Earticle

초록

영어

A new facial feature position self-calibration method based on active computer vision is proposed in this paper to realize facial expression recognition. Compared with traditional method, the proposed method based on the extension focus thought only needs four linearly independent translational movements, one real rotational movement and one virtual rotational movement rather than the calibration reference object to realize the linear solutions orderly for internal reference matrix of camera, hand-eye relationship and feature point target depth. The experiment result shows that the proposed method is feasible and effective and the measurement errors of two-dimensional and three-dimensional feature points can be below 0.40mm, thus able to meet the industrial accuracy requirements.

목차

Abstract
 1. Introduction
 2. Calibration Principle
  2.1. Internal Reference Matrix of Camera
  2.2. Coordinate Relationship Transforamtion
  2.3. Extebsuib Focus
 3. Calibration of Hand-Eye Relationship Rotation Matrix
 4. Calibration of Internal Parameter Matrix of Camera
 5. Calibration of Feature Point target Depth
 6. Calibration of Facial Feature Relationship Translation Vector
 7. Simulation Experiment
  7.1. Simulation Environment and Data Source
  7.2. Result and Analysis
 References

키워드

저자

• Chen Chao [ Department of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China ]
• Huang Linlin [ Department of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605