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Research on Vision-Based Emotion Cognition of Home Service Robot

Author: ZhuDingDing
Tutor: CaiZeSu
School: Harbin Institute of Technology
Course: Computer Science and Technology
Keywords: Affective Computing Object detection Facial Expression Recognition Feature library reconstruction Distance-based hash
CLC: TP242
Type: Master's thesis
Year: 2011
Downloads: 53
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Abstract


In the field of harmonious human-computer interaction and artificial intelligence , affective computing as a new direction of research , the growing attention . In this paper, a computer vision method for home service robot cognitive human emotions through facial expression recognition , and then react accordingly , it has emotional cognitive function . First, this paper AdaBoost algorithm to detect the face , eyes, nose , mouth , three organs . This first proposed by Paul Viola and Michael Jones object detection method has the characteristics of a real-time, robust and high accuracy rate . Detect human face for expression library and collection of images to be identification , used to detect other three organs of the face image anti-rotation correction . Rich characteristics compared with human face , eyes , nose, mouth , etc. contained in the face organ characterized more single its effective detection , it is difficult in a complex background , therefore the detection of the face organ is carried out in the face region . Then, expression feature extraction of face images using principal component analysis method to construct expression signature database , used to treat the measured expression image recognition . The expression zone positioning , not rough to the entire face area as the expression area , but to use the more accurate positioning face geometry characteristics of expression district . The innovation of this paper and the main contribution is to use Vassilis Athitsos distance hash the expression signature database refactoring , cutting expression feature size of the library , improve the efficiency of expression recognition . Finally , this paper uses K nearest neighbor classification of static image and a collection of images from the camera frame to complete the identification of the facial expression . In recognition of facial expression , family service robots will take appropriate action to reasonable interaction with people .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Robotics > Robot
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