Semantic portrait color transfer with internet images
Authors: Yang, Y., Zhao, H., You, L., Tu, R., Wu, X. and Jin, X.
Journal: Multimedia Tools and Applications
Volume: 76
Issue: 1
Pages: 523-541
eISSN: 1573-7721
ISSN: 1380-7501
DOI: 10.1007/s11042-015-3063-x
Abstract:We present a novel color transfer method for portraits by exploring their high-level semantic information. First, a database is set up which consists of a collection of portrait images download from the Internet, and each of them is manually segmented using image matting as a preprocessing step. Second, we search the database using Face++ to find the images with similar poses to a given source portrait image, and choose one satisfactory image from the results as the target. Third, we extract portrait foregrounds from both source and target images. Then, the system extracts the semantic information, such as faces, eyes, eyebrows, lips, teeth, etc., from the extracted foreground of the source using image matting algorithms. After that, we perform color transfer between corresponding parts with the same semantic information. We get the final transferred result by seamlessly compositing different parts together using alpha blending. Experimental results show that our semantics-driven approach can generate better color transfer results for portraits than previous methods and provide users a new means to retouch their portraits.
https://eprints.bournemouth.ac.uk/33100/
Source: Scopus
Semantic portrait color transfer with internet images
Authors: Yang, Y., Zhao, H., You, L., Tu, R., Wu, X. and Jin, X.
Journal: MULTIMEDIA TOOLS AND APPLICATIONS
Volume: 76
Issue: 1
Pages: 523-541
eISSN: 1573-7721
ISSN: 1380-7501
DOI: 10.1007/s11042-015-3063-x
https://eprints.bournemouth.ac.uk/33100/
Source: Web of Science (Lite)
Semantic portrait color transfer with internet images
Authors: Yang, Y., Zhao, H., You, L., Tu, R., Wu, X. and Jin, X.
Journal: Multimedia Tools and Applications
Volume: 76
Issue: 1
Pages: 523-541
eISSN: 1573-7721
ISSN: 1380-7501
DOI: 10.1007/s11042-015-3063-x
Abstract:© 2015, Springer Science+Business Media New York. We present a novel color transfer method for portraits by exploring their high-level semantic information. First, a database is set up which consists of a collection of portrait images download from the Internet, and each of them is manually segmented using image matting as a preprocessing step. Second, we search the database using Face++ to find the images with similar poses to a given source portrait image, and choose one satisfactory image from the results as the target. Third, we extract portrait foregrounds from both source and target images. Then, the system extracts the semantic information, such as faces, eyes, eyebrows, lips, teeth, etc., from the extracted foreground of the source using image matting algorithms. After that, we perform color transfer between corresponding parts with the same semantic information. We get the final transferred result by seamlessly compositing different parts together using alpha blending. Experimental results show that our semantics-driven approach can generate better color transfer results for portraits than previous methods and provide users a new means to retouch their portraits.
https://eprints.bournemouth.ac.uk/33100/
Source: Manual
Preferred by: Lihua You
Semantic portrait color transfer with internet images
Authors: Yang, Y., Zhao, H., You, L., Tu, R., Wu, X. and Jin, X.
Journal: Multimedia Tools and Applications
Volume: 76
Issue: 1
Pages: 523-541
ISSN: 1380-7501
Abstract:We present a novel color transfer method for portraits by exploring their high-level semantic information. First, a database is set up which consists of a collection of portrait images download from the Internet, and each of them is manually segmented using image matting as a preprocessing step. Second, we search the database using Face++ to find the images with similar poses to a given source portrait image, and choose one satisfactory image from the results as the target. Third, we extract portrait foregrounds from both source and target images. Then, the system extracts the semantic information, such as faces, eyes, eyebrows, lips, teeth, etc., from the extracted foreground of the source using image matting algorithms. After that, we perform color transfer between corresponding parts with the same semantic information. We get the final transferred result by seamlessly compositing different parts together using alpha blending. Experimental results show that our semantics-driven approach can generate better color transfer results for portraits than previous methods and provide users a new means to retouch their portraits.
https://eprints.bournemouth.ac.uk/33100/
Source: BURO EPrints