How People Use Visual Landmarks for Locomotion Distance Estimation: The Case Study of Eye Tracking

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 213)

Abstract

Research has been focusing on how people navigate in the virtual space since the technology of virtual reality was developed. However, not enough has been known about the process of the virtual space cognition. During locomotion, distance could be visually accessed by integrating motion cues, such as optic flow, or by the self-displacement process in which people compare the change of their self-position relative to individual identifiable objects (i.e. landmarks) in the environment along the movement. In this study, we attempted to demonstrate the effect of the later mechanism by separating the static visual scenes from the motion cues in a simulated self-movement using a static-frame paradigm. In addition, we compared the eye tracking pattern in the static scene condition (without motion cues) with the eye tracking pattern in the full visual cue condition (with motion cues). The results suggested that when only static visual scenes were available during the simulated self-movement, people were able to reproduce the traveled distance. The eye tracking results also revealed there were two different perceptual processes for locomotion distance estimation and it was suggested that locomotion distance could be estimated not only by optic flow as we already knew, but also by the self-displacement process from the visual static scenes.

Keywords

Landmarks Locomotion distance estimation Eye tracking 

Notes

Acknowledgments

We would like to thank Dr. Frances Wang from University of Illinois at Urbana-Champaign and Dr. Wang Ying from Institute of Psychology, CAS for their instructions and constructive suggestions on our study. And we thank Dr. Yao Lin from Institute of Psychology, CAS for his help on data analysis. Special thanks are given to our participants for their patience and valuable time.

References

  1. 1.
    Warren WH (1995) Self-motion: visual perception and visual control. In: Epstein W, Rogers S (eds) Perception of space and motion handbook of perception and cognition. Academic Press, San Diego, pp 263–325CrossRefGoogle Scholar
  2. 2.
    Klatzky RL, Loomis JM, Golledge RG, Cicinelli JG, Doherty S, Pellegrino JW (1990) Acquisition of route and survey knowledge in the absence of vision. J Mot Behav 22:19–43CrossRefGoogle Scholar
  3. 3.
    Klatzky RL, Loomis JM, Golledge RG (1997) Encoding spatial representations through nonvisually guided locomotion: tests of human path integration. In: Medin D The psychology of learning and motivation, Academic Press, San Diego, pp 41–84Google Scholar
  4. 4.
    Berthoz A, IsraIël L, Georges-François P, Grasso R, Tsuzuku T (1995) Spatial memory of body linear displacement: what is being stored? Science 269:95–98CrossRefGoogle Scholar
  5. 5.
    Lappe M, Frenz H, Bührmann T, Kolesnik M (2005) Virtual odometry from visual flow. Proc SPIE 5666:493–502CrossRefGoogle Scholar
  6. 6.
    Redlick PF, Jenkin M, Harris RL (2001) Humans can use optic flow to estimate distance of travel. Vision Res 41:213–219CrossRefGoogle Scholar
  7. 7.
    Wan X, Wang RF, Crowell JA (2012) The effect of landmarks in human path integration. Acta Psychologica 140(1):7–12Google Scholar
  8. 8.
    Ellmore TM, McNaughton BL (2004) Human path integration by optic flow. Spat Cogn 4(3):255–272CrossRefGoogle Scholar
  9. 9.
    Gibson JJ (1950) Perception of the visual world. Houghton Mifflin, BostonGoogle Scholar
  10. 10.
    Kearns MJ, Warren WH, Duchon AP, Tarr MJ (2002) Path integration from optic flow and body senses in a homing task. Perception 31:349–374CrossRefGoogle Scholar
  11. 11.
    Bremmer F, Lappe M (1999) The use of optical velocities for distance discrimination and reproduction during visually simulated self-motion. Exp Brain Res 127:33–42CrossRefGoogle Scholar
  12. 12.
    Frenz H, Lappe M (2005) Absolute travel distance from optic flow. Vision Res 45:1679–1692CrossRefGoogle Scholar
  13. 13.
    Frenz H, Lappe M, Kolesnik M, Bührmann T (2007) Estimation of travel distance from visual motion in virtual environments. ACM Trans Appl Percept 4(1):1–18CrossRefGoogle Scholar
  14. 14.
    Riecke BE, van Veen HACH, Bülthoff HH (2002) Visual homing is possible without landmarks: a path integration study in virtual reality. Presence 11(5):443–473Google Scholar
  15. 15.
    Lappe M, Jenkin M, Harris LR (2007) Travel distance estimation from visual motion by leaky path integration. Exp Brain Res 180:35–48CrossRefGoogle Scholar
  16. 16.
    Loomis JM, Da Silva JA, Philbeck JW, Fukusima SS (1996) Visual perception of location and distance. Curr Dir Psychol Sci 5:72–77CrossRefGoogle Scholar
  17. 17.
    Witt JK, Stefanucci JK, Riener CR, Proffitt DR (2007) Seeing beyond the target: environmental context affects distance perception. Perception 36:1752–1768CrossRefGoogle Scholar
  18. 18.
    Sun H, Campos JL, Young M, Chan GSW (2004) The contributions of static visual cues, nonvisual cues, and optic flow in distance estimation. Perception 33:49–65CrossRefGoogle Scholar
  19. 19.
    Frenz H, Lappe M (2006) Visual distance estimation in static compared to moving virtual scenes. Span J Psychol 9(2):321–331Google Scholar
  20. 20.
    Angelaki DE, Hess BJM (2005) Self-motion-induced eye movements: effects on visual acuity and navigation. Nat Rev Neurosci 6:966–976CrossRefGoogle Scholar
  21. 21.
    Loomis JM, Klatzky RL, Golledge RG, Cicinelli JG, Pellegrino JW, Fry PA (1993) Nonvisual navigation by blind and sighted: assessment of path integration ability. J Exp Psychol Gen 122(1):73–91Google Scholar
  22. 22.
    Loomis JM, Knapp JM (2003) Visual perception of egocentric distance in real and virtual environments. In: Hettinger LJ, Haas MW (eds) Virtual and adaptive environments. Erlbaum, Mahwah, pp 21–46Google Scholar
  23. 23.
    Thompson WB, Willemsen P, Gooch AA, Creem-Regehr SH, Loomis JM, Beall AC (2004) Does the quality of the computer graphics matter when judging distances in visually immersive environments? Presence 13:560–571CrossRefGoogle Scholar
  24. 24.
    Riecke BE, Schulte-Pelkum J, Bülthoff HH (2005) Perceiving simulated ego-motions in virtual reality—comparing large screen displays with HMDs. Proc SPIE 5666:344–355CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Institute of PsychologyChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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