Face segmentation using skin-color map in videophone applications
Abstract
This paper addresses our proposed method to automatically segment out a person's face from a given image that consists of a head-and-shoulders view of the person and a complex background scene. The method involves a fast, reliable, and effective algorithm that exploits the spatial distribution characteristics of human skin color. A universal skin-color map is derived and used on the chrominance component of the input image to detect pixels with skin-color appearance. Then, based on the spatial distribution of the detected skin-color pixels and their corresponding luminance values, the algorithm employs a set of novel regularization processes to reinforce regions of skin-color pixels that are more likely to belong to the facial regions and eliminate those that are not. The performance of the face-segmentation algorithm is illustrated by some simulation results carried out on various head-and-shoulders test images. The use of face segmentation for video coding in applications such as videotelephony is then presented. We explain how the face-segmentation results can be used to improve the perceptual quality of a videophone sequence encoded by the H.261-compliant coder.
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Corneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527 · see citing works
- Authors
- Chai, D., & Ngan, K. N.
- Affiliations
- The University of Western Australia (AU)
- ORCID
- Venue
- IEEE Transactions on Circuits and Systems for Video Technology
- Published
- 1999-06
- Volume
- 9
- Issue
- 4
- Pages
- 551-564
- ISSN
- 1051-8215 (ISSN-L)
- OpenAlex
- W2126178892
- Cited by
- 707
- References
- 24
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 7 · 2023: 8 · 2022: 11 · 2021: 13 · 2020: 13 · 2019: 16 · 2018: 18 · 2017: 26 · 2016: 34 · 2015: 36 · 2014: 47 · 2013: 39 · 2012: 51
- FWCI
- 20.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Circuits and Systems for Video Technology (publishedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Physical Sciences › Computer Science › Signal Processing › Video Coding and Compression Technologies
- Keywords
- face segmentation, skin color, video telephony, chrominance, luminance, regularization, video compression, H.261, perceptual quality
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