We use cookies on this website, you can read about them here. To use the website as intended please... ACCEPT COOKIES
UAL Research Online

Corpus-based visual synthesis: an approach for artistic stylization

Mital, Parag. K and Grierson, Mick and Smith, Tim (2013) Corpus-based visual synthesis: an approach for artistic stylization. In: SAP '13: Proceedings of the ACM Symposium on Applied Perception. Association For Computing Machinery, New York, U.S., pp. 51-58. ISBN 9781450322621

Type of Research: Book Section
Creators: Mital, Parag. K and Grierson, Mick and Smith, Tim

We investigate an approach to the artistic stylization of photographic images and videos that uses an understanding of the role of abstract representations in art and perception. We first learn a database of representations from a corpus of images or image sequences. Using this database, our approach synthesizes a target image or video by matching geometric representations in the target to the closest matches in the database based on their shape and color similarity. We show how changing a few parameters of the synthesis process can result in stylizations that represent aesthetics associated with Impressionist, Cubist, and Abstract Expressionist paintings. As the stylization process is fast enough to work in real-time, our approach can also be used to learn and synthesize the same camera image, even aggregating the database with each new video frame in real-time, a process we call "Memory Mosaicing". Finally, we report the user feedback of 21 participants using an augmented reality version of "Memory Mosaicing" in an installation called Augmented Reality Hallucinations, where the target scene and database came from a camera mounted on augmented reality goggles. This information was collected during an exhibition of 15,000 participants at the Digital Design Weekend at the Victoria and Albert Museum (co-located during the London Design Festival).

Official Website: http://dx.doi.org/10.1145/2492494.2492505
Publisher/Broadcaster/Company: Association For Computing Machinery
Your affiliations with UAL: Research Centres/Networks > Institute for Creative Computing
Date: 2013
Digital Object Identifier: 10.1145/2492494.2492505
Date Deposited: 29 Jul 2015 12:41
Last Modified: 14 Feb 2024 16:36
Item ID: 21077
URI: https://ualresearchonline.arts.ac.uk/id/eprint/21077

Repository Staff Only: item control page | University Staff: Request a correction