ETRI-Knowledge Sharing Plaform

로그인

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 Robust Deep Age Estimation Method Using Artificially Generated Image Set
Cited 10 time in scopus Download 24 time Share share facebook twitter linkedin kakaostory
저자
장재윤, 전승혁, 김재홍, 윤호섭
발행일
201710
출처
ETRI Journal, v.39 no.5, pp.643-651
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.17.0117.0078
협약과제
16IC1200, 실환경하에서 인지센서네트워크(PSN) 기반 지능형 로봇의 사용자 정보(신원, 행동, 위치) 자동 추출 및 인식 기술 개발, 윤호섭
초록
Human age estimation is one of the key factors in the field of Human-Robot Interaction/Human-Computer Interaction (HRI/HCI). Owing to the development of deep-learning technologies, age recognition has recently been attempted. In general, however, deep learning techniques require a large-scale database, and for age learning with variations, a conventional database is insufficient. For this reason, we propose an age estimation method using artificially generated data. Image data are artificially generated through 3D information, thus solving the problem of shortage of training data, and helping with the training of the deep-learning technique. Augmentation using 3D has advantages over 2D because it creates new images with more information. We use a deep architecture as a pre-trained model, and improve the estimation capacity using artificially augmented training images. The deep architecture can outperform traditional estimation methods, and the improved method showed increased reliability. We have achieved state-of-the-art performance using the proposed method in the Morph- II dataset and have proven that the proposed method can be used effectively using the Adience dataset.
키워드
3d augmentation, Age estimation, Age regression, Convolutional neural network
KSP 제안 키워드
3D information, Age recognition, Art performance, Conventional Database, Convolution neural network(CNN), Deep architecture, Estimation method, Human age estimation, Human-Robot Interaction(HRI), Image data, Improved method
본 저작물은 공공누리 제4유형 : 출처표시 + 상업적 이용금지 + 변경금지 조건에 따라 이용할 수 있습니다.
제4유형