Information Technology Reference
In-Depth Information
Arnheim, R. (1966).
Towards a psychology of art/entropy and art—an essay on disorder and order
.
The Regents of the University of California.
Arnheim, R. (1969).
Visual thinking
. Berkeley: University of California Press.
Athitsos, V., Swain, M. J., & Frankel, C. (1997). Distinguishing photographs and graphics on the
world wide web. In
Proceedings of the 1997 workshop on content-based access of image and
video libraries (CBAIVL '97), CAIVL '97
(pp. 10-17). Washington: IEEE Computer Society.
Baluja, S., Pomerlau, D., & Todd, J. (1994). Towards automated artificial evolution for computer-
generated images.
Connection Science
,
6
(2), 325-354.
Boden, M. A. (1990).
The creative mind: myths and mechanisms
. New York: Basic Books.
Burt, C. (1933). The psychology of art. In
How the mind works
. London: Allen and Unwin.
Canny, J. (1986). A computational approach to edge detection.
IEEE Transactions on Pattern Anal-
ysis and Machine Intelligence
,
8
(6), 679-698.
Chamorro-Premuzic, T., & Furnham, A. (2004). Art judgement: a measure related to both person-
ality and intelligence?
Imagination, Cognition and Personality
,
24
, 3-25.
Cope, D. (1992). On the algorithmic representation of musical style. In O. Laske (Ed.),
Under-
standing music with AI: perspectives on music cognition
(pp. 354-363). Cambridge: MIT Press.
Cutzu, F., Hammoud, R. I., & Leykin, A. (2003). Estimating the photorealism of images: distin-
guishing paintings from photographs. In
CVPR (2)
(pp. 305-312). Washington: IEEE Computer
Society.
Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2006). Studying aesthetics in photographic images using a
computational approach. In
Lecture notes in computer science
.
Computer vision—ECCV 2006,
9th European conference on computer vision, part III
, Graz, Austria (pp. 288-301). Berlin:
Springer.
Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2008). Image retrieval: ideas, influences, and trends
of the new age.
ACM Computing Surveys
,
40
, 5:1-5:60.
http://doi.acm.org/10.1145/1348246.
Dorin, A., & Korb, K. B. (2009). Improbable creativity. In M. Boden, M. D'Inverno, & J. McCor-
mack (Eds.),
Dagstuhl seminar proceedings: Vol. 09291
.
Computational creativity: an interdis-
ciplinary approach
, Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany.
Eysenck, H. (1969). Factor analytic study of the Maitland Graves Design Judgement Test.
Percep-
tual and Motor Skills
,
24
, 13-14.
Eysenck, H. J. (1983). A new measure of 'good taste' in visual art.
Leonardo, Special Issue: Psy-
chology and the Arts
,
16
(3), 229-231.
http://www.jstor.org/stable/1574921
.
Eysenck, H. J., & Castle, M. (1971). Comparative study of artists and nonartists on the Maitland
Graves Design Judgment Test.
Journal of Applied Psychology
,
55
(4), 389-392.
Eysenck, H. J., Götz, K. O., Long, H. Y., Nias, D. K. B., & Ross, M. (1984).
A new visual aesthetic sensitivity test—IV. Cross-cultural comparisons between a Chi-
nese sample from Singapore and an English sample.
Personality and Individual Differ-
ences
,
5
(5), 599-600.
http://www.sciencedirect.com/science/article/B6V9F-45WYSPS-1M/2/
Field, D. J., Hayes, A., & Hess, R. F. (2000). The roles of polarity and symmetry in the perceptual
grouping of contour fragments.
Spatial Vision
,
13
(1), 51-66.
Fisher, Y. (Ed.) (1995).
Fractal image compression: theory and application
. London: Springer.
Frois, J., & Eysenck, H. J. (1995). The visual aesthetic sensitivity test applied to Portuguese chil-
dren and fine arts students.
Creativity Research Journal
,
8
(3), 277-284.
http://www.leaonline.
Furnham, A., & Walker, J. (2001). The influence of personality traits, previous experience
of art, and demographic variables on artistic preference.
Personality and Individual Dif-
ferences
,
31
(6), 997-1017.
http://www.sciencedirect.com/science/article/B6V9F-440BD9B-J/
Götz, K. (1985).
VAST: visual aesthetic sensitivity test
. Dusseldorf: Concept Verlag.
