Каталог ссылок
Компанец Дмитрий Олегович
По теме: "Разработка и исследование техники аутентификации/идентификации
сетевого пользователя на основе карактеристик асимметрии лица"
Порталы:
1. http://www.biometrics.ru
– информационный портал, посвященный биометрическим технологиям
и проблемам информационной безопасности, который призван объединить
профессионалов в этой области.
2. http://library.graphicon.ru:8080/catalog/62
– Анализ изображений лица. Библиотека ссылок на англоязычные статьи
с аннотациями.
3. http://daily.sec.ru
– Портал по безопаности. Здесь собрана самая полная и актуальная
информация по системам безопасности и средствам связи.
4. http://www.bezpeka.com/
– Украинский Центр информационной безопасности. Оказание услуг по
вопросам обеспечения информационной безопасности, разработка и поставка
программных средств защиты информации, оn-line библиотека, научно-исследовательская
деятельность.
5. http://www.bromba.com/faq/biofaqe.htm
– FAQ covering basic information, performance, implementation, and
security.
6. http://www.biomet.org/
– brings together a diverse and comprehensive selection of biometric
information. It provides an extensive web resource for biometric
news, products, companies and analysis.
7. http://www.biometricscatalog.org/
– A US-government sponsored database of information about biometric
technologies including research and evaluation reports, news articles,
vendors and consultants, government documents and legislative text.
8. http://www.biometrics.org/
– The Biometric Consortium serves as a focal point for research,
development, testing, evaluation, and application of biometric-based
personal identification/verification technology.
9. http://biometrics.cse.msu.edu/
– An extensive web resource for biometric news, products, companies
and analysis.
Сайты фирм и организаций:
1. http://www.biolink.ru/
– "Biolink" – системы биометрической идентификации. Сведения
о компании и ее продуктах для проведения биометрической аутентификации
личности. Описания решений. Каталог продуктов.
2. http://videoko.narod.ru/
– Интеллектуальная система видеонаблюдения и распознавания лиц «ВидеОко».
3. http://www.iss.ru/
– Интеллектуальные Системы Безопасности : Intelligent Security Systems
(ISS). Компания разрабатывает, производит и экспортирует интегрированные
интеллектуальные системы безопасности. Цифровые системы видеонаблюдения.
Компьютерные системы удаленного наблюдения…
4. http://www.goal.ru/
– Интеллектуальные системы охраны помещений и личности на базе персонального
компьютера. Системы цифровой видео и аудио записи, контроля доступа
на базе ПК, аппаратно-программные комплексы.
5. http://www.kodos.ru/
– Российский производитель полного спектра систем безопасности.
Торговая марка "КОДОС"– комплексные системы безопасности,
охранно–пожарные системы, системы контроля доступа, системы цифрового
видеонаблюдения.
6. http://www.iai.donetsk.ua/prod/ind.php3?l=r&pr=45
– Описание программного продукта REC2002. Система REC2002 способна
блокировать компьютер и открывать доступ только определенному пользователю
при его появлении перед видеокамерой.
7. http://www.itv.ru/products/face/
– Автоматизированная система видеозахвата лиц и идентификации личности
по изображению лица человека. Сканирует и запоминает лица всех людей,
проходящих мимо видеокамеры. Определяет идентичность входных данных,
представляющих собой изображения лица человека, осуществляет анализ,
инвариантный синтез образа объекта, сравнение с базой данных и распознавание.
Персональные страницы:
1. The
Face Detection Homepage by Dr. Robert Frischholz – This
page is focused on the task of detecting faces in arbitrary images.
2. D.
M. Gavrila – Publications Papers Articles Computer Vision
Image Processing.
3. Daphna
Weinshall – Computer and human vision, machine and perceptual
learning .
Отдельные статьи по теме:
1. Appearance factorization for facial expression analysis
– This paper addresses the issue of face representations for facial expression
analysis and synthesis.
2. A
New Kernel Direct Discriminant Analysis (KDDA) Algorithm for Face
Recognition – In this paper new kernel direct discriminant
analysis (KDDA) algorithm is proposedr. First, a recently advocated
direct linear discriminant analysis (DLDA) algorithm is overviewed..
3. Three-Dimensional
Face Recognition Using Surface Space Combinations –In
this paper a range of three-dimensional face recognition systems,
based on the fishersurface method developed in previous work, is
tested.
4. A
Bayesian Occlusion Model for Sequential Object Matching
– Article on the problem of locating instances of a known object
in a novel scene by matching the fiducial features of the object.
5. An
Illumination Invariant Face Recognition System for Access Control
using Video – Illumination and pose invariance are the
most challenging aspects of face recognition. In this paper a fully
automatic face recognition system that uses video information to
achieve illumination and pose robustness is described.
6. Exploratory
Sparse Models for Face Recognition – In this paper, a
class of sparse regularization methods are considered for developing
and exploring sparse classifiers for face recognition. The sparse
classification method aims to both select the most important features
and maximize the classification margin, in a manner similar to support
vector machines.
7. Using
Local Context To Improve Face Detection – Most face detection
algorithms locate faces by classifying the content of a detection
window iterating over all positions and scales of the input image.
Recent developments have accelerated this process up to real-time
performance at high levels of accuracy. However, even the best of
today's computational systems are far from being able to compete
with the detection capabilities of the human visual system.
8. Determining
pose of a human face from a single monocular image –
A new approach for estimating 3D head pose form a monocular image
is proposed. It employs general prior knowledge of face structure
and the corresponding geometrical constraints provided by the location
of vanishing point to determine pose of human faces.
9. On-line
Face Tracking Using a Feature Driven Level Set – An efficient
and general framework for the incorporation of statistical prior
information, based on a wide variety of detectable point features,
into level set based object tracking is presented.
10. Automated
Registration of 3D Faces using Dense Surface Models –
Dense surface models can be used to register unseen surfaces, using
an algorithm which is a hybrid of iterative closest-point (ICP)
and active shape model (ASM) fitting.
11. Face
Detection Based on Multiple Regression and Recognition Support Vector
Machines – This paper presents a novel approach to face
detection. A potential face pattern is first filtered by a Gaussian
derivative filter bank to generate a set of derivative images, which
are then transformed by the Angular Radial Transform (ART) to form
a compact set of representation feature vectors.
12. A
Multi-Stage Approach to Facial Feature Detection –A
novel shape constraint technique which is incorporated into a multi-stage
algorithm to automatically locate features on the human face is
discribed.
13. Face
Recognition Using Shape-from-shading – The sparse classification
method aims to both select the most important features and maximize
the classification margin, in a manner similar to support vector
machines.
14. Pose-Independent
Face Identification from Video Sequences – A scheme for
pose-independent face recognition is presented. An "unwrapped''
texture map is constructed from a video sequence using a texture-from-motion
approach, which is shown to be quite accurate. Simple lighting normalization
methods improve robustness to directional and/or varying lighting
conditions.
15. Recognition
of Facial Expressions in the Presence of Occlusion –
A new approach for the recognition of facial expressions from video
sequences in the presence of occlusion.
16. Markov
fields for recognition derived from facial texture error
– When attempting to code faces for modelling or recognition, estimates
of dimensions are typically obtained from an ensemble. These tend
to be significantly sub-optimal. Each face contains both predictable
and non–predictable qualities; only the predictable aspects are
useful for defining coding systems for other faces.
17. A
SOM Based Approach to Skin Detection with Application in Real Time
Systems – A large body of human image processing techniques
use skin detection as a first primitive for subsequent feature extraction.
Well established methods of colour modelling, such as histograms
and Gaussian mixture models have enabled the construction of suitably
accurate skin detectors.
18. Face
Verification via ECOC – A novel approach to face verification
based on the Error Correcting Output Coding (ECOC) classifier design
concept. In the training phase the client set if repeatedly divided
into two ECOC specified sub-sets (super-classes) to train a set
of binary classifiers. The output of the classifiers defines the
ECOC feature space, in which it is easier to separate transformed
patterns representing clients and imposters.
19. Recognising
Trajectories of Facial Identities Using Kernel Discriminant Analysis
– A comprehensive approach to address three challenging problems
in face recognition: modelling faces across multi-views, extracting
the non-linear discriminant features, and recognising faces dynamically
in a spatio-temporal context. A multi-view dynamic face model is
designed to extract the shape-and-pose-free facial texture patterns.
20. The
Face Detection Homepage by Dr. Robert Frischholz – This
page is focused on the task of detecting faces in arbitrary images.
21. Face
Databases – In this chapter we review 27 publicly available
databases for face recognition, face detection, and facial expression
analysis.
22. Multiple
Face Recognition from Omnidirectional Video – A very
important task in meeting understanding is to know who is attending
to the meeting and CAMEO's task is to infer people's identity from
video. In this paper, we present an approach to identify people
from an omnidirectional video sequence.
23. Face
Recognition Across Pose and Illumination – As the use
of face recognition systems expands towards less restricted environments,
the development of algorithms for view and illumination invariant
face recognition becomes important. However, the performance of
current algorithms degrades significantly when tested across pose
and illumination as documented in a number of evaluations.
24. Appearance-Based
Face Recognition and Light-Fields – Arguably the most
important decision to be made when developing an object recognition
algorithm is selecting the scene measurements or features on which
to base the algorithm. In appearance-based object recognition the
features are chosen to be the pixel intensity values in an image
of the object.
25. Facial
expression analysis – Handbook of face recognition,
26. Facial
Asymmetry Quantification for Expression Invariant Human Identification
– Investigation of facial asymmetry as a biometric under expression
variation.
27. A
Quantified Study of Facial Asymmetry in 3D Faces – With
the rapid development of 3D imaging technology, the wide usage of
3D surface information for research and applications is becoming
a convenient reality. This study is focused on a quantified analysis
of facial asymmetry of more than 100 3D human faces (individuals).
28. Human
Identification versus Expression Classification via Bagging on Facial
Asymmetry – We demonstrate a dual usage of quantified
facial asymmetry for (1) human identification under expression variations
and (2) expression classification across different human subjects.
Our experiments show the effectiveness of using statistical bagging
and feature subspace selection BEFORE applying classiffers such
as Linear Discriminant Analysis.
29. Illuminating
the Face – This paper presents a novel method for solving
the shape from shading problem in the restricted domain of human
faces.
30. Facial
Asymmetry: A New Biometric – In this work, we investigate
in depth the effect of statistical facial asymmetry measurement
as a biometric under expression variations.
31. Bimodal
expression of emotion by face and voice – In a series
of studies, we developed semi-automated methods of discriminating
emotion and para-linguistic communication in face and voice.
Прочее:
Вилла
"Куршавель" – Визитная карточка новой гостиницы в Симеизе.
Собственный проект.