Quantitative evaluation of near regular texture synthesis algorithms

Wen Chieh Lin; James Hays; Chenyu Wu; Vivek Kwatra; Yanxi Liu

doi:10.1109/CVPR.2006.233

Quantitative evaluation of near regular texture synthesis algorithms

Wen Chieh Lin
, James Hays
, Chenyu Wu
, Vivek Kwatra
, Yanxi Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

51 Scopus citations

Abstract

Near regular textures are pervasive in man-made and natural world. Their global regularity and local randomness pose new difficulties to the state of the art texture analysis and synthesis algorithms. We carry out a systematic comparison study on the performance of four texture synthesis algorithms on near-regular textures. Our results confirm that faithful near-regular texture synthesis remains a challenging problem for the state of the art general purpose texture synthesis algorithms. In addition, we provide comparison of human perception with computer evaluations on the quality of the texture synthesis results.

Original language	English (US)
Title of host publication	Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Pages	427-434
Number of pages	8
DOIs	https://doi.org/10.1109/CVPR.2006.233
State	Published - 2006
Event	2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 - New York, NY, United States Duration: Jun 17 2006 → Jun 22 2006

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume	1
ISSN (Print)	1063-6919

Other

Other	2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Country/Territory	United States
City	New York, NY
Period	6/17/06 → 6/22/06

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition

Access to Document

10.1109/CVPR.2006.233

Cite this

Lin, W. C., Hays, J., Wu, C., Kwatra, V., & Liu, Y. (2006). Quantitative evaluation of near regular texture synthesis algorithms. In Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 (pp. 427-434). Article 1640789 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 1). https://doi.org/10.1109/CVPR.2006.233

@inproceedings{3ec23c00472c4a488c8ea868b502976e,

title = "Quantitative evaluation of near regular texture synthesis algorithms",

abstract = "Near regular textures are pervasive in man-made and natural world. Their global regularity and local randomness pose new difficulties to the state of the art texture analysis and synthesis algorithms. We carry out a systematic comparison study on the performance of four texture synthesis algorithms on near-regular textures. Our results confirm that faithful near-regular texture synthesis remains a challenging problem for the state of the art general purpose texture synthesis algorithms. In addition, we provide comparison of human perception with computer evaluations on the quality of the texture synthesis results.",

author = "Lin, \{Wen Chieh\} and James Hays and Chenyu Wu and Vivek Kwatra and Yanxi Liu",

year = "2006",

doi = "10.1109/CVPR.2006.233",

language = "English (US)",

isbn = "0769525970",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

pages = "427--434",

booktitle = "Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006",

note = "2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 ; Conference date: 17-06-2006 Through 22-06-2006",

}

Lin, WC, Hays, J, Wu, C, Kwatra, V & Liu, Y 2006, Quantitative evaluation of near regular texture synthesis algorithms. in Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006., 1640789, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 427-434, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006, New York, NY, United States, 6/17/06. https://doi.org/10.1109/CVPR.2006.233

Quantitative evaluation of near regular texture synthesis algorithms. / Lin, Wen Chieh; Hays, James; Wu, Chenyu et al.
Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006. 2006. p. 427-434 1640789 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Quantitative evaluation of near regular texture synthesis algorithms

AU - Lin, Wen Chieh

AU - Hays, James

AU - Wu, Chenyu

AU - Kwatra, Vivek

AU - Liu, Yanxi

PY - 2006

Y1 - 2006

N2 - Near regular textures are pervasive in man-made and natural world. Their global regularity and local randomness pose new difficulties to the state of the art texture analysis and synthesis algorithms. We carry out a systematic comparison study on the performance of four texture synthesis algorithms on near-regular textures. Our results confirm that faithful near-regular texture synthesis remains a challenging problem for the state of the art general purpose texture synthesis algorithms. In addition, we provide comparison of human perception with computer evaluations on the quality of the texture synthesis results.

AB - Near regular textures are pervasive in man-made and natural world. Their global regularity and local randomness pose new difficulties to the state of the art texture analysis and synthesis algorithms. We carry out a systematic comparison study on the performance of four texture synthesis algorithms on near-regular textures. Our results confirm that faithful near-regular texture synthesis remains a challenging problem for the state of the art general purpose texture synthesis algorithms. In addition, we provide comparison of human perception with computer evaluations on the quality of the texture synthesis results.

UR - https://www.scopus.com/pages/publications/33845583381

UR - https://www.scopus.com/pages/publications/33845583381#tab=citedBy

U2 - 10.1109/CVPR.2006.233

DO - 10.1109/CVPR.2006.233

M3 - Conference contribution

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SN - 9780769525976

T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

SP - 427

EP - 434

BT - Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006

T2 - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006

Y2 - 17 June 2006 through 22 June 2006

ER -

Lin WC, Hays J, Wu C, Kwatra V, Liu Y. Quantitative evaluation of near regular texture synthesis algorithms. In Proceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006. 2006. p. 427-434. 1640789. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). doi: 10.1109/CVPR.2006.233

Quantitative evaluation of near regular texture synthesis algorithms

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All Science Journal Classification (ASJC) codes

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