A New Similarity Measurement For Face Recognition PDF Download
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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: 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: 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: Haibin Yan
Publisher: Springer
ISBN: 9789811044830
Category : Computers
Languages : en
Pages : 82
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Book Description
This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification. Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.
Author: Marian Moise
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Peter Corcoran
Publisher: BoD – Books on Demand
ISBN: 9533075155
Category : Computers
Languages : en
Pages : 266
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Book Description
As a baby, one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section presents an architecture for face recognition based on Hidden Markov Models; it is followed by an article on coding methods. The next section is devoted to 3D methods of face recognition and is followed by a section covering various aspects and techniques in video. Next short section is devoted to the characterization and detection of features in faces. Finally, you can find an article on the human perception of faces and how different neurological or psychological disorders can affect this.
Author: Danelle Alexis Wilbraham
Publisher:
ISBN:
Category : Face perception
Languages : en
Pages : 120
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Book Description
Abstract: Faces are important stimuli because they are critical for functioning in our social world. Namely, the face is the only reliably exposed body part that can be used to distinguish one person from another, and facial expressions convey emotions that facilitate social interaction. When studying faces as a vision scientist, one way to conceptualize face recognition is to think of faces as a specific class of object. Unlike other objects, faces are recognized on a subordinate level, where the primary task is to distinguish face A from face B. With other objects, the primary task is to distinguish among different classes of objects (e.g. cups vs. chairs). However, faces and other objects share the property of being three dimensional, and thus subject to an infinite number of viewing directions in addition to the multitudes of illumination conditions that might be presented. Two general classes of recognition models have emerged in the object recognition literature and are also applicable to face recognition. Models in the first class are typically based on features of some sort and rely on object-centered representations. The observer is conceptualized as a "feature extractor," extracting namable features from the image that are used to construct a single, generalizable representation of the object. The second class includes models that are based on properties of the image and rely on viewer-centered representations. These models characterize the observer as a "pixel pattern comparator," and posit many stored representations for each object. Many of the feature-based models in the object recognition literature rely on properties such as parallelism and co-termination, which are not useful in describing faces. Therefore, for the most part, models in the face recognition literature take a more image-based approach. One major difficulty with the research area is that studies claiming to provide psychophysical support for an image-based conception of human face recognition fail to measure the image differences. Because of this lack of control, it is impossible to ensure that the changes in the images themselves are independent of the judgments being made by the observers. The present study aimed to correct this problem by measuring the image differences and using these differences to construct conditions that, under an image-based regime, would facilitate or impair the ability to perform and identity judgment. Observers saw a face followed by two alternative faces and their task was simply to indicate which of the two alternatives shared the same identity as the first face. These alternatives could have a changed expression or a change in illumination conditions. In one condition, the match and the incorrect alternative (the foil) shared the same degree of image similarity with the sample. In the facilitating condition, the correct match was more similar to the sample face than was the foil. The impairment condition had matches that were less similar to the sample than the foil. If only the pixel intensity information is being used, one would predict good performance in the facilitation condition, and increasingly poor performance in the equal similarity and impairment conditions. Results showed that the manipulation of the image similarity had no appreciable effect on human performance. An image-based algorithm was trained to perform the same task and though it performed better than was predicted, the results did not correlate well with human performance. In light of these results, I conclude that popular approaches to face recognition are not sufficient descriptors of human face recognition, and suggest further research to confirm this conclusion. Alternative models and supporting data are also discussed.
Author: Peter Corcoran
Publisher: BoD – Books on Demand
ISBN: 9533073683
Category : Computers
Languages : en
Pages : 342
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Book Description
As a baby one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section on Statistical Face Models and Classifiers presents reviews and refinements of some well-known statistical models. The next section presents two articles exploring the use of Infrared imaging techniques and is followed by few articles devoted to refinements of classical methods. New approaches to improve the robustness of face analysis techniques are followed by two articles dealing with real-time challenges in video sequences. A final article explores human perceptual issues of face recognition.
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: Linda Bernice James
Publisher:
ISBN:
Category : Difference (Psychology)
Languages : en
Pages : 122
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Book Description
