What does water look like?
Inhaltsverzeichnis
Reference
Marta Kryven and William Cowan: What does water look like? In: Computational Aesthetics 2014.
DOI
http://dx.doi.org/10.1145/2630099.2630110
Abstract
What makes images of water look like water? We conducted four psychophysical experiments to isolate perceptual qualities that make water easy to recognize. Water recognition is facilitated by colour and by three patterns of waves. Low spatial frequencies (LSF) (<4.4 cpd) contribute more to recognition than high spatial frequencies (HSF). Here we describe the experimental methodology and results. Knowing which aspects of appearance identify water can inform perceptually inspired depiction of water, can create visual illusions and can reduce computation in realistic simulations.
Extended Abstract
Bibtex
@inproceedings{Kryven:2014:WLL:2630099.2630110,
author = {Kryven, Marta and Cowan, William},
title = {What Does Water Look Like?},
booktitle = {Proceedings of the Workshop on Computational Aesthetics},
series = {CAe '14},
year = {2014},
isbn = {978-1-4503-3019-0},
location = {Vancouver, British Columbia, Canada},
pages = {53--56},
numpages = {4},
url = {http://doi.acm.org/10.1145/2630099.2630110 http://de.evo-art.org/index.php?title=What_does_water_look_like%3F },
doi = {10.1145/2630099.2630110},
acmid = {2630110},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {non-photorealistic rendering, object recognition, perception, spatial frequency scales, water simulation},
}
Used References
Bar, M., Neta, M., and Linz, H. 2006. Very first impressions. Emotion 6, 269.
De Valois, R., and De Valois, K. 1988. Spatial Vision. Oxford: Oxford University Press.
Delorme, A., Richard, G., and Fabre-Thorpe, M. 2000. Ultra-rapid categorisation of natural scenes does not rely on colour cues: a study in monkeys and humans. Vision research 40, 2187--2200.
Field, D. J. 1987. Relations between the statistics of natural images and the response properties of cortical cells. JOSA A 4, 2379--2394.
Hoffman, D. D., and Singh, M. 1997. Salience of visual parts. Cognition 63, 29--78.
Holcombe, A. O. 2009. Seeing slow and seeing fast: two limits on perception. Trends in cognitive sciences 13, 216--221.
Marta Kryven , William Cowan, Modelling perceptually efficient aquatic environments, Proceedings of the ACM Symposium on Applied Perception, August 22-23, 2013, Dublin, Ireland http://doi.acm.org/10.1145/2492494.2501888
Liu, C., Sharan, L., Adelson, E. H., and Rosenholtz, R. 2010. Exploring features in a bayesian framework for material recognition. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, IEEE, 239--246.
M I Mills, Image synthesis: optical identity or pictorial communication, Proceedings of Graphics Interface '85 on Computer-generated images: the state of the art, p.3-10, January 1986, Montreal, Quebec, Canada http://dl.acm.org/citation.cfm?id=20314&CFID=588525319&CFTOKEN=29804931
Alessandro Perina , Marco Cristani , Vittorio Murino, Learning natural scene categories by selective multi-scale feature extraction, Image and Vision Computing, v.28 n.6, p.927-939, June, 2010 http://dx.doi.org/10.1016/j.imavis.2009.11.007
Pope, R. M., and Fry, E. S. 1997. Absorption spectrum (380--700 nm) of pure water. ii. integrating cavity measurements. Applied optics 36, 8710--8723.
Selst, M. V., and Jolicoeur, P. 1994. A solution to the effect of sample size on outlier elimination. The Quarterly Journal of Experimental Psychology Section A 47, 3, 631--650.
Thorpe, S., Fize, D., Marlot, C., et al. 1996. Speed of processing in the human visual system. Nature 381, 520--522.
Treisman, A. M., and Gelade, G. 1980. A feature-integration theory of attention. Cognitive psychology 12, 1, 97--136.
Julia Vogel , Bernt Schiele, Semantic Modeling of Natural Scenes for Content-Based Image Retrieval, International Journal of Computer Vision, v.72 n.2, p.133-157, April 2007 http://dx.doi.org/10.1007/s11263-006-8614-1
Links
Full Text
[extern file]
