Article

Feature Guided Texture Synthesis (FGTS) for artistic style transfer

Authors:

Hock Soon SeahAuthors Info & Claims

DIMEA '07: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts

Pages 44 - 49

https://doi.org/10.1145/1306813.1306830

Published: 19 September 2007 Publication History

Abstract

Artistic images and paintings can be regarded as a composition of content and style. The aim of artistic style transfer is to synthesize a stylized image with content of source image but novel style from style example. Based on texture synthesis, a novel Feature Guided Texture Synthesis (FGTS) algorithm for artistic style transfer is proposed in this paper. Compared with existing example-based methods, the content of a source image is better defined in FGTS with a feature field generated from the source image. Though the style is modelled with low-level statistical features, the style transfer process is guided with the feature field which incorporates style and content during synthesis process. Moreover, a modified L neighborhood distance metric is developed to provide better measures of perceptual similarity. Results and comparisons are given to demonstrate that FGTS is an effective method for artistic style transfer.

References

[1]

J. S. D. Bonet. Multiresolution sampling procedure for analysis and synthesis of texture images. In SIGGRAPH 97 Conference Proceedings, pages 361--368, 1997.

Digital Library

[2]

G. Borgefors. Hierarchical chamfer matching: a parametric edge matching algorithm. In IEEE Trans. Pattern Analysis and Machine Intelligence 10., pages 849--865, 1988.

Digital Library

[3]

A. Efros and W. T. Freeman. Image quilting for texture synthesis and transfer. In Proceedings of SIGGRAPH 2001, pages 341--346, 2001.

Digital Library

[4]

A. Efros and T. Leung. Texture synthesis by non-parametric sampling. In Proceedings of ICCV, pages 1033--1038, 1999.

Digital Library

[5]

W. T. Freeman, T. R. Jones, and E. Pasztor. Example-based super-resolution. In IEEE Computer Graphics and Applications, pages 56--65, 2002.

Digital Library

[6]

A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin. Image analogies. In Proceedings of SIGGRAPH 2001, pages 327--340, 2001.

Digital Library

[7]

V. Kwatra, A. Schodl, I. Essa, G. Turk, and A. Bobick. Graphcut textures: Image and video synthesis using graph cuts. In Proceedings of SIGGRAPH 2003, pages 277--286, 2003.

Digital Library

[8]

L. Liang, C. Liu, Y. Q. Xu, B. Guo, and H. Y. Shum. Real-time texture synthesis by patch-based sampling. In ACM Transactions on Graphics (TOG), pages 127 -- 150, 2001.

Digital Library

[9]

M. Mignotte. Bayesian rendering with non-parametric multiscale prior model. In Proceedings of ICPR02, 2002.

Digital Library

[10]

V. Ostromoukhov and R. D. Hersch. Artistic screening. In Proceedings of SIGGRAPH '95, pages 219--228, 1995.

Digital Library

[11]

J. D. Powell. The theory of radial basis function approximation. In Cambridge University Numerical Analysis Report, 1990.

[12]

C. Soler, M. P. Cani, and A. Angelidis. Hierarchical pattern mapping. In ACM Siggraph, pages 673--680, 2002.

Digital Library

[13]

J. B. Tenenbaum and W. T. Freeman. Separating Style and Content with Bilinear Models. Neural Computation, 12(6):1247--1283, 2000.

Digital Library

[14]

O. Veryovka. Animation with threshold textures. In Graphics Interface (GI'02), 2002.

[15]

O. Veryovka and J. Buchanan. Comprehensive Halftoning of 3D Scenes. Computer Graphics Forum, 18(3):13--22, 1999.

[16]

O. Veryovka and J. Buchanan. Texture Based Dither Matrices. Computer Graphics Forum, 19(1):51--64, 2000.

[17]

L. Wei and M. Levoy. Fast texture synthesis using tree-structured vector quantization. In SIGGRAPH 2000 Conference Proceedings, pages 479--488, 2000.

Digital Library

[18]

Q. Wu and Y. Yu. Feature matching and deformation for texture synthesis. In Proceedings of SIGGRAPH 2004, 2004.

Digital Library

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Published In

cover image ACM Conferences

DIMEA '07: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts

September 2007

212 pages

ISBN:9781595937087

DOI:10.1145/1306813

Conference Chairs:
Kevin Kok Wai Wong
Murdoch University, Australia
,
Lance Fung
Murdoch University, Australia
,
Peter Cole
Murdoch University, Australia

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

IFIP Specialist Group on Entertainment Computing
IEEE Western Australia Section
Murdoch University
Department of Industry and Resources
Nokia
ACM: Association for Computing Machinery
SIGCHI Singapore

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 September 2007

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DIMEA07

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ACM

DIMEA07: Second International Conference on Digital Interactive Media in Entertainment and Arts

September 19 - 21, 2007

Perth, Australia

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Overall Acceptance Rate 59 of 77 submissions, 77%

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Cited By

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https://doi.org/10.1186/s40561-023-00287-1
Azuaje GLiew KEpure EYada SWakamiya SAramaki E(2023)Visualyre: multimodal album art generation for independent musiciansPersonal and Ubiquitous Computing10.1007/s00779-023-01724-127:5(1861-1872)Online publication date: 15-May-2023
https://doi.org/10.1007/s00779-023-01724-1
Varghese DBartindale TMontague KBaillie Smith MOlivier P(2022)Supporting Real-time Peer-Mentoring of Rural VolunteersProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517598(1-13)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517598
Azuaje GLiew KEpure EYada SWakamiya SAramaki E(2021)Visualyre: Multimodal visualization of lyricsProceedings of the 16th International Audio Mostly Conference10.1145/3478384.3478420(130-134)Online publication date: 1-Sep-2021
https://dl.acm.org/doi/10.1145/3478384.3478420
Park SSeo KNoh J(2020)Neural crossbreedACM Transactions on Graphics10.1145/3414685.341779739:6(1-15)Online publication date: 27-Nov-2020
https://dl.acm.org/doi/10.1145/3414685.3417797
Jing YYang YFeng ZYe JYu YSong M(2020)Neural Style Transfer: A ReviewIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.292133626:11(3365-3385)Online publication date: 1-Nov-2020
https://doi.org/10.1109/TVCG.2019.2921336
Chen LYang JAmsaleg LHuet BLarson MGravier GHung HNgo CTsang Ooi W(2019)Recognizing the Style of Visual Arts via Adaptive Cross-layer CorrelationProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3350977(2459-2467)Online publication date: 15-Oct-2019
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Cai XSong B(2018)Semantic object removal with convolutional neural network feature-based inpainting approachMultimedia Systems10.1007/s00530-018-0585-x24:5(597-609)Online publication date: 1-Oct-2018
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Toyoura MAbe NMao X(2017)Scene-Aware Style Transferring Using GISTTransactions on Computational Science XXX10.1007/978-3-662-56006-8_3(29-49)Online publication date: 25-Oct-2017
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