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STUDY on DETECT STROKE SYMPTOMS USING FACE FEATURES
- Authors
- Umirzakova, S.; Whangbo, T.K.
- Issue Date
- 2018
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- drooping mouth detection; face feature analysis; forehead wrinkle detection; Stroke detection
- Citation
- 9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018, pp.429 - 431
- Journal Title
- 9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018
- Start Page
- 429
- End Page
- 431
- ISSN
- 0000-0000
- Abstract
- This paper present the early symptoms of stroke detection using face features. To achieve that, in this paper calculated wrinkles on forehead area, eye moving, mouth drooping, cheek line detection. Experimental results show that proposed stroke detection method achieved good results in this field. © 2018 IEEE.
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Collections - IT융합대학 > 컴퓨터공학과 > 1. Journal Articles
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Related Researcher
- Whangbo, Taeg Keun
- College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))