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.
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Acknowledgments
We would like to thank the anonymous reviewers for their constructive comments. Xiaogang Jin was supported by the National Natural Science Foundation of China (61472351). Hanli Zhao was supported by Zhejiang Provincial Natural Science Foundation of China (LY15F020019).
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Yang, Y., Zhao, H., You, L. et al. Semantic portrait color transfer with internet images. Multimed Tools Appl 76, 523–541 (2017). https://doi.org/10.1007/s11042-015-3063-x
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DOI: https://doi.org/10.1007/s11042-015-3063-x