Hostname: page-component-8448b6f56d-wq2xx Total loading time: 0 Render date: 2024-04-18T18:12:27.471Z Has data issue: false hasContentIssue false

Visual Distance Estimation in Static Compared to Moving Virtual Scenes

Published online by Cambridge University Press:  10 April 2014

Harald Frenz*
Affiliation:
Westfälische Wilhelms-Universität Münster, Germany
Markus Lappe
Affiliation:
Westfälische Wilhelms-Universität Münster, Germany
*
Correspondence concerning this article should be addressed to Harald Frenz, Allgemeine und angewandte Psychologie, Westfälische Wilhelms-Universität Münster, 48149 Münster, Germany. E-mail: frenzh@uni-muenster.de

Abstract

Visual motion is used to control direction and speed of self-motion and time-to-contact with an obstacle. In earlier work, we found that human subjects can discriminate between the distances of different visually simulated self-motions in a virtual scene. Distance indication in terms of an exocentric interval adjustment task, however, revealed linear correlation between perceived and indicated distances but with a profound distance underestimation. One possible explanation for this underestimation is the perception of visual space in virtual environments. Humans perceive visual space in natural scenes as curved, and distances are increasingly underestimated with increasing distance from the observer. Such spatial compression may also exist in our virtual environment. We therefore surveyed perceived visual space in a static virtual scene. We asked observers to compare two horizontal depth intervals, similar to experiments performed in natural space. Subjects had to indicate the size of one depth interval relative to a second interval. Our observers perceived visual space in the virtual environment as compressed, similar to the perception found in natural scenes. However, the nonlinear depth function we found can not explain the observed distance underestimation of visual simulated self-motions in the same environment.

El movimiento visual se emplea en el control de la dirección y la velocidad de la auto-locomoción y, también, para conocer el tiempo de contacto con un obstáculo. En trabajos anteriores encontramos que los observadores humanos pueden discriminar entre las distancias de diferentes auto-locomociones simuladas visualmente en una escena virtual. La indicación de la distancia mediante una tarea de ajuste de intervalo exocéntrico, sin embargo, reveló una correlación lineal entre las distancias percibidas y las indicadas, pero con una gran subestimación de la distancia. Una posible explicación de esta subestimación se basa en las características de la percepción visual del espacio en ambientes virtuales. En las escenas naturales los humanos percibimos el espacio visual como curvado, y las distancias se subestiman con el incremento de la separación respecto al observador. Esta compresión espacial también puede existir en nuestro ambiente virtual. Por ello, se decidió evaluar el espacio visual percibido en una escena estática virtual. Pedimos a los observadores que comparasen dos intervalos de profundidad horizontal, similares a experimentos llevados a cabo en el espacio natural. Los sujetos debían indicar el tamaño de un intervalo de profundidad con respecto a un segundo intervalo. Nuestros observadores percibían el espacio visual en el ambiente virtual como comprimido, similar a la percepción encontrada en escenas naturales. Sin embargo, la función no lineal de profundidad que encontramos no puede explicar la subestimación observada de la distancia de las auto-locomociones visuales simuladas en el mismo ambiente.

Type
Monographic Section: Spatial Vision and Visual Space
Copyright
Copyright © Cambridge University Press 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Berthoz, A., Israel, I., Georges-Francois, P., Grasso, R., & Tsuzuku, T. (1995). Spatial memory of body linear displacement: What is being stored? Science, 269, 9598.CrossRefGoogle ScholarPubMed
Bertin, R.J., Israël, I., & Lappe, M. (2000). Perception of two-dimensional, simulated ego-motion from optic flow. Vision Research, 40, 29512971.CrossRefGoogle ScholarPubMed
Beusmans, J. M. (1998). Optic flow and the metric of the visual ground plane. Vision Research, 38, 11531170.CrossRefGoogle ScholarPubMed
Bremmer, F., & Lappe, M. (1999). The use of optic flow for distance discrimination and reproduction during visually simulated self motion. Experimental Brain Research, 127, 3342.CrossRefGoogle Scholar
Bronstein, A., & Buckwell, D. (1997). Automatic control of postural sway by visual motion parallax. Experimental Brain Research, 113, 243248.CrossRefGoogle ScholarPubMed
Cuijpers, R.H., Kappers, A.M.L., & Koenderink, J.J. (2000). Large systematic deviations in visual parallelism. Perception, 29, 14671482.CrossRefGoogle ScholarPubMed
Cuijpers, R.H., Kappers, A.M.L., & Koenderink, J J. (2002). Visual perception of collinearity. Perception and Psychophysics, 64, 392404.CrossRefGoogle ScholarPubMed
Foley, J.M. (1980). Binocular distance perception. Psychological Review, 87, 411434.CrossRefGoogle ScholarPubMed
Foley, J.M., Ribeiro-Filho, N.P., & Da Silva, J.A. (2004). Visual perception of extent and the geometry of visual space. Vision Research, 44, 147156.CrossRefGoogle ScholarPubMed
Frenz, H., Bremmer, F., & Lappe, M. (2003). Discrimination of travel distances from ‘situated’ optic flow. Vision Research, 43, 21732183.CrossRefGoogle ScholarPubMed
Frenz, H., & Lappe, M. (2005). Absolute travel distances from optic flow. Vision Research, 45, 16791692.CrossRefGoogle ScholarPubMed
Gilinsky, A.S. (1951). Perceived size and distance in visual space. Psychological Review, 58, 460482.CrossRefGoogle ScholarPubMed
He, Z.J., Wu, B., Ooi, T.L., Yarbrough, G., & Wu, J. (2004). Judging egocentric distance on the ground: Occlusion and surface integration. Perception, 33, 789806.CrossRefGoogle ScholarPubMed
Hecht, H., & Savelsbergh, G.J.P. (2004). Advances in psychology 135 — Time-to-contact. Amsterdam, Boston, Heidelberg: Elsevier.Google Scholar
Hecht, H., van Doorn, A., & Koenderink, J.J. (1999). Compression of visual space in natural scenes and their photographic counterparts. Perception and Psychophysics, 61, 12691286.CrossRefGoogle ScholarPubMed
Indow, T. (1991). A critical review of Luneburg's model with regard to global structure of visual space. Psychological Review, 98, 430–53.CrossRefGoogle ScholarPubMed
Kearns, M.J., Warren, W.H., Duchon, A.P., & Tarr, M.J. (2002). Path integration from optic flow and body senses in a homing task. Perception, 31, 349374.CrossRefGoogle Scholar
Knapp, J.M., & Loomis, J.M. (2004). Limited field of view of head-mounted displays is not the cause of distance underestimation in virtual environments. Presence, 13, 572577.CrossRefGoogle Scholar
Koenderink, J.J., van Doorn, A., Kappers, A.M., & Todd, J.T. (2002). Pappus in optical space. Perception and Psychophysics, 64, 380391.CrossRefGoogle ScholarPubMed
Lappe, M., Bremmer, F., & van den Berg, A.V. (1999). Perception of self-motion from visual flow. Trends in Cognitive Sciences, 3, 329336.CrossRefGoogle ScholarPubMed
Lappe, M., Frenz, H., Bührmann, T., & Kolesnik, M. (2005). Virtual odometry from visual flow. Proceedings of SPIE, 5666, 493502.Google Scholar
Lee, D.N. (1980). The optic flow field: The foundation of vision. Philosophical Transactions of the Royal Society of London B, 290, 169179.Google ScholarPubMed
Loomis, J.M., Da Silva, J.A., Fujita, N., & Fukusima, S.S. (1992). Visual space perception and visually directed action. Journal of Experimental Psychology: Human Perception Performance, 18, 906–21.Google ScholarPubMed
Loomis, J.M., Klatzky, R.L., Golledge, R.G., Cicinelli, J.G., Pellegrino, J.W., & Fry, P.A. (1993). Nonvisual navigation by blind and sighted: Assessment of path integration ability. Journal of Experimental Psychology: General, 122, 7391.CrossRefGoogle ScholarPubMed
Loomis, J.M., & Knapp, J.M. (2003). Visual perception of egocentric distance in real and virtual environments. In Hettinger, L.J. & Haas, M.W. (Eds.), Virtual and adaptive environments (pp. 2146). Mahwah NJ: Erlbaum.Google Scholar
Loomis, J.M., & Philibeck, J.W. (1999). Is the anisotropy of perceived 3-D shape invariant across scale? Perception and Psychophysics, 61, 397402.CrossRefGoogle ScholarPubMed
Loomis, J.M., Philibeck, J.W., & Zahorik, P. (2002). Dissociation between location and shape in visual space. Journal of Experimental Psychology: Human Perception Performance, 28, 12021212.Google ScholarPubMed
Luneburg, R.K. (1947). Mathematical analysis of binocular vision. Princeton, NJ: Princeton University Press.Google Scholar
Norman, J.F., Todd, J.T., Perotti, V.J., & Tittle, J.S. (1996). The visual perception of three-dimensional length. Journal of Experimental Psychology: Human Perception Performance, 22, 173186.Google ScholarPubMed
Peruch, P., May, M., & Wartenberg, F. (1997). Homing in virtual environments: Effects of field of view and path layout. Perception, 26, 301311.CrossRefGoogle ScholarPubMed
Prokop, T., Schubert, M., & Berger, W. (1997). Visual influence on human locomotion: Modulation to changes in optic flow. Experimental Brain Research, 114, 6370.CrossRefGoogle ScholarPubMed
Redlick, F.P., Jenkin, M., & Harris, L.R. (2001). Humans can use optic flow to estimate distance of travel. Vision Research, 41, 213219.CrossRefGoogle ScholarPubMed
Riecke, B.E., van Veen, H.A.H.C., & Bülthoff, H.H. (2002). Visual homing is possible without landmarks: A path integration study in virtual reality. Presence, 11, 443473.CrossRefGoogle Scholar
Sun, H.-J., Campos, J.L., & Chan, G.S. (2004). Multisensory integration in the estimation of relative path length. Experimental Brain Research, 154, 246254.CrossRefGoogle ScholarPubMed
Sun, H.-J., Campos, J.L., Young, M., Chan, G.S., & Ellard, C.G. (2004). The contributions of static visual cues, nonvisual cues, and optic flow in distance estimation. Perception, 33, 4965.CrossRefGoogle ScholarPubMed
Thompson, W.B., Willemsen, P., Gooch, A.A., Creem-Regehr, S.H., Loomis, J.M., & Beall, A.C. (2004). Does the quality of the computer graphics matter when judging distances in visually immersive environments? Presence, 13, 560571.CrossRefGoogle Scholar
Wagner, M. (1985). The metric of visual space. Perception and Psychophysics, 38, 483495.CrossRefGoogle ScholarPubMed
Warren, W.H. (1998). Visually controlled locomotion: 40 years later. Ecological Psychology, 10, 177219.CrossRefGoogle Scholar
Witmer, B.G., & Kline, P.B. (1998). Judging perceived and traversed distance in virtual environments. Presence, 7, 144167.CrossRefGoogle Scholar
Wu, B., Ooi, T.L., & He, Z.J. (2004). Perceiving distance accurately by a directional process of integrating ground information. Nature, 428, 7377.CrossRefGoogle ScholarPubMed