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检索条件"主题词=face recognition algorithm"

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PFW: a face database in the wild for studying face identification and verification in uncontrolled environment

PFW: a face database in the wild for studying face identific...

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2nd IAPR Asian Conference on Pattern recognition (ACPR)

作者： Wang, Hai Kang, Bongnam Kim, Daijin Pohang Univ Sci & Technol Dept Comp Sci & Engn Pohang 790784 South Korea

ISBN: (纸本)9781479921904

To train and evaluate various face recognition algorithms, quite many databases have been created. But most of them have been created under controlled conditions to study the specific variations of the face recognition problem. These variations include position, pose, lighting, background, camera quality and gender. But in real environment, there are also many applications in which there is little or no control over such variations. Labeled faces in the Wild, a database has been provided to study the latter, unconstrained face recognition problem. However, LFW is proposed for face verification problem, while we observe that a good verification performance cannot guarantee a good identification performance in real situation. Further, the face images in LFW are not sufficient for training to get a state of the art performance. PFW, POS faces in the Wild, on the contrast, is a large database which can be served both for evaluating face verification and face identification algorithms. Specifically, PFW contains a certain number of identities and each identity contains quite many images, thus make it suitable both for large scale supervised and semi supervised training. In this paper, we also provide some rules for evaluating the identification algorithm performance in real environment. To the best of our knowledge, our database is the first public available large face data set proposed for face identification in unconstrained environment.

关键词： Facial recognition face Database Verification personal identity face recognition algorithm face verification large database face Environments Controlled conditions

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Pose Independent face recognition by Localizing Local Binary Patterns via Deformation Components 22

Pose Independent Face Recognition by Localizing Local Binary...

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22nd International Conference on Pattern recognition (ICPR)

作者： Masi, Iacopo Ferrari, Claudio Del Bimbo, Alberto Medioni, Gerard Univ Florence MICC I-50121 Florence Italy Univ So Calif USC IRIS Lab Los Angeles CA USA

ISBN: (纸本)9781479952083

In this paper we address the problem of pose independent face recognition with a gallery set containing one frontal face image per enrolled subject while the probe set is composed by just a face image undergoing pose variations. The approach uses a set of aligned 3D models to learn deformation components using a 3D Morphable Model (3DMM). This further allows fitting a 3DMM efficiently on an image using a Ridge regression solution, regularized on the face space estimated via PCA. Then the approach describes each profile face by computing Local Binary Pattern (LBP) histograms localized on each deformed vertex, projected on a rendered frontal view. In the experimental result we evaluate the proposed method on the CMU Multi-PIE to assess face recognition algorithm across pose. We show how our process leads to higher performance than regular baselines reporting high recognition rate considering a range of facial poses in the probe set, up to +/- 45 degrees. Finally we remark that our approach can handle continuous pose variations and it is comparable with recent state-of-the-art approaches.

关键词： face recognition pose estimation regression analysis solid modelling 3D morphable model 3DMM CMU multiPIE LBP PCA continuous pose variations deformation components face image face recognition algorithm frontal face image gallery set local binary pattern histograms local binary pattern localization pose independent face recognition pose variations probe set ridge regression solution Deformable models face face recognition Probes Shape Solid modeling Three-dimensional displays Facial recognition entity modeling three-dimensional displays face recognition algorithm face face Deformable models pose estimation Probes LBP gene LBP principal components analysis Passive Cutaneous Anaphylaxis regression analysis

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Minimum Variance Method to Obtain the Best Shot in Video for face recognition

Minimum Variance Method to Obtain the Best Shot in Video for...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Ohzeki, Kazuo Aoyama, Ryota Hirakawa, Yutaka Shibaura Inst Technol Grad Sch Engn & Sci Koutou Ku 3-7-5 Toyosu Tokyo 108 Japan

ISBN: (纸本)9788360810668

This paper describes a face recognition algorithm using feature points of face parts, which is classified as a feature-based method. As recognition performance depends on the combination of adopted feature points, we utilize all reliable feature points effectively. From moving video input, well-conditioned face images with a frontal direction and without facial expression are extracted. To select such well-conditioned images, an iteratively minimizing variance method is used with variable input face images. This iteration drastically brings convergence to the minimum variance of 1 for a quarter to an eighth of all data, which means 3.75-7.5 Hz by frequency on average. Also, the maximum interval, which is the worst case, between the two values with minimum deviation is about 0.8 seconds for the tested feature point sample.

关键词： face recognition feature extraction image classification video signal processing face recognition algorithm feature points feature-based method frequency 3.75 Hz to 7.5 Hz minimum variance method moving video input variable input face images Electronic mail face face recognition Feature extraction Lighting Three-dimensional displays Yttrium

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Handling Illumination Variation in face recognition using Multiscale Retinex 8

Handling Illumination Variation in Face Recognition using Mu...

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International Conference on Advanced Computer Science and Information Systems (ICACSIS)

作者： Gunawan, Alexander A. S. Setiadi, Hendry Bina Nusantara Univ Sch Comp Sci Math Dept Jakarta Indonesia

ISBN: (纸本)9781509046294

face recognition has an important role in the age of information technology to improve comfort and security. Various face recognition algorithms are proven to be effective if done under a controlled environment. However, recognition performance will decrease significantly in the uncontrolled environment, for example caused by illumination variation. This paper discusses the approach to deal with varying illumination on face recognition with Multi-Scale Retinex method. To verify accuracy of this algorithm, it is used Principal Component Analysis (PCA) and Eulidean distance as algorithms to identify faces. In the experiments, Multi-Scale Retinex is also compared to other normalization methods, such as gamma correction, histogram equalization, Retinex, and Single-Scale Retinex. Based on several face recognition dataset, that is Extended Yale B, faces95, and Grimace, it can be concluded that the Multi-Scale Retinex method with one scale (Single-Scale Retinex) can properly normalize the illumination on the face image in term of speed and performance.

关键词： Lighting face recognition Training Reflectivity face Principal component analysis Image color analysis Facial recognition Lighting image colour analysis principal components analysis face face illumination information technology Reflectance Functional training face recognition algorithm multi-scale

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A Reference-Based Framework for Pose Invariant face recognition 11

A Reference-Based Framework for Pose Invariant Face Recognit...

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11th IEEE International Conference and Workshops on Automatic face and Gesture recognition (IEEE FG)

作者： Kafai, Mehran Eshghi, Kave An, Le Bhanu, Bir HP Labs Palo Alto CA 94304 USA Google Inc Mountain View CA 94043 USA Univ North Carolina Chapel Hill BRIC Chapel Hill NC 27599 USA Univ Calif Riverside Ctr Res Intelligent Syst Riverside CA 92521 USA

ISBN: (纸本)9781479960262

While face recognition technology has made significant progress in recent years, practical pose invariant face recognition remains a challenge. This paper describes a reference-based framework for solving this problem. The similarity between a face image and a set of reference individuals defines the reference-based descriptor for a face image. recognition is performed using the reference-based descriptors of probe and gallery images. The dimensionality of the face descriptor generated by the accompanying face recognition algorithm is reduced to the number of individuals in the reference set. The proposed framework is a generalization of previous recognition methods that use indirect similarity and reference-based descriptors. Results are shown on a combination of seven publicly available face databases (LFW, FEI, RaFD, FERET, facePix, CMU-PIE, and Multi-PIE). The proposed approach achieves good accuracy as compared to popular state-of-theart algorithms, and it is computationally efficient.

关键词： Facial recognition Descriptors face recognition algorithm face Invariant Frameworks Subject Headings

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Puzzling face Verification algorithms for Privacy Protection

Puzzling Face Verification Algorithms for Privacy Protection

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2014 IEEE International Workshop on Information Forensics and Security (WIFS)

作者： Bhattarai, Binod Mignon, Alexis Jurie, Frederic Furon, Teddy Univ Caen GREYC Caen France Inria Rennes France

ISBN: (纸本)9781479988822

This paper presents a new approach for de-identifying face images, i.e. for preventing automatic matching with public face collections. The overall motivation is to offer tools for privacy protection on social networks. We address this question by drawing a parallel between face de-identification and oracle attacks in digital watermarking. In our case, the identity of the face is seen as the watermark to be removed. Inspired by oracle attacks, we forge de-identified faces by superimposing a collection of carefully designed noise patterns onto the original face. The modification of the image is controlled to minimize the probability of good recognition while minimizing the distortion. In addition, these de-identified images are - by construction - made robust to counter attacks such as blurring. We present an experimental validation in which we de-identify LFW faces and show that resulting images are still recognized by human beings while deceiving a state-of-the-art face recognition algorithm.

关键词： face face images face verification Digital watermarking Privacy BLURRING Information retrieval systems-Teletext and videotex Watermarking Social Networks Human face recognition algorithm

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Class Attendance Management System Using face recognition 7

Class Attendance Management System Using Face Recognition

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7th International Conference on Computer and Communication Engineering (ICCCE)

作者： Salim, Omar Abdul Rhman Olanrewaju, Rashidah Funke Balogun, Wasiu Adebayo Int Islamic Univ Malaysia Dept Elect & Comp Engn Fac Engn Kuala Lumpur Malaysia Lagos State Polytech Dept Mechatron Ikorodu Nigeria

ISBN: (纸本)9781538669921

We are living in a world where everything is automated and linked online. The internet of things, image processing, and machine learning are evolving day by day. Many systems have been completely changed due to this evolve to achieve more accurate results. The attendance system is a typical example of this transition, starting from the traditional signature on a paper sheet to face recognition. This paper proposes a method of developing a comprehensive embedded class attendance system using facial recognition with controlling the door access. The system is based on Raspberry Pi that runs Raspbian (Linux) Operating System installed on micro SD card. The Raspberry Pi Camera, as well as a 5-inch screen, are connected to the Raspberry Pi. By facing the camera, the camera will capture the image then pass it to the Raspberry Pi which is programmed to handle the face recognition by implementing the Local Binary Patterns algorithm LBPs. If the student's input image matches with the trained dataset image the prototype door will open using Servo Motor, then the attendance results will be stored in the MySQL database. The database is connected to Attendance Management System (AMS) web server, which makes the attendance results reachable to any online connected web browser. The system has 95% accuracy with the dataset of 11 person images.

关键词： attendance system LBPs face recognition algorithm Raspberry Pi

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Embedded Door Access Control Systems Based on face recognition: A Survey

Embedded Door Access Control Systems Based on Face Recogniti...

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7th International Conference on Signal Processing and Communication Systems (ICSPCS)

作者： Al-Shebani, Qasim Premaratne, Prashan Vial, Peter Univ Wollongong Sch Elect & Comp & Telecommun Engn North Wollongong NSW 2522 Australia

ISBN: (纸本)9781479913190

The implementation of face recognition techniques in an embedded system is a very important aspect of various security applications, such as authorization identification in cash machines and door access for employee attendance. The purpose of this paper is to survey the existing hardware implementations of a face recognition system, particularly those who used for developing an embedded door access control system. This includes a brief discussion about face recognition algorithms and the hardware platforms outlining the importance of using a Field Programmable Gate Array (FPGA) device, which can be used to design an embedded door access control system. It is found that the success of any door access control system depends on the type of face recognition algorithm in the feature extraction phase of the face recognition system and the selected hardware device. Based on a comparison between different feature extraction algorithms, the use of a hybrid feature extraction technique can improve the accuracy of face recognition system. An efficient door access control system can be obtained using a FPGA device, which is preferable because of its technical characteristics of parallelism, re-programmability and very high speed, in the implementation of a face recognition system.

关键词： face recognition system access control system face recognition algorithm DOOR Field programmable gate arrays Facial recognition Feature extraction face recognition techniques Hardware Platform technical features Embedded systems

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THE CONTOURLET TRANSFROM AND SVM CLASSIFICATION FOR face recognition

THE CONTOURLET TRANSFROM AND SVM CLASSIFICATION FOR FACE REC...

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International Conference on Apperceiving Computing and Intelligence Analysis

作者： Wang, Yi Li, Jian-Ping Lin, Jie Liu, Lin Univ Elect Sci & Technol China Sch Engn & Comp Sci Chengdu 610054 Peoples R China

ISBN: (纸本)9781424434275

In this paper, we introduce a face recognition approach based on the contourlet transform and support vector machine, which takes technological advantages of both support vector machine and the contourlet transform for feature extraction. The contributions of this paper include the following aspects: (1) support vector machine is successfully applied to face recognition by using the contourlet transform as the face representation in face image processing phase;(2) the contourlet transform are used to represent a whole face in a computable dimensional space. The new method was evaluated with many experiments, and the experimental results show that our face recognition algorithm is effective and competitive.

关键词： The contourlet transform face recognition algorithm support vector machine (SVM)

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A face recognition system that simulates perception impairments of autistic children

A face recognition system that simulates perception impairme...

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2012 IEEE International Conference on Development and Learning and Epigenetic Robotics, ICDL 2012

作者： Wu, Horng Chen, Wen-Chun Mayer, N.M. Department of Electrical Engineering Nat'l. Chung Cheng University Min-Hsiung Chia-Yi Taiwan

ISBN: (纸本)9781467349635

We use a face recognition algorithm to model differences in perception between autistic and non autistic children. With our model it is possible to reproduce several phenomena of autism by assuming that autistic children lack the ability to abstract from horizontal invariants. In particular, we can explain why autistic children are able to better recognize faces from parts of the face while the overall recognition of faces is worse than in non autistic children. © 2012 IEEE.

关键词： Autistic Children face recognition system face recognition algorithm autism face senses Perception Facial recognition

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