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Head Pose Estimation Based On Detecting Facial Features

첫 페이지 보기
  • 발행기관
    보안공학연구지원센터(IJMUE) 바로가기
  • 간행물
    International Journal of Multimedia and Ubiquitous Engineering SCOPUS 바로가기
  • 통권
    Vol.10 No.3 (2015.03)바로가기
  • 페이지
    pp.311-322
  • 저자
    Hiyam Hatem, Zou Beiji, Raed Majeed, Jumana Waleed, Mohammed Lutf
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A241991

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원문정보

초록

영어
Head pose estimation is recently a more popular area of research. Challenging conditions, such as extreme pose, lighting, and occlusion, has historically hampered traditional, model-based methods. This paper presents a proposal of an integrated method for head pose estimation based on face detection and tracking. This method first locates certain facial features and based on their relative locations determine the head pose, the head pose estimated using coordinates of both eyes and a mouth relative to the nose as the origin of the coordinate system. The nose position is set up as the origin. The coordinates of the other parts defined from the origin, the distance between the face parts normalized so that the coordinates are independent of the image size. For facial feature detection from the detected face region, Haar-like feature utilized along with AdaBoost learning, the Adaboost learning algorithm used for creating optimized learning data. From the experiments, the proposed approach shows robustness in face and facial feature detection and eventually produces better results in estimating head pose rather than simply using Haar-like feature for both face and facial feature detection. The computational cost is low because it uses only those three points.

목차

Abstract
 1. Introduction
 2. Geometric Approaches
  2.1. Facial Feature Detection Using Haar-like Feature
  2.2. Adaboost for Feature Selection
  2.3. Attention Cascade Structure
 3. Head Pose Estimation
 4. Experimental Results
  4.1. Pointing’04 Database:
  4.2. ESOGU Face Detection Database
  4.3. Face Detection Dataset and Benchmark (FDDB)
 5. Conclusion
 Acknowledgements
 References

키워드

Face detection Head-pose estimation Geometric feature AdaBoost learning function

저자

  • Hiyam Hatem [ School of Information Science and Engineering, Central South University, Changsha, 410083, China, Department of Computer Science, Collage of Sciences, Baghdad University, Iraq ]
  • Zou Beiji [ School of Information Science and Engineering, Central South University, Changsha, 410083, China ]
  • Raed Majeed [ School of Information Science and Engineering, Central South University, Changsha, 410083, China ]
  • Jumana Waleed [ School of Information Science and Engineering, Central South University, Changsha, 410083, China ]
  • Mohammed Lutf [ Department of Electronics and information Engineering, Huazhong University of science and technology, Wuhan, China ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
  • 설립연도
    2006
  • 분야
    공학>컴퓨터학
  • 소개
    1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업

간행물

  • 간행물명
    International Journal of Multimedia and Ubiquitous Engineering
  • 간기
    월간
  • pISSN
    1975-0080
  • 수록기간
    2008~2016
  • 등재여부
    SCOPUS
  • 십진분류
    KDC 505 DDC 605

이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.10 No.3

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