Quantitative evaluation of near regular texture synthesis algorithms

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

42 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 languageEnglish
Title of host publicationProceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Pages427-434
Number of pages8
DOIs
StatePublished - 22 Dec 2006
Event2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 - New York, NY, United States
Duration: 17 Jun 200622 Jun 2006

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1
ISSN (Print)1063-6919

Conference

Conference2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
CountryUnited States
CityNew York, NY
Period17/06/0622/06/06

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    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). [1640789] (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 1). https://doi.org/10.1109/CVPR.2006.233