Perceiving motion transitions in pedestrian crowds

  • Authors:
  • Qin Gu;Chang Yun;Zhigang Deng

  • Affiliations:
  • University of Houston;University of Houston;University of Houston

  • Venue:
  • Proceedings of the 17th ACM Symposium on Virtual Reality Software and Technology
  • Year:
  • 2010

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Abstract

Perception of motion transitions in a pedestrian crowd is affected by many collective features such as crowd density, appearance variations, motion variations, and sub-group interaction patterns. We conducted a series of psychophysical experiments to investigate how these crowd features can influence human perception on walking motion transitions in a crowd when inexpensive motion blending algorithms are used. Our results provide useful implications and practical guidelines for performance-oriented crowd applications such as real-time games to improve the perceptual realism by effectively disguising motion transitions.