Harry Wechsler – författare
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6 produkter
6 produkter
Reliable Face Recognition Methods
System Design, Implementation and Evaluation
Inbunden, Engelska, 2006
1 098 kr
Skickas inom 10-15 vardagar
One of the grand challenges for computational intelligence is to understand how people process and recognize faces and to develop automated face recognition systems, one of the major biometric technologies today. Solving the face recognition problem will have a major scientific impact, as recognizing people is the first, and a critical step, towards building intelligent machines that can function in human environments. Reliable Face Recognition Systems is a state-of-the-art survey text that examines the evolution of face-recognition systems as they drive for superior reliability and describes methods being considered and tested for enhancing system design and implementation. Providing the required background and motivation, the book explores new directions in the field and offers specific guidance on the most promising venues for future R&D, as well as realistic performance evaluation. With its well-focused approach and clarity of presentation, this new text/reference is an excellent resource for computer scientists, computer engineers, and other professionals and researchers who need to learn about face recognition.In addition, it is ideally suited to students studying biometrics, pattern recognition, and human-computer interaction.
1 100 kr
Skickas inom 10-15 vardagar
One of the challenges for computational intelligence and biometrics is to understand how people process and recognize faces and to develop automated and reliable face recognition systems. Biometrics has become the major component in the complex decision making process associated with security applications. The many challenges addressed for face detection and authentication include cluttered environments, occlusion and disguise, temporal changes, robust training and open set testing.Reliable Face Recognition Methods seeks to comprehensively address the face recognition problem while gaining new insights from complementary fields of endeavor such as neurosciences, statistics, signal and image processing, computer vision, machine learning and data mining. This book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future research and development.Endorsements by: Ruud Bolle (IBM), John Daugman (Cambridge University, UK), David Zhang (Hong Kong Polytechnic University, China), Stan Li (Chinese Academy of Sciences, China), Tom Huang (University of Illinois, USA).
1 855 kr
Skickas inom 5-8 vardagar
Mobile biometrics - the use of physical and/or behavioral characteristics of humans to allow their recognition by mobile/smart phones - aims to achieve conventional functionality and robustness while also supporting portability and mobility, bringing greater convenience and opportunity for its deployment in a wide range of operational environments from consumer applications to law enforcement. But achieving these aims brings new challenges such as issues with power consumption, algorithm complexity, device memory limitations, frequent changes in operational environment, security, durability, reliability, and connectivity. Mobile Biometrics provides a timely survey of the state of the art research and developments in this rapidly growing area.Topics covered in Mobile Biometrics include mobile biometric sensor design, deep neural network for mobile person recognition with audio-visual signals, active authentication using facial attributes, fusion of shape and texture features for lip biometry in mobile devices, mobile device usage data as behavioral biometrics, continuous mobile authentication using user phone interaction, smartwatch-based gait biometrics, mobile four-fingers biometrics system, palm print recognition on mobile devices, periocular region for smartphone biometrics, and face anti-spoofing on mobile devices.
1 100 kr
Skickas inom 10-15 vardagar
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.
1 100 kr
Skickas inom 10-15 vardagar
Intelligent robotics has become the focus of extensiveresearch activity. This effort has been motivated by thewide variety of applications that can benefit from thedevelopments. These applications often involve mobilerobots, multiple robots working and interacting in the samework area, and operations in hazardous environments likenuclear power plants. Applications in the consumer andservice sectors are also attracting interest. Theseapplications have highlighted the importance of performance,safety, reliability, and fault tolerance.This volume is a selection of papers from a NATO AdvancedStudy Institute held in July 1989 with a focus on activeperception and robot vision. The papers deal with suchissues as motion understanding, 3-D data analysis, errorminimization, object and environment modeling, objectdetection and recognition, parallel and real-time vision,and data fusion. The paradigm underlying the papers is thatrobotic systems require repeated and hierarchicalapplication of the perception-planning-action cycle. Theprimary focus of the papers is the perception part of thecycle. Issues related to complete implementations are alsodiscussed.
1 068 kr
Skickas inom 10-15 vardagar
The NATO Advanced Study Institute From Statistics to Neural Networks, Theory and Pattern Recognition Applications took place in Les Arcs, Bourg Saint Maurice, France, from June 21 through July 2, 1993. The meeting brought to gether over 100 participants (including 19 invited lecturers) from 20 countries. The invited lecturers whose contributions appear in this volume are: L. Almeida (INESC, Portugal), G. Carpenter (Boston, USA), V. Cherkassky (Minnesota, USA), F. Fogelman Soulie (LRI, France), W. Freeman (Berkeley, USA), J. Friedman (Stanford, USA), F. Girosi (MIT, USA and IRST, Italy), S. Grossberg (Boston, USA), T. Hastie (AT&T, USA), J. Kittler (Surrey, UK), R. Lippmann (MIT Lincoln Lab, USA), J. Moody (OGI, USA), G. Palm (U1m, Germany), B. Ripley (Oxford, UK), R. Tibshirani (Toronto, Canada), H. Wechsler (GMU, USA), C. Wellekens (Eurecom, France) and H. White (San Diego, USA). The ASI consisted of lectures overviewing major aspects of statistical and neural network learning, their links to biological learning and non-linear dynamics (chaos), and real-life examples of pattern recognition applications. As a result of lively interactions between the participants, the following topics emerged as major themes of the meeting: (1) Unified framework for the study of Predictive Learning in Statistics and Artificial Neural Networks (ANNs); (2) Differences and similarities between statistical and ANN methods for non parametric estimation from examples (learning); (3) Fundamental connections between artificial learning systems and biological learning systems.