Similarity Measures for Face Recognition PDF Download
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Author: Enrico Vezzetti
Publisher: Bentham Science Publishers
ISBN: 1681080443
Category : Computers
Languages : en
Pages : 108
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Book Description
Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.
Author: Enrico Vezzetti
Publisher: Bentham Science Publishers
ISBN: 1681080443
Category : Computers
Languages : en
Pages : 108
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Book Description
Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.
Author: Kadhim M Hashim
Publisher:
ISBN:
Category :
Languages : en
Pages : 138
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Book Description
This book introduces proposed new standards between digital images, which recorded the best results for the similarity between two images, although the images were exposed to a large amount of noise, and a peak signal to noise scale )PSNR)was used. The reference to noise as a measure of the noise ratio in the image processing and computer vision measuring image similarity among the two images becomes a fundamental case in many problems. In recent years, many images of similarity measures were proposed, most of them work with very particular kind of image distortions. Some of them are viable to a wider range of applications such as the structural similarity measure (SSIM) index. This chapter presents an introduction to image similarity, similarity methods and explains the most related works in detail; also it presents a literature survey for image similarity measures.
Author: Ron Kimmel
Publisher: Springer
ISBN: 3642193099
Category : Computers
Languages : en
Pages : 747
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Book Description
The four-volume set LNCS 6492-6495 constitutes the thoroughly refereed post-proceedings of the 10th Asian Conference on Computer Vision, ACCV 2009, held in Queenstown, New Zealand in November 2010. All together the four volumes present 206 revised papers selected from a total of 739 Submissions. All current issues in computer vision are addressed ranging from algorithms that attempt to automatically understand the content of images, optical methods coupled with computational techniques that enhance and improve images, and capturing and analyzing the world's geometry while preparing the higher level image and shape understanding. Novel geometry techniques, statistical learning methods, and modern algebraic procedures are dealt with as well.
Author: H.B. Mitchell
Publisher: Springer Science & Business Media
ISBN: 3642112161
Category : Technology & Engineering
Languages : en
Pages : 247
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Book Description
The purpose of this book is to provide a practical introduction to the th- ries, techniques and applications of image fusion. The present work has been designed as a textbook for a one-semester ?nal-year undergraduate, or ?r- year graduate, course in image fusion. It should also be useful to practising engineers who wish to learn the concepts of image fusion and apply them to practical applications. In addition, the book may also be used as a supp- mentary text for a graduate course on topics in advanced image processing. The book complements the author’s previous work on multi-sensor data [1] fusion by concentrating exclusively on the theories, techniques and app- cations of image fusion. The book is intended to be self-contained in so far as the subject of image fusion is concerned, although some prior exposure to the ?eld of computer vision and image processing may be helpful to the reader. Apart from two preliminary chapters, the book is divided into three parts.
Author: Aurélio Campilho
Publisher: Springer
ISBN: 3319415018
Category : Computers
Languages : en
Pages : 810
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Book Description
This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Image Analysis and Recognition, ICIAR 2016, held in Póvoa de Varzim, Portugal, in July 2016. The 79 revised full papers and 10 short papers presented were carefully reviewed and selected from 167 submissions. The papers are organized in the following topical sections: Advances in Data Analytics and Pattern Recognition with Applications, Image Enhancement and Restoration, Image Quality Assessment, Image Segmentation, Pattern Analysis and Recognition, Feature Extraction, Detection and Recognition, Matching, Motion and Tracking, 3D Computer Vision, RGB-D Camera Applications, Visual Perception in Robotics, Biometrics, Biomedical Imaging, Brain Imaging, Cardiovascular Image Analysis, Image Analysis in Ophthalmology, Document Analysis, Applications, and Obituaries. The chapter 'Morphological Separation of Clustered Nuclei in Histological Images' is published open access under a CC BY 4.0 license at link.springer.com.
Author: Miloš Oravec
Publisher: BoD – Books on Demand
ISBN: 9533070609
Category : Computers
Languages : en
Pages : 414
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Book Description
This book aims to bring together selected recent advances, applications and original results in the area of biometric face recognition. They can be useful for researchers, engineers, graduate and postgraduate students, experts in this area and hopefully also for people interested generally in computer science, security, machine learning and artificial intelligence. Various methods, approaches and algorithms for recognition of human faces are used by authors of the chapters of this book, e.g. PCA, LDA, artificial neural networks, wavelets, curvelets, kernel methods, Gabor filters, active appearance models, 2D and 3D representations, optical correlation, hidden Markov models and others. Also a broad range of problems is covered: feature extraction and dimensionality reduction (chapters 1-4), 2D face recognition from the point of view of full system proposal (chapters 5-10), illumination and pose problems (chapters 11-13), eye movement (chapter 14), 3D face recognition (chapters 15-19) and hardware issues (chapters 19-20).
Author: Marsyita Hanafi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This thesis presents techniques for detecting and recognizing faces under various imaging conditions. In particular, it presents a system that combines several methods for face detection and recognition. Initially, the faces in the images are located using the Viola-Jones method and each detected face is represented by a subimage. Then, an eye and mouth detection method is used to identify the coordinates of the eyes and mouth, which are then used to update the subimages so that the subimages contain only the face area. After that, a method based on Bayesian estimation and a fuzzy membership function is used to identify the actual faces on both subimages (obtained from the first and second steps). Then, a face similarity measure is used to locate the oval shape of a face in both subimages. The similarity measures between the two faces are compared and the one with the highest value is selected. In the recognition task, the Trace transform method is used to extract the face signatures from the oval shape face. These signatures are evaluated using the BANCA and FERET databases in authentication tasks. Here, the signatures with discriminating ability are selected and were used to construct a classifier. However, the classifier was shown to be a weak classifier. This problem is tackled by constructing a boosted assembly of classifiers developed by a Gentle Adaboost algorithm. The proposed methodologies are evaluated using a family album database.
Author: Harry Wechsler
Publisher: Springer Science & Business Media
ISBN: 3642722016
Category : Computers
Languages : en
Pages : 645
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Book Description
The NATO Advanced Study Institute (ASI) on Face Recognition: From Theory to Applications took place in Stirling, Scotland, UK, from June 23 through July 4, 1997. The meeting brought together 95 participants (including 18 invited lecturers) from 22 countries. The lecturers are leading researchers from academia, govemment, and industry from allover the world. The lecturers presented an encompassing view of face recognition, and identified trends for future developments and the means for implementing robust face recognition systems. The scientific programme consisted of invited lectures, three panels, and (oral and poster) presentations from students attending the AS!. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (i) human processing of face recognition and its relevance to forensic systems, (ii) face coding, (iii) connectionist methods and support vector machines (SVM), (iv) hybrid methods for face recognition, and (v) predictive learning and performance evaluation. The goals of the panels were to provide links among the lectures and to emphasis the themes of the meeting. The topics of the panels were: (i) How the human visual system processes faces, (ii) Issues in applying face recognition: data bases, evaluation and systems, and (iii) Classification issues involved in face recognition. The presentations made by students gave them an opportunity to receive feedback from the invited lecturers and suggestions for future work.
Author: Chengjun Liu
Publisher: Springer Science & Business Media
ISBN: 3642284574
Category : Technology & Engineering
Languages : en
Pages : 238
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Book Description
Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance. Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures.
Author: Antonio J. Colmenarez
Publisher: Springer Science & Business Media
ISBN: 140207803X
Category : Computers
Languages : en
Pages : 150
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Book Description
Computer vision algorithms for the analysis of video data are obtained from a camera aimed at the user of an interactive system. It is potentially useful to enhance the interface between users and machines. These image sequences provide information from which machines can identify and keep track of their users, recognize their facial expressions and gestures, and complement other forms of human-computer interfaces. Facial Analysis from Continuous Video with Applications to Human-Computer Interfaces presents a learning technique based on information-theoretic discrimination which is used to construct face and facial feature detectors. This book also describes a real-time system for face and facial feature detection and tracking in continuous video. Finally, this book presents a probabilistic framework for embedded face and facial expression recognition from image sequences. Facial Analysis from Continuous Video with Applications to Human-Computer Interfaces is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a secondary text for graduate-level students in computer science and engineering.
