The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Segmentation and tracking of faces in color images
Abstract
The authors present a new approach for automatically segmentation and tracking of faces in color images. Segmentation of faces is performed by evaluating color and shape information. First, skin-like regions are determined based on the color attributes hue and saturation. Then regions with elliptical shape are selected as face hypotheses. They are verified by searching for facial features in their interior. After a face is reliably detected it is tracked over time. Tracking is realized by using an active contour model. The exterior forces of the snake are defined based on color features. They push or pull snaxels perpendicular to the snake. Results for tracking are shown for an image sequence consisting of 150 frames.
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Metadata
- Authors
- Sobottka, K., & Pitas, I.
- Affiliations
- Aristotle University of Thessaloniki (GR)
- ORCID
- Pitas, I.
- Venue
- Proceedings of the Second International Conference on Automatic Face and Gesture Recognition
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-23
- Pages
- 236-241
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2122753056
- Cited by
- 157
- References
- 12
- Citations by year
- 2021: 2 · 2019: 1 · 2018: 1 · 2017: 2 · 2016: 3 · 2015: 1 · 2014: 2 · 2013: 5 · 2012: 4
- FWCI
- 14.26
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- 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 › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Keywords
- face segmentation, face tracking, color images, skin color detection, hue and saturation, facial feature detection, snakes, color features, video sequences
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