RESEARCH ON FACE RECOGNITION ALGORITHM UNDER COMPLEX CONDITIONS
DOI:
https://doi.org/10.53555/eijas.v4i3.79Keywords:
Face recognition Bayes illumination, Bayes, IlluminationAbstract
This paper presents a face model based on Bayesian networks. The main idea is to establish a Bayesian network model based on the cognitive theory in daily life. The input of the network is the feature of facial organs on the face (that the organs have relevance in the model), and the output is the specific type of the face. Then the feature vectors of facial organs are extracted according to a certain algorithm. Finally, the specific categories are calculated by Gauss distribution and joint tree algorithm. Experimental results show the algorithm has excellent recognition effect.
References
. Moses Y, Adini Y and Ullman S. Face recognition:the problem of com-pensating for changes in illumination direction .In:Proceedings of ECCV-94,Stockholm,2-6 May 1994, Berlin:Springer-Verlag ,1994, 286-296.
. Adini Yael,Moses Yeal,Ullman Shimon.Face Recognition:The Problem of Compensating for Changes in Illumination Direction.IEEE transaction on pattern analysis and machine intelligence,1997,19 (7) :72 l-733.
. Phillips P J,Rauss,R Der S.,FERET (FacE REcognition Technology) Recognition Algorithm Development and Test Teport,ARL-TR-995,US Army Research Laboratory, 1996.
. Phillips P J,Grother P,Micheals R J,Blackburn D M,Tabassi E,Bone J M.FRVT 2002:Evaluation Report,Face Recognition Vendor Test 2002 Results,March 2003.
. Turk M and Pentland A. Face recognition using eigenfaces[C]. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition. 1991:586-591.
. Sakai T Nagao M,Kanade T.Computer Analysis and Classification Photographs of Human Face[C].Proc.1st USA-Japan Computer Conf.,55-62.
. Lades M, Vorbruggen J C.Buhmann J.Distortion invariant object recognition in the dynamic link architecture[J].IEEE Trans on omputers,1993,42(3):300-311:255-259.
. Bischel M and Pentland A. Human face recognition and face image set’s topology [J]. CVGIP: Image Understanding, 1994, 59(2):254-26l.
. Turk M and Pentland A.Face processing:Models for recognition[C].Proc.Intelligent Robots and Computer Vision VIII,SPIE,1989:22-32.
. Bellhumer P N, Hespanha J. Kriegman D.Eigenfaces VS fisherfaces:Recognition using class specific linear projection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,Special Issue on Face Recognition,1997,17(7):71 1-720.
. Penev P, Atick J.Local Feature Analysis:A General Statistical Theory for Object Representation[J]. Network: Computationin Neural Systems, 1996, 7(3), 477-500.
. Kass M, Witkin A, Terzopoulos D.Snakes:Active contour models[J].Joumal of Computer Vision,1 988,321-331.
. Xie X, Sudhakar R, Zhuang H.Improving eye feature extraction using deformable templates [J].Pattern Recognition.1994, 27(6):791-799.
. Volker Blanz,Thomas Vetter.A Morphable Model For the Synthesis of 3D Faces[C].Proceedings of the 26th annual conference on Computer graphics and interactive techniques,1999:187-194.
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