Visual Hallucination For Computational Creation
Inhaltsverzeichnis
Reference
Leonid Berov and Kai-Uwe Kuhnberger: Visual Hallucination For Computational Creation. In: Computational Creativity 2016 ICCC 2016, 107-114
DOI
Abstract
Research on computational painters usually focuses on simulating rational parts of the generative process. From an art-historic perspective it is plausible to assume that also an arational process, namely visual hallucination, played an important role in modern fine art movements like Surrealism. The present work investigates this connection between creativity and hallucination. Using psychological findings, a three-step process of perception-based creativity is derived to connect the two phenomena. Insights on the neurological correlates of hallucination are used to define properties necessary for modelling them. Based on these properties a recent technique for feature visualisation in Convolutional Neural Networks is identified as a computational model of hallucination. Contrasting the thus enabled perception-based approach with the Painting Fool allows to introduce a distinction between two distinct creative acts, sketch composition and rendering. The contribution of this work is threefold: First, a computational model of hallucination is presented and discussed in the context of a computational painter. Second, a theoretic distinction is introduced that aligns research on different strands of computational creativity and captures the differences to current computational painters. Third, the case is made that computational methods can be used to simulate abnormal mental patterns, thus investigating the role that “madness” might play in creativity – instead of simply renouncing the myth of the mad artist.
Extended Abstract
Bibtex
@inproceedings{
author = {Leonid Berov and Kai-Uwe Kuhnberger},
title = {Visual Hallucination For Computational Creation},
booktitle = {Proceedings of the Seventh International Conference on Computational Creativity},
series = {ICCC2016},
year = {2016},
month = {Jun-July},
location = {Paris, France},
pages = {107-114},
url = {http://www.computationalcreativity.net/iccc2016/wp-content/uploads/2016/01/Visual-Hallucination-For-Computational-Creation.pdf http://de.evo-art.org/index.php?title=Visual_Hallucination_For_Computational_Creation },
publisher = {Sony CSL Paris},
}
Used References
Arag´on, J. L.; Naumis, G. G.; Bai, M.; Torres, M.; and Maini, P. K. 2008. Turbulent Luminance in Impassioned van Gogh Paintings. Journal of Mathematical Imaging and Vision 30(3):275–283.
Bhattacharya, S.; Sukthankar, R.; and Shah, M. 2010. A framework for photo-quality assessment and enhancement based on visual aesthetics. In Proceedings of the international conference on Multimedia, 271–280. ACM.
Blumer, D. 2002. The illness of Vincent van Gogh. American Journal of Psychiatry.
Burke,W. 2002. The neural basis of Charles Bonnet hallucinations: a hypothesis. Journal of Neurology, Neurosurgery & Psychiatry 73(5):535–541.
Cohen-Or, D.; Sorkine, O.; Gal, R.; Leyvand, T.; and Xu, Y.-Q. 2006. Color harmonization. In ACM Transactions on Graphics (TOG), volume 25, 624–630. ACM.
Colton, S.; Halskov, J.; Ventura, D.; Gouldstone, I.; Cook, M.; Blanca, P.; and others. 2015. The Painting Fool Sees! New Projects with the Automated Painter.
Colton, S.; Valstar, M. F.; and Pantic, M. 2008. Emotionally aware automated portrait painting. In Proceedings of the 3rd conference on DIMEA, 304–311. ACM.
Colton, S. 2012. The Painting Fool: Stories from Building an Automated Painter. In McCormack, J., and d’Inverno, M., eds., Computers and Creativity. Berlin, Heidelberg: Springer Berlin Heidelberg. 3–38.
Csikszentmihalyi, M. 1997. Flow and the Psychology of Discovery and Invention. HarperPerennial, New York 39.
Elgammal, A., and Saleh, B. 2015. Quantifying Creativity in Art Networks.
Felleman, D. J., and Van Essen, D. C. 1991. Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex 1(1):1–47.
Flowers, J. H., and Garbin, C. P. 1989. Creativity and perception. In Handbook of creativity. Springer. 147–162. Frey, J. G. 1936. Miro and the Surrealists. Parnassus 8(5):13–15.
Gatys, L. A.; Ecker, A. S.; and Bethge, M. 2015. A neural algorithm of artistic style.
Gerv´as, P. 2009. Computational Approaches to Storytelling and Creativity.
Hinton, G. E.; Srivastava, N.; Krizhevsky, A.; Sutskever, I.; and Salakhutdinov, R. R. 2012. Improving neural networks by preventing co-adaptation of feature detectors. arXiv:1207.0580 [cs].
Jardri, R., and Den`eve, S. 2013. Computational models of hallucinations. In The neuroscience of hallucinations. Springer. 289–313.
Keeler, M. H. 1970. Kl¨uver’s Mechanisms of Hallucinations as Illustrated by the Paintings of Max Ernst. In M.D, W. K., ed., Origin and Mechanisms of Hallucinations. Springer US. 205–208.
Koch, C. 2015. Do Androids Dream? Scientific American Mind 26(6):24–27.
Krizhevsky, A.; Sutskever, I.; and Hinton, G. E. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems, 1097–1105.
LeCun, Y.; Bottou, L.; Bengio, Y.; and Haffner, P. 1998. Gradient-based learning applied to document recognition. Proceedings of the IEEE 86(11):2278–2324.
Li, C., and Chen, T. 2009. Aesthetic visual quality assessment of paintings. Selected Topics in Signal Processing, IEEE Journal of 3(2):236–252.
Luo, W.; Wang, X.; and Tang, X. 2011. Content-based photo quality assessment. In International Conference on Computer Vision, 2206–2213. IEEE.
Mahendran, A., and Vedaldi, A. 2015. Understanding deep image representations by inverting them. In Proceedings of the IEEE CVPR, 5188–5196. IEEE.
McCorduck, P. 1991. Aaron’s code: meta-art, artificial intelligence, and the work of Harold Cohen. Macmillan.
M´egevand, P.; Groppe, D. M.; Goldfinger, M. S.; Hwang, S. T.; Kingsley, P. B.; Davidesco, I.; and Mehta, A. D. 2014. Seeing Scenes: Topographic Visual Hallucinations Evoked by Direct Electrical Stimulation of the Parahippocampal Place Area. The Journal of Neuroscience 34(16):5399– 5405.
Merabet, L. B.; Maguire, D.; Warde, A.; Alterescu, K.; Stickgold, R.; and Pascual-Leone, A. 2004. Visual hallucinations during prolonged blindfolding in sighted subjects. Journal of Neuro-Ophthalmology 24(2):109–113.
Mocellin, R.;Walterfang, M.; and Velakoulis, D. 2006. Neuropsychiatry of complex visual hallucinations. Australian and New Zealand journal of psychiatry 40(9):742–751.
Mordvintsev, A.; Olah, C.; and Tyka, M. 2015. Inceptionism: Going Deeper into Neural Networks. Google Research Blog.
Phillips,W. 1948. Partisan Review, February, 1948, Volume XV, Number 2, volume XV of Partisan Review. New York, NY: Added Enterprises.
Russakovsky, O.; Deng, J.; Su, H.; Krause, J.; Satheesh, S.; Ma, S.; Huang, Z.; Karpathy, A.; Khosla, A.; Bernstein, M.; Berg, A. C.; and Fei-Fei, L. 2014. ImageNet Large Scale Visual Recognition Challenge. arXiv:1409.0575 [cs].
Santhouse, A. M.; Howard, R. J.; and Ffytche, D. H. 2000. Visual hallucinatory syndromes and the anatomy of the visual brain. Brain 123(10):2055–2064.
Szegedy, C.; Liu, W.; Jia, Y.; Sermanet, P.; Reed, S.; Anguelov, D.; Erhan, D.; Vanhoucke, V.; and Rabinovich, A. 2015. Going deeper with convolutions. In Proceedings of the IEEE CVPR, 1–9.
Teufel, C.; Subramaniam, N.; Dobler, V.; Perez, J.; Finnemann, J.; Mehta, P. R.; Goodyer, I. M.; and Fletcher, P. C. 2015. Shift toward prior knowledge confers a perceptual advantage in early psychosis and psychosis-prone healthy individuals. Proceedings of the National Academy of Sciences 112(43):13401–13406.
van Gogh, V. 1889. Letter 827: To Willemien van Gogh. Vincent van Gogh: The Letters. Van Gogh Museum. Veale, T. 2012. Exploding the creativity myth: the computational foundations of linguistic creativity. London ; New York: Continuum International Pub. Group.
Yao, L.; Suryanarayan, P.; Qiao, M.; Wang, J. Z.; and Li, J. 2012. Oscar: On-site composition and aesthetics feedback through exemplars for photographers. International Journal of Computer Vision 96(3):353–383.
Zeiler, M. D., and Fergus, R. 2014. Visualizing and Understanding Convolutional Networks. In Computer Vision– ECCV 2014, 818–833. Springer.
Zeki, S.;Watson, J. D.; Lueck, C. J.; Friston, K. J.; Kennard, C.; and Frackowiak, R. S. 1991. A direct demonstration of functional specialization in human visual cortex. The Journal of Neuroscience 11(3):641–649.
