Relevant content for the tag: vision

Publications

https://ivizlab.org/wp-content/uploads/sites/2/2017/09/chi15T.jpg

Touch of the Eye: Does Observation Reflect Haptic Metaphors in Art Drawing?
Conference Proceedings: ACM Conf on Human Factors in Computing Systems (CHI '15), 2015
pp. 579-588

S. Choi, S. DiPaola

Seoul, South Korea


https://ivizlab.org/wp-content/uploads/sites/2/2017/09/eva2013bT.jpg

How a Painter Paints: An Interdisciplinary Understanding of Embodied Creativity
Conference Proceedings: Electronic Visualisation and the Arts, 2013
pp. 127-134

S. Choi, S. DiPaola

London, UK

British Computer Society


https://ivizlab.org/wp-content/uploads/sites/2/2017/09/ijcgt2011T.jpg

Expressive Animated Character Sequences Using Knowledge-based Painterly Rendering
Journal Article: International Journal of Computer Games Technology, International Journal of Computer Games Technology, 2011
Vol. 2011, Article ID 164949, 7 pages

H. Seifi, S. DiPaola, A. Arya

Face, Portrait, Mask: Using a Parameterised System to Explore Synthetic Face Space
Conference Proceedings: Electronic Visualisation in Arts and Culture, 2010
pp 213-227

S. DiPaola

Springer


https://ivizlab.org/wp-content/uploads/sites/2/2017/09/leonardo2009T.jpg

Rembrandt’s textural agency: A shared perspective in visual art and science
Journal Article: Leonardo, 2010
Vol 43, No 3, pp 145-151

S. DiPaola, C. Riebe, J. Enns

MIT Press


https://ivizlab.org/wp-content/uploads/sites/2/2017/09/vision2009T.jpg

Following The Masters: Viewer Gaze is Directed by Relative Detail in Painted Portraits
Journal Article: Journal of Vision, 2009
Vol 9, No 8, pp 368 (abstract)

C. Riebe, S. DiPaola, J. Enns

Research

Deep Learning AI Creativity For Visuals / Words

Using Cognitive Science as a basis for our work, we attempt to model aspects of human creativity in AI. Specially we are using Neural Networks (and evolutionary systems) in the form of Deep Learning, CNNs, RNNs and other modern techniques to model aspects of human expression and creativity.


Cognitive (AI) Based Abstraction

What is abstraction? Can you use AI techniques to model the semantics of an idea, object, or entity, where that understanding allows for abstraction of the meaning? We use several AI techniques including genetic programming, Neural Nets and Deep Learning to explore abstraction in its many forms. Mainly here in the visual and narrative arts.


Painterly NPR Project

Portrait artists and painters in general have over centuries developed, a little understood, intuitive and open methodology that exploits cognitive mechanisms in the human perception and visual system.


Rembrandt / Vision Science Work

Using new visual computer modelling techniques, we show that artists use vision based techniques (lost and found edges, center of focus techniques) to guide the eye path of the viewer through their paintings in significant ways.