1. What can caricatures tell us about face recognition processes?

2. They used face recognition to spot known terrorists.

3. Facial feature extraction is import part in face recognition.

4. A face recognition code, very useful.

5. Face recognition process is the use of wavelet methods(), we believe that useful.

6. A distance classifier has been built up for face recognition.

7. Face detection is the necessary earlier task in face recognition process, aiming at separating the face area from the background image.

8. It is for Face Recognition complete code can be used directly.

9. Face Recognition System code integrity, and can be used directly.

10. This was where language, face recognition and memory were mainly based.

11. To take a face memory test used in Laura Germine's new study, go to http://www.testmybrain.org/ and click on "Face Recognition, Emotion Perception, and Personality."

12. It is essential to realize the automatic face recognition system.

13. A novel face recognition method called null space discriminant projection embedding(NDPE) is proposed.

14. And in the feature extraction process, a new face recognition method based on CSVD and non Negative Matrix Factorization(NMF) is presented.

15. Face recognition technology has found wide applications such as human identification, security surveillance, intelligent interface, etc.

16. Similarly, automatic face recognition would solve the pesky problem of photograph labeling.

17. If successful, it will produce a deeper understanding of the human face recognition system.

18. Maybe only several dozen, judging from some of the work on temporal lobe neurons involved in face recognition.

18. Wish you will love and make progress everyday!

19. Models of face processing Finally, I want to move from cognitive models of word recognition to cognitive models of face recognition.

20. Using both experimental studies and computer simulation, existing theories of face recognition and learning in general will be evaluated and developed.

21. However, the implications of the work extend beyond theories of face recognition to theories of visual object and word recognition.

22. Multivariate analysis has many uses in pattern recognition . Take the face recognition as example.

23. The experimental results encourage the application of thermogram for human face recognition.

24. The main goal of this subject is realization of the automatic face recognition system.

25. They are used in everything from inspecting spark plugs to face recognition.

26. An efficient method which based on the face classification is being used to the face recognition.

27. In this paper, face detection and recognition technology has been studied to realize an automatic face recognition for video search system.

28. Absrtact: Non- negative matrix factorization(NMF)is a method of parts- based feature extraction, it has been already applied to face recognition successfully.

29. Lip is one of the most important facial features, and plays key roles in a variety of fields such as audio-visual speech, authentication, lip synchronization, face recognition, etc.

30. In recent months, he has devised an algorithmic approach to face recognition that has produced prodigious results.

31. Automatic Face Recognition ( AFR ) is challenging in image processing and analyzing.

32. A method of applying Non - negative Matrix Factorization ( NMF ) group strategy for face recognition is put forward.

33. At the same time, face recognition function can identify faces 5.

34. Joyface. net , is a entertainment sites dedicated to face recognition and portrait.

35. Aiming at improving correct recognition rate in this case, a face recognition approach correlative with face poses is presented.

36. For wavelet transformation can reduce dimension and interfere information , so improve face recognition rate and speed.

37. In face recognition process, the dominant area in face of information acquired was right facial area.

38. She says the late-blooming nature of face recognition may simply be a case of practice making perfect.

39. For this PhD programme I will be at high level mammalian visual system, e . g . face recognition.

40. A common classification, commonly used in face recognition, palmprint recognition , pattern recognition.

41. Automatic Face Recognition (AFR) aims at endowing computers with the ability to identify different human beings according to face images.

42. From experimental results, this improved face recognition algorithm has a better performance than the original one.

43. Experimental results show that the fusion method is valid in face recognition.

44. A complete automatic face recognition system consists of three main parts: detecting the human face from the image(), extracting the face feature and recognizing face.

45. The portrait images taken with the camera's Face Recognition function are organized neatly in the folder of the name registered with the camera.

46. The face recognition can be applied to: intelligent entrance guard system, computer security, machine vision, medical diagnostic system and 3-D animation etc.

47. Second half focuses on face recognition, an ecologically important instance of the general object recognition problem.

48. A new supervised kernel subspace method for face recognition was proposed.

49. Face recognition source code. Face Recognition System for the primary.

50. Automatic Face Recognition ( AFR ) includes two tasks: identification and verification.

51. An optical processor for high speed human face recognition is designed.

52. Based on the ORL face database for face recognition source code, the recognition rate of 88.

53. SVM that uses eigen faces for face recognition code integrity, has been tested.

54. This article applies AFR(automatic Face Recognition) to the online testing system, and sets up a framework model of the testing system implementation flow.

55. Twodimensional LDA face recognition matlab program, very easy to use.

56. Face Detection plays a key role in automatic face recognition.

57. It is the first step for any fully automatic face recognition system and has lots of applications.

58. So this paper presents a design which use the combination of RFID technology and face recognition technology for identity verification in access control system.

59. Not only that, the software also features an independent Face Recognition function that recognizes the faces in the picture stored in your PC to sort the photos by the face speedily.

60. While prior evidence had suggested that face recognition might be slow to mature, Germine said few scientists had suspected that it might continue building for so many years into adulthood.

61. "There are still tons of practical and other aspects of face recognition before we can use this core method to make a well-rounded system that works under a variety of conditions," he says.

62. Face contour extraction is a significant precondition of facial image analysis such as facial features detection and face recognition.

63. This paper presents a novel algorithm for quasi-frontal face recognition based on the wavelet decomposition technique and a multi-class Support Vector Machine (SVM) model.

64. Definition of facial feature extraction affects direct rate of face recognition.

65. Results The present results showed that, in facial race recognition, gender recognition and joint property recognition(), the key area of face recognition was eyebrow and eye.

66. Automatic human face recognition is attractive in pattern recognition and image procession. The human face is a complex pattern.

67. Include: neural networks, handwriting character recognition, fingerprint recognition, voice recognition, face recognition, expert systems.

68. Face contour extraction is the base of face recognition and the foundation of 3D face model reconstruction.

69. So this paper presents a solution which using face recognition technology for identity verification in remote login.

70. Objective To study face recognition rule of Chinese subjects during judging the differences of facial recognition of race, gender and their joint property.

71. The model is applied in face recognition and image segmentation approach using gradient operator is proposed to increase the recognition accuracy.

72. This paper proposes a face recognition algorithm based on the principle components analysis ( PCA ) reconstruction.

73. In 3 D face recognition field , binocular vision system is one of the primate step.

74. In this paper, biometrics has been studied and more attention been paid on face recognition ( FR ) .

75. Identification can be made by retinal or iris scanning, fingerprints, or face recognition.

76. An optical image recognition system based on the volume holographic storage technology is constructed. It is applied to an "electronic guard" system based on the real time human face recognition.

77. A face recognition source code, very useful. Thank you to use!

78. In the third part of this thesis, the algorithm of our automatic face recognition system is presented in details.

79. Automatic face recognition is one of the most important subject in the field of pattern recognition.

80. Face detection, face recognition, object identification, observation substrate recognition, statistical shape recognition, machine learning.

81. In the face recognition, important information not only exists in the picture element in two-order statistical property but also contains in the high-order statistical property.

82. An Automatic Face Recognition Method based on independent component analysis and Maximum Entropy Modeling is proposed in this paper.

83. This paper proposes a new algorithm to boost performance of probabilistic reasoning model(PRM) face recognition methods.