Latent face model for across-media face recognition

Lv, Jiang-Jing; Huang, Jiashui; Zhou, Xiangdong; Zhou, Xi; Feng, Yong

doi:10.1016/j.neucom.2016.08.036

Cited by 4 publications

(1 citation statement)

References 30 publications

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“…In recent years, on the basis of careful research on feature face technology, domestic scholars have tried to combine feature extraction method based on feature face with various back-end classifiers and proposed various improved versions or extended algorithms. The main research contents include linear/nonlinear discriminant analysis [6], Bayesian probability model [7], support vector machine (SVM) [8], artificial neural network (NN) [9], and intra/intraclass dual subspace analysis method [10].…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Algorithm of Identity Authentication Based on Facial Features

Yuan

Wang

et al. 2021

Wireless Communications and Mobile Computing

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Identity recognition is a research hotspot in the information age. Nowadays, more and more occasions require identity recognition, especially in smart home. Identity recognition of the head of the household can avoid many troubles, such as home identification and network information authentication. Nowadays, in smart home identification, especially based on face recognition, system authentication is basically through feature matching. Although this method is convenient and quick to use, it lacks intelligence. Nowadays, for the make-up, facelift, posture, and other differences, the accuracy of the system is greatly reduced. In this paper, the face recognition method is used for identity authentication. Firstly, the AdaBoost learning algorithm is used to construct the face detection and eye detection classifier to realize the detection and localization of the face and eyes. Secondly, the two-dimensional discrete wavelet transform is used to extract facial features and construct a personal face dynamic feature database. Finally, an improved elastic template matching algorithm is used to establish an intelligent classification method for dynamic face elasticity models. The simulation shows that the proposed method can intelligently adapt to various environments without reducing the accuracy.

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Section: Introductionmentioning

confidence: 99%

Research on Intelligent Algorithm of Identity Authentication Based on Facial Features

Yuan

Wang

et al. 2021

Wireless Communications and Mobile Computing

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A novel facial image recognition method based on perceptual hash using quintet triple binary pattern

Tuncer

Doğan

Abdar

et al. 2020

Multimed Tools Appl

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Image classification (categorization) can be considered as one of the most breathtaking domains of contemporary research. Indeed, people cannot hide their faces and related lineaments since it is highly needed for daily communications. Therefore, face recognition is extensively used in biometric applications for security and personnel attendance control. In this study, a novel face recognition method based on perceptual hash is presented. The proposed perceptual hash is utilized for preprocessing and feature extraction phases. Discrete Wavelet Transform (DWT) and a novel graph based binary pattern, called quintet triple binary pattern (QTBP), are used. Meanwhile, the K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms are employed for classification task. The proposed face recognition method is tested on five well-known face datasets: AT&T, Face94, CIE, AR and LFW. Our proposed method achieved 100.0% classification accuracy for the AT&T, Face94 and CIE datasets, 99.4% for AR dataset and 97.1% classification accuracy for the LFW dataset. The time cost of the proposed method is O(nlogn). The obtained results and comparisons distinctly indicate that our proposed has a very good classification capability with short execution time.

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Systematic evaluation of deep face recognition methods

You

Han

et al. 2020

Neurocomputing

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Latent face model for across-media face recognition

Cited by 4 publications

References 30 publications

Research on Intelligent Algorithm of Identity Authentication Based on Facial Features

Research on Intelligent Algorithm of Identity Authentication Based on Facial Features

A novel facial image recognition method based on perceptual hash using quintet triple binary pattern

Systematic evaluation of deep face recognition methods

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