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Detail
Journal Article
딥러닝 기반 고성능 얼굴 인식 기술 동향
- Issue Date
- 2018-08
- Citation
- 전자통신동향분석, v.33, no.4, pp.45-53
- ISSN
- 1225-6455
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- Korean
- Type
- Journal Article
- Abstract
- As face recognition (FR) has been well studied over the past decades, FR technology has been applied to many real-world applications such as surveillance and biometric systems. However, in the real-world scenarios, FR performances have been known to be significantly degraded owing to variations in face images, such as the pose, illumination, and low-resolution. Recently, visual intelligence technology has been rapidly growing owing to advances in deep learning, which has also improved the FR performance. Furthermore, the FR performance based on deep learning has been reported to surpass the perfor-mance level of human perception. In this article, we discuss deep-learning based high-performance FR technologies in terms of representative deep-learning based FR architectures and recent FR algorithms robust to face image variations (i.e., pose-robust FR, illumination-robust FR, and video FR). In addition, we investigate big face image datasets widely adopted for performance evaluations of the most recent deep-learning based FR algorithms.
- KSP Keywords
- Biometric system, Face Image, High performance, Image datasets, Performance evaluation, Real-world applications, deep learning(DL), face recognition, human perception, illumination-robust, low resolution
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
