Innovative Technologies in Everyday Life (2016)
SpringerBriefs in Computer Science – Springer, 2016.
ISBN: 978-3-319-45697-3 (Print)
ISBN: 978-3-319-45699-7 (eBook)
This SpringerBrief provides an overview of contemporary innovative technologies and discusses their impact on our daily lives. Written from a technical perspective, and yet using language and terminology accessible to non-experts, it describes the technologies, the key players in each area, the most popular apps and services (and their pros and cons), as well as relevant usage statistics.
It is targeted at a broad audience, ranging from young gadget enthusiasts to senior citizens trying to get used to new devices and associated apps. By offering a structured overview of some of the most useful technologies current available, putting them in perspective, and suggesting numerous resources for further exploration, the book gives its readers a clear path for learning new topics through apps and web-based resources, making better choices of apps and websites for frequent use, using social networks effectively, protecting their privacy and staying safe online, and enjoying the opportunities brought about by these technological advances without being completely consumed by them.
Optical Flow and Trajectory Estimation Methods (2016)
Joel Gibson and Oge Marques
SpringerBriefs in Computer Science – Springer, 2016.
ISBN: 978-3-319-44940-1 (Print)
ISBN: 978-3-319-44941-8 (eBook)
This brief focuses on two main problems in the domain of optical flow and trajectory estimation: (i) The problem of finding convex optimization methods to apply sparsity to optical flow; and (ii) The problem of how to extend sparsity to improve trajectories in a computationally tractable way.
Beginning with a review of optical flow fundamentals, it discusses the commonly used flow estimation strategies and the advantages or shortcomings of each. The brief also introduces the concepts associated with sparsity including dictionaries and low rank matrices. Next, it provides context for optical flow and trajectory methods including algorithms, data sets, and performance measurement. The second half of the brief covers sparse regularization of total variation optical flow and robust low rank trajectories. The authors describe a new approach that uses partially-overlapping patches to accelerate the calculation and is implemented in a coarse-to-fine strategy. Experimental results show that combining total variation and a sparse constraint from a learned dictionary is more effective than employing total variation alone.
The brief is targeted at researchers and practitioners in the fields of engineering and computer science. It caters particularly to new researchers looking for cutting edge topics in optical flow as well as veterans of optical flow wishing to learn of the latest advances in multi-frame methods.
Driver Drowsiness Detection: Systems and Solutions (2014)
Aleksandar Čolić, Oge Marques, and Borko Furht
SpringerBriefs in Computer Science – Springer, 2014.
ISBN: 978-3-319-11534-4 (Print)
ISBN: 978-3-319-11535-1 (eBook)
This short book presents an overview of driver drowsiness detection systems and associated technologies and available solutions.
There is a substantial amount of evidence that suggests that driver drowsiness plays a significant role in road accidents, claiming the lives of thousands of people every year worldwide. This is a problem that needs to be seriously addressed. If vehicles become equipped with technology capable of detecting signs of driver drowsiness in a timely manner, many potential accidents will be prevented and many lives will be spared as a result.
In this monograph we define drowsiness and quantify its impact and significance, describe several different methods for measuring and detecting driver drowsiness, survey existing solutions, provide guidance on how they can be implemented, and discuss the associated technical challenges.
It is targeted at researchers and practitioners in the fields of engineering and computer science. It caters particularly to readers who want to develop their own methods and systems for driver drowsiness detection using computer vision, image processing, and machine learning techniques to detect driver drowsiness using behavioral cues (e.g., nodding of the head, yawning, or closing of the eyes for prolonged periods of time) and alert the driver accordingly.
Practical Image and Video Processing Using MATLAB (in Chinese) (2013)
Tsinghua University Press / John Wiley & Sons, 2013.
Visual Information Retrieval Using Java and LIRE (2013)
Mathias Lux and Oge Marques
Synthesis Lectures on Information Concepts, Retrieval, and Services – Morgan & Claypool, 2013.
ISBN: 978-1608459186 (Print)
Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories.
The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image’s visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image’s pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on.
In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images — an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR.
Practical Image and Video Processing Using MATLAB (2011)
Wiley-IEEE Press, 2011.
ISBN: 978-0-470-04815-3 (Print)
ISBN: 978-1-118-09347-4 (eBook)
Resources for all readers:
- Download all images (zip)
- Download all video clips (zip)
- Download all auxiliary MATLAB scripts and functions (zip)
- Download the OCR package for Tutorial 19.1 (zip)
- Sample materials:
Resources for instructors:
- Institution name
- Course name and code
- Semester that you’re scheduled to teach the course
- Current textbook
- Your official educational institution email address
This is the first book to combine image and video processing with a practical MATLAB-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation.
The book has been organized into two parts:
Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation.
Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB.
Extra features of this book include:
- More than 30 MATLAB tutorials, which consist of step-by-step guides to exploring image and video processing techniques using MATLAB
- Chapters supported by figures, examples, illustrative problems, and exercises
- Useful websites and an extensive list of bibliographical references
This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own.
Handbook of Video Databases (2003)
Borko Furht and Oge Marques (editors)
CRC Press, 2003.
ISBN: 978-0-849-37006-9 (Print)
ISBN: 978-0-203-48986-4 (eBook)
Technology has spurred the growth of huge image and video libraries, many growing into the hundreds of terabytes. As a result there is a great demand among organizations for the design of databases that can effectively support the storage, search, retrieval, and transmission of video data. Engineers and researchers in the field demand a comprehensive reference that will help them design and implement the most complex video database projects.
Handbook of Video Databases: Design and Applications presents a thorough overview in 45 chapters from more than 100 renowned experts in the field. This book provides the tools to help overcome the problems of storage, cataloging, and retrieval, by exploring content standardization and other content classification and analysis methods. The challenge of these complex problems make this book a must-have for video database practitioners in the fields of image and video processing, computer vision, multimedia systems, data mining, and many other diverse disciplines.
Content-Based Image and Video Retrieval (2002)
Oge Marques and Borko Furht
ISBN: 978-1-4020-7004-4 (Print)
ISBN: 978-1-4615-0987-5 (eBook)
Content-Based Image And Video Retrieval addresses the basic concepts and techniques for designing content-based image and video retrieval systems. It also discusses a variety of design choices for the key components of these systems. This book gives a comprehensive survey of the content-based image retrieval systems, including several content-based video retrieval systems. The survey includes both research and commercial content-based retrieval systems.
Content-Based Image And Video Retrieval includes pointers to two hundred representative bibliographic references on this field, ranging from survey papers to descriptions of recent work in the area, entire books and more than seventy websites. Finally, the book presents a detailed case study of designing MUSE–a content-based image retrieval system developed at Florida Atlantic University in Boca Raton, Florida.
Processamento Digital de Imagens (in Portuguese) (1999)
Processamento Digital de Imagens (in Portuguese)
Oge Marques and Hugo Vieira Neto
This book is currently out of print. You can download a free PDF containing the full text here.