgf.1506443:2Online publication date: 30-Apr-2024
https://doi.org/10.1111/cgf.15064
Mogra SKhamidi MFadli F(2023)Insight into vegetation inclusion along urban roads: A pilot study on the preferences of expatriate roadside users in downtown Doha, QatarLandscape Online10.3097/LO.2023.1108(1108)Online publication date: 20-May-2023
https://doi.org/10.3097/LO.2023.1108
Amos MWebster J(2022)Crowd-Sourced Identification of Characteristics of Collective Human MotionArtificial Life10.1162/artl_a_0038128:4(401-422)Online publication date: 1-Nov-2022
https://doi.org/10.1162/artl_a_00381
Huang ZLi LWang L(2022)Emotion-Based Crowd Model Evaluation Method Based on Features Distribution DistanceProceedings of the 2022 6th International Conference on Computer Science and Artificial Intelligence10.1145/3577530.3577567(231-236)Online publication date: 9-Dec-2022
https://dl.acm.org/doi/10.1145/3577530.3577567
Giunchi DBovo RCharalambous PLiarokapis FShipman AJames SSteed AHeinis T(2021)Perceived Realism of Pedestrian Crowds Trajectories in VRProceedings of the 27th ACM Symposium on Virtual Reality Software and Technology10.1145/3489849.3489860(1-5)Online publication date: 8-Dec-2021
https://dl.acm.org/doi/10.1145/3489849.3489860
Randhavane TBera AKubin EGray KManocha D(2021)Modeling Data-Driven Dominance Traits for Virtual Characters Using Gait AnalysisIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.295306327:6(2967-2979)Online publication date: 1-Jun-2021
https://doi.org/10.1109/TVCG.2019.2953063
Mazumdar AMousas C(2021)Synthesizing affective virtual reality multicharacter experiencesComputer Animation and Virtual Worlds10.1002/cav.200432:3-4Online publication date: 24-May-2021
https://doi.org/10.1002/cav.2004
Webster JAmos M(2020)A Turing test for crowdsRoyal Society Open Science10.1098/rsos.2003077:7(200307)Online publication date: 22-Jul-2020
https://doi.org/10.1098/rsos.200307
Nelson MMazumdar AJamal SChen YMousas C(2020)Walking in a Crowd Full of Virtual Characters: Effects of Virtual Character Appearance on Human Movement BehaviorAdvances in Visual Computing10.1007/978-3-030-64556-4_48(617-629)Online publication date: 5-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-64556-4_48
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