Principles and Methods for Face Recognition and Face Modelling

Rawlinson, Tim; Bhalerao, Abhir; Wang, Li

doi:10.4018/978-1-60566-836-9.ch003

Cited by 9 publications

(3 citation statements)

References 24 publications

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“…For the multi-classification problem with k training samples, it is necessary to construct a classification hyperplane between class i and the remaining k-1 categories. The subclassifier is K-1 second-class discriminant RVM classifier, and the optimization problem corresponding to the i-th RVM classifier can be expressed by (1).…”

Section: One Against Rest Classificationmentioning

confidence: 99%

The Application of Face Recognition System

Wang¹

2022

Advances in Social Science, Education and Humanities Research

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With the rapid development of computers and the internet, information security is particularly important. In the past, identification is mainly used with passwords or ID cards, but it is easy to be stolen or forgotten. However face recognition systems can quickly and simply solve the problem, so currently, it begins to be widely used in various field. This passage will mainly introduce the application of face recognition system by reading a lot of literature. In the first section, the passage will provide the definition of face recognition system and its basic working principle. It is reported that the face recognition system has developed from simple rule-based recognition to mechanized automatic recognition. Afterwards, the application of face recognition system in various aspects will be introduced in this passage, it includes five broad applications in the financial field, education field, transportation field and public security field. In conclusion, now the world becomes more and more better because of the advance in science and technology, so face recognition is slowly recognized by people, and we also began to use it in different fields.

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Section: One Against Rest Classificationmentioning

confidence: 99%

The Application of Face Recognition System

Wang¹

2022

Advances in Social Science, Education and Humanities Research

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“…The components are forehead, left eyebrow, right eyebrow, left eye, right eye, nose, left cheek, right cheek, and mouth. Tim et al (5) proposed the principles and methods for face recognition and face modelling using adding the active shape model, skin textures. Yoshihisa et al (6) proposed the security management for mobile devise by face recognition using Bayes law.…”

Section: Introductionmentioning

confidence: 99%

Face Recognition System on Mobile using Similarity Data Mining Technique

Jareanpon

2015

Proceedings of the 3rd International Conference on Intelligent Systems and Image Processing 2015

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This paper proposed the mobile face recognition using data mining technique system. This system is able to help the police to find the suspects from the crime database using Smartphones. The police has to mark the 10 important points in face that are 2 of beginning of the eye lids, 2 of end of the eye lids, nose tip, 2 of center of pupils, 2 of end of mouths, and chin prominence. This system is divided into 2 main functions which are creating the database, and recognizing the face in database. From the recognition process, this research used the data mining technique called "K-nearest neighbor technique". Our experiment is tested on the 100 pictures students from

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“…Bayesian face recognition has better performance compared to eigenfaces [27]. Rawlinson et al [28] presents eigen and fisher face for face recognition. Feature based methods are robust to illumination and pose variations.…”

Section: Related Workmentioning

confidence: 99%