Books in Computer vision and pattern recognition

Group and Crowd Behavior for Computer Vision

1st Edition
April 10, 2017
Vittorio Murino + 3 more
English
Hardback
9 7 8 0 1 2 8 0 9 2 7 6 7
eBook
9 7 8 0 1 2 8 0 9 2 8 0 4

Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation of people. Part Two focuses on features and representations with the aim of recognizing the presence of groups and crowds in image and video data. It discusses low level processing methods to individuate when and where a group or crowd is placed in the scene, spanning from the use of people detectors toward more ad-hoc strategies to individuate group and crowd formations. Part Three discusses methods for analyzing the behavior of groups and the crowd once they have been detected, showing how to extract semantic information, predicting/tracking the movement of a group, the formation or disaggregation of a group/crowd and the identification of different kinds of groups/crowds depending on their behavior. The final section focuses on identifying and promoting datasets for group/crowd analysis and modeling, presenting and discussing metrics for evaluating the pros and cons of the various models and methods. This book gives computer vision researcher techniques for segmentation and grouping, tracking and reasoning for solving group and crowd modeling and analysis, as well as more general problems in computer vision and machine learning.

Discrete-Time Neural Observers

1st Edition
February 6, 2017
Alma Y Alanis + 1 more
English
Paperback
9 7 8 0 1 2 8 1 0 5 4 3 6
eBook
9 7 8 0 1 2 8 1 0 5 4 4 3

Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their application in meaningful areas, such as electric three phase induction motors and anaerobic process, which show the applicability of such designs. The proposed schemes can be employed for different applications beyond those presented. The book presents solutions for the state estimation problem of unknown nonlinear systems based on two schemes. For the first one, a full state estimation problem is considered; the second one considers the reduced order case with, and without, the presence of unknown delays. Both schemes are developed in discrete-time using recurrent high order neural networks in order to design the neural observers, and the online training of the respective neural networks is performed by Kalman Filtering.

Human Recognition in Unconstrained Environments

1st Edition
January 9, 2017
Maria De Marsico + 2 more
English
Hardback
9 7 8 0 0 8 1 0 0 7 0 5 1
eBook
9 7 8 0 0 8 1 0 0 7 1 2 9

Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting

1st Edition
December 5, 2016
Simone Balocco + 4 more
English
Hardback
9 7 8 0 1 2 8 1 1 0 1 8 8
eBook
9 7 8 0 1 2 8 1 1 0 1 9 5

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting.

Multi-Dimensional Summarization in Cyber-Physical Society

1st Edition
November 14, 2016
Hai Zhuge
English
Paperback
9 7 8 0 1 2 8 0 3 4 5 5 2
eBook
9 7 8 0 1 2 8 0 3 4 6 4 4

Text summarization has been studied for over a half century, but traditional methods process texts empirically and neglect the fundamental characteristics and principles of language use and understanding. Automatic summarization is a desirable technique for processing big data. This reference summarizes previous text summarization approaches in a multi-dimensional category space, introduces a multi-dimensional methodology for research and development, unveils the basic characteristics and principles of language use and understanding, investigates some fundamental mechanisms of summarization, studies dimensions on representations, and proposes a multi-dimensional evaluation mechanism. Investigation extends to incorporating pictures into summary and to the summarization of videos, graphs and pictures, and converges to a general summarization method. Further, some basic behaviors of summarization are studied in the complex cyber-physical-socia... space. Finally, a creative summarization mechanism is proposed as an effort toward the creative summarization of things, which is an open process of interactions among physical objects, data, people, and systems in cyber-physical-socia... space through a multi-dimensional lens of semantic computing. The author’s insights can inspire research and development of many computing areas.

Learning-Based Local Visual Representation and Indexing

1st Edition
March 23, 2015
Rongrong Ji + 4 more
English
Paperback
9 7 8 0 1 2 8 0 2 4 0 9 6
eBook
9 7 8 0 1 2 8 0 2 6 2 0 5

Learning-Based Local Visual Representation and Indexing, reviews the state-of-the-art in visual content representation and indexing, introduces cutting-edge techniques in learning based visual representation, and discusses emerging topics in visual local representation, and introduces the most recent advances in content-based visual search techniques.

Emerging Trends in Image Processing, Computer Vision and Pattern Recognition

1st Edition
December 9, 2014
Leonidas Deligiannidis + 1 more
English
Paperback
9 7 8 0 1 2 8 0 2 0 4 5 6
eBook
9 7 8 0 1 2 8 0 2 0 9 2 0

Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition discusses the latest in trends in imaging science which at its core consists of three intertwined computer science fields, namely: Image Processing, Computer Vision, and Pattern Recognition. There is significant renewed interest in each of these three fields fueled by Big Data and Data Analytic initiatives including but not limited to; applications as diverse as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering. These three core topics discussed here provide a solid introduction to image processing along with low-level processing techniques, computer vision fundamentals along with examples of applied applications and pattern recognition algorithms and methodologies that will be of value to the image processing and computer vision research communities. Drawing upon the knowledge of recognized experts with years of practical experience and discussing new and novel applications Editors’ Leonidas Deligiannidis and Hamid Arabnia cover; Many perspectives of image processing spanning from fundamental mathematical theory and sampling, to image representation and reconstruction, filtering in spatial and frequency domain, geometrical transformations, and image restoration and segmentation Key application techniques in computer vision some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication Pattern recognition algorithms including but not limited to; Supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms. How to use image processing and visualization to analyze big data.

Face Detection and Recognition on Mobile Devices

1st Edition
November 25, 2014
Haowei Liu
English
eBook
9 7 8 0 1 2 4 1 7 1 2 8 2

This hands-on guide gives an overview of computer vision and enables engineers to understand the implications and challenges behind mobile platform design choices. Using face-related algorithms as examples, the author surveys and illustrates how design choices and algorithms can be geared towards developing power-saving and efficient applications on resource constrained mobile platforms.

Digital Picture Processing

2nd Edition
Volume 2
June 28, 2014
Azriel Rosenfeld
English
eBook
9 7 8 1 4 8 3 2 9 4 7 8 0

Computer Science and Applied Mathematics: Digital Picture Processing, Second Edition, Volume 2 focuses on picture or image processing, which is concerned with the manipulation and analysis of pictures by computer. This book emphasizes the three major subareas in picture processing—digitizat... and compression; enhancement, restoration, and reconstruction; and matching, description, and recognition. This volume is organized into four chapters. Chapter 9 discusses registration and matching, while Chapter 10 considers segmentation into parts. The representation of parts and geometric property measurement is elaborated in Chapter 11. The last chapter is devoted to the non-geometric properties, picture descriptions, and models for classes of pictures. This publication is suitable for specialists and professionals working in the field of digital picture processing.

Pattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems

1st Edition
Volume 16
June 28, 2014
E.S. Gelsema + 1 more
English
eBook
9 7 8 1 4 8 3 2 9 7 8 4 2

The era of detailed comparisons of the merits of techniques of pattern recognition and artificial intelligence and of the integration of such techniques into flexible and powerful systems has begun.So confirm the editors of this fourth volume of Pattern Recognition in Practice, in their preface to the book.The 42 quality papers are sourced from a broad range of international specialists involved in developing pattern recognition methodologies and those using pattern recognition techniques in their professional work. The publication is divided into six sections: Pattern Recognition, Signal and Image Processing, Probabilistic Reasoning, Neural Networks, Comparative Studies, and Hybrid Systems, giving prospective users a feeling for the applicability of the various methods in their particular field of specialization.

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