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Game Design For Free-To-Play Live Service

by Stanislav Stankovic

~~67,58€~~ 60,82€ 10% OFF

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 "Game Design for Free to Play Live Service" is the ultimate guide to designing successful free-to-play mobile games. With case studies and expert insights, this book is essential reading for any game developer looking to create a hit mobile game.
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Virtual Reality And Virtual Environments In 10 Lectures

by Stanislav Stankovic

59,61€ + 10% CARD

 The book is based on the material originally developed for the course on Virtual Reality, which the author was teaching at Tampere University of Technology, as well as course on Virtual Environments that the author had prepared for the University for Advancing Studies at Tempe, Arizona. This original purpose has influenced the structure of this book as well as the depth to which we explore the presented concepts. Therefore, our intention in this book is to give an introduction into the important issues regarding a series of related concepts of Virtual Reality, Augmented Reality, and Virtual Environments. We do not attempt to go into any of these issues in depth but rather outline general principles and discuss them in a sense broad enough to provide sufficient foundations for a further study. In other words, we aim to provide a set of keywords to the reader in order give him a good starting point from which he could go on and explore any of these issues in detail. Table of Contents: Preface / Acknowledgments / Lecture 1--Introduction / Lecture 2--History of VR and Current Applications / Lecture 3--Human Senses / Lecture 4--VR Systems / Lecture 5--User Experience, Human Computer Interaction and UI / Lecture 6--Input Devices and Tracking / Lecture 7--Displays / Lecture 8--Networked VR / Lecture 9--Augmented Reality / Lecture 10--VE and Video Games / Bibliography / Author''s Biography / Index
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Contextual Analysis Of Videos

by Dorothy Monekosso, How-Lung Eng, Myo Thida e Paolo Remagnino

37,09€ + 10% CARD

 Video context analysis is an active and vibrant research area, which provides means for extracting, analyzing and understanding behavior of a single target and multiple targets.
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Wavelet Image Compression

by William Pearlman

33,11€ + 10% CARD

 Table of Contents: Introduction / Characteristics of the Wavelet Transform / Generic Wavelet-based Coding Systems / The FBI Fingerprint Image Compression Standard / Set Partition Embedded Block (SPECK) Coding / Tree-based Wavelet Transform Coding Systems / Rate Control for Embedded Block Coders / Conclusion
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Image Understanding Using Sparse Representations

by Andreas Spanias, Jayaraman J. Thiagarajan, Karthikeyan Natesan Ramamurthy e Pavan Turaga

37,09€ + 10% CARD

 Frameworks that enhance the performance of sparse models in such applications by imposing constraints based on the prior discriminatory information and the underlying geometrical structure, and kernelizing the sparse coding and dictionary learning methods are presented.
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Image Fusion In Remote Sensing - Conventional And Deep Learning Approaches

by Arian Azarang e Nasser Kehtarnavaz

33,11€ + 10% CARD

 Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.
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Super Resolution Of Images And Video

by Aggelos K. Katsaggelos, Javier Mateos e Rafael Molina

37,09€ + 10% CARD

 SR techniques are being applied to a variety of fields, such as obtaining improved still images from video sequences (video printing), high definition television, high performance color Liquid Crystal Display (LCD) screens, improvement of the quality of color images taken by one CCD, video surveillance, remote sensing, and medical imaging.
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Dictionary Learning In Visual Computing

by Baoxin Li e Qiang Zhang

59,61€ + 10% CARD

 The last few years have witnessed fast development on dictionary learning approaches for a set of visual computing tasks, largely due to their utilization in developing new techniques based on sparse representation. Compared with conventional techniques employing manually defined dictionaries, such as Fourier Transform and Wavelet Transform, dictionary learning aims at obtaining a dictionary adaptively from the data so as to support optimal sparse representation of the data. In contrast to conventional clustering algorithms like K-means, where a data point is associated with only one cluster center, in a dictionary-based representation, a data point can be associated with a small set of dictionary atoms. Thus, dictionary learning provides a more flexible representation of data and may have the potential to capture more relevant features from the original feature space of the data. One of the early algorithms for dictionary learning is K-SVD. In recent years, many variations/extensionsof K-SVD and other new algorithms have been proposed, with some aiming at adding discriminative capability to the dictionary, and some attempting to model the relationship of multiple dictionaries. One prominent application of dictionary learning is in the general field of visual computing, where long-standing challenges have seen promising new solutions based on sparse representation with learned dictionaries. With a timely review of recent advances of dictionary learning in visual computing, covering the most recent literature with an emphasis on papers after 2008, this book provides a systematic presentation of the general methodologies, specific algorithms, and examples of applications for those who wish to have a quick start on this subject.
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Recognition Of Humans And Their Activities Using Video

by Amit K. Roy-Chowdhury, Rama Chellappa e S. Kevin Zhou

33,11€ + 10% CARD

 The recognition of humans and their activities from video sequences is currently a very active area of research because of its applications in video surveillance, design of realistic entertainment systems, multimedia communications, and medical diagnosis. In this lecture, we discuss the use of face and gait signatures for human identification and recognition of human activities from video sequences. We survey existing work and describe some of the more well-known methods in these areas. We also describe our own research and outline future possibilities. In the area of face recognition, we start with the traditional methods for image-based analysis and then describe some of the more recent developments related to the use of video sequences, 3D models, and techniques for representing variations of illumination. We note that the main challenge facing researchers in this area is the development of recognition strategies that are robust to changes due to pose, illumination, disguise, and aging. Gait recognition is a more recent area of research in video understanding, although it has been studied for a long time in psychophysics and kinesiology. The goal for video scientists working in this area is to automatically extract the parameters for representation of human gait. We describe some of the techniques that have been developed for this purpose, most of which are appearance based. We also highlight the challenges involved in dealing with changes in viewpoint and propose methods based on image synthesis, visual hull, and 3D models. In the domain of human activity recognition, we present an extensive survey of various methods that have been developed in different disciplines like artificial intelligence, image processing, pattern recognition, and computer vision. We then outline our method for modeling complex activities using 2D and 3D deformable shape theory. The wide application of automatic human identification and activity recognition methods will require the fusionof different modalities like face and gait, dealing with the problems of pose and illumination variations, and accurate computation of 3D models. The last chapter of this lecture deals with these areas of future research.
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Combating Bad Weather Part Ii - Fog Removal From Image And Video

by Abhishek Kumar Tripathi e Sudipta Mukhopadhyay

30,46€ + 10% CARD

 Presented fog removal algorithm is independent of the intensity of the fog, thus even in the case of the heavy fog presented algorithm performs well. Qualitative and quantitative results confirm that the presented fog removal algorithm outperformed previous algorithms in terms of perceptual quality, color fidelity and execution time.
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Biomedical Image Analysis - Segmentation

by Nilanjan Ray e Scott Acton

37,09€ + 10% CARD

 The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation
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Multimodal Learning Toward Micro-Video Understanding

by Liqiang Nie, Meng Liu e Xuemeng Song

72,86€ + 10% CARD

 Thus, it is highly desirable to develop an effective scheme for the high-order micro-video understanding.Micro-video understanding is, however, non-trivial due to the following challenges:(1) how to represent micro-videos that only convey one or few high-level themes or concepts;
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Combating Bad Weather Part I - Rain Removal From Video

by Abhishek Kumar Tripathi e Sudipta Mukhopadhyay

46,36€ + 10% CARD

 Current vision systems are designed to perform in normal weather condition. However, no one can escape from severe weather conditions. Bad weather reduces scene contrast and visibility, which results in degradation in the performance of various computer vision algorithms such as object tracking, segmentation and recognition. Thus, current vision systems must include some mechanisms that enable them to perform up to the mark in bad weather conditions such as rain and fog. Rain causes the spatial and temporal intensity variations in images or video frames. These intensity changes are due to the random distribution and high velocities of the raindrops. Fog causes low contrast and whiteness in the image and leads to a shift in the color. This book has studied rain and fog from the perspective of vision. The book has two main goals: 1) removal of rain from videos captured by a moving and static camera, 2) removal of the fog from images and videos captured by a moving single uncalibrated camera system. The book begins with a literature survey. Pros and cons of the selected prior art algorithms are described, and a general framework for the development of an efficient rain removal algorithm is explored. Temporal and spatiotemporal properties of rain pixels are analyzed and using these properties, two rain removal algorithms for the videos captured by a static camera are developed. For the removal of rain, temporal and spatiotemporal algorithms require fewer numbers of consecutive frames which reduces buffer size and delay. These algorithms do not assume the shape, size and velocity of raindrops which make it robust to different rain conditions (i.e., heavy rain, light rain and moderate rain). In a practical situation, there is no ground truth available for rain video. Thus, no reference quality metric is very useful in measuring the efficacy of the rain removal algorithms. Temporal variance and spatiotemporal variance are presented in this book as no reference quality metrics. An efficient rain removal algorithm using meteorological properties of rain is developed. The relation among the orientation of the raindrops, wind velocity and terminal velocity is established. This relation is used in the estimation of shape-based features of the raindrop. Meteorological property-based features helped to discriminate the rain and non-rain pixels. Most of the prior art algorithms are designed for the videos captured by a static camera. The use of global motion compensation with all rain removal algorithms designed for videos captured by static camera results in better accuracy for videos captured by moving camera. Qualitative and quantitative results confirm that probabilistic temporal, spatiotemporal and meteorological algorithms outperformed other prior art algorithms in terms of the perceptual quality, buffer size, execution delay and system cost. The work presented in this book can find wide application in entertainment industries, transportation, tracking and consumer electronics. Table of Contents: Acknowledgments / Introduction / Analysis of Rain / Dataset and Performance Metrics / Important Rain Detection Algorithms / Probabilistic Approach for Detection and Removal of Rain / Impact of Camera Motion on Detection of Rain / Meteorological Approach for Detection and Removal of Rain from Videos / Conclusion and Scope of Future Work / Bibliography / Authors' Biographies
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Light Field Sampling

by Cha Zhang e Tsuhan Chen

37,09€ + 10% CARD

 Light field is one of the most representative image-based rendering techniques that generate novel virtual views from images instead of 3D models. The light field capture and rendering process can be considered as a procedure of sampling the light rays in the space and interpolating those in novel views. As a result, light field can be studied as a high-dimensional signal sampling problem, which has attracted a lot of research interest and become a convergence point between computer graphics and signal processing, and even computer vision. This lecture focuses on answering two questions regarding light field sampling, namely how many images are needed for a light field, and if such number is limited, where we should capture them. The book can be divided into three parts. First, we give a complete analysis on uniform sampling of IBR data. By introducing the surface plenoptic function, we are able to analyze the Fourier spectrum of non-Lambertian and occluded scenes. Given the spectrum,we also apply the generalized sampling theorem on the IBR data, which results in better rendering quality than rectangular sampling for complex scenes. Such uniform sampling analysis provides general guidelines on how the images in IBR should be taken. For instance, it shows that non-Lambertian and occluded scenes often require a higher sampling rate. Next, we describe a very general sampling framework named freeform sampling. Freeform sampling handles three kinds of problems: sample reduction, minimum sampling rate to meet an error requirement, and minimization of reconstruction error given a fixed number of samples. When the to-be-reconstructed function values are unknown, freeform sampling becomes active sampling. Algorithms of active sampling are developed for light field and show better results than the traditional uniform sampling approach. Third, we present a self-reconfigurable camera array that we developed, which features a very efficient algorithm for real-time rendering andthe ability of automatically reconfiguring the cameras to improve the rendering quality. Both are based on active sampling. Our camera array is able to render dynamic scenes interactively at high quality. To the best of our knowledge, it is the first camera array that can reconfigure the camera positions automatically.
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Tensor Voting - A Perceptual Organization Approach To Computer Vision And Machine Learning

by Gerard Medioni e Philippos Mordohai

37,09€ + 10% CARD

 This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California.
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Real-Time Image And Video Processing - From Research To Reality

by Mark Gamadia e Nasser Kehtarnavaz

39,74€ + 10% CARD

 This book presents an overview of the guidelines and strategies for transitioning an image or video processing algorithm from a research environment into a real-time constrained environment.
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Joint Source-Channel Video Transmission

by Aggelos Katsaggelos e Fan Zhai

37,09€ + 10% CARD

 This book deals with the problem of joint source-channel video transmission, i.e., the joint optimal allocation of resources at the application layer and the other network layers, such as data rate adaptation, channel coding, power adaptation in wireless networks, quality of service (QoS) support from the network, and packet scheduling, for efficient video transmission. Real-time video communication applications, such as videoconferencing, video telephony, and on-demand video streaming, have gained increased popularity. However, a key problem in video transmission over the existing Internet and wireless networks is the incompatibility between the nature of the network conditions and the QoS requirements (in terms, for example, of bandwidth, delay, and packet loss) of real-time video applications. To deal with this incompatibility, a natural approach is to adapt the end-system to the network. The joint source-channel coding approach aims to efficiently perform content-aware cross-layerresource allocation, thus increasing the communication efficiency of multiple network layers. Our purpose in this book is to review the basic elements of the state-of-the-art approaches toward joint source-channel video transmission for wired and wireless systems. In this book, we present a general resource-distortion optimization framework, which is used throughout the book to guide our discussions on various techniques of joint source-channel video transmission. In this framework, network resources from multiple layers are assigned to each video packet according to its level of importance. It provides not only an optimization benchmark against which the performance of other sub-optimal systems can be evaluated, but also a useful tool for assessing the effectiveness of different error control components in practical system design. This book is therefore written to be accessible to researchers, expert industrial R&D engineers, and university students who are interested in the cutting edge technologies in joint source-channel video transmission. Contents: Introduction / Elements of a Video Communication System / Joint Source-Channel Coding / Error-Resilient Video Coding / Channel Modeling and Channel Coding / Internet Video Transmission / Wireless Video Transmission / Conclusions
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Mpeg-4 Beyond Conventional Video Coding

by Deepak S Turaga, Mihaela Schaar e Thomas Stockhammer

33,11€ + 10% CARD

 An important merit of the MPEG-4 video standard is that it not only provided tools and algorithms for enhancing the compression efficiency of existing MPEG-2 and H.263 standards but also contributed key innovative solutions for new multimedia applications such as real-time video streaming to PCs and cell phones over Internet and wireless networks, interactive services, and multimedia access. Many of these solutions are currently used in practice or have been important stepping-stones for new standards and technologies. In this book, we do not aim at providing a complete reference for MPEG-4 video as many excellent references on the topic already exist. Instead, we focus on three topics that we believe formed key innovations of MPEG-4 video and that will continue to serve as an inspiration and basis for new, emerging standards, products, and technologies. The three topics highlighted in this book are object-based coding and scalability, Fine Granularity Scalability, and error resiliencetools. This book is aimed at engineering students as well as professionals interested in learning about these MPEG-4 technologies for multimedia streaming and interaction. Finally, it is not aimed as a substitute or manual for the MPEG-4 standard, but rather as a tutorial focused on the principles and algorithms underlying it.
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Remote Sensing Image Processing

by Devis Tuia, Gustavo Camps-Valls, Jesus Malo, Luis Gómez-Chova e Sandra Jiménez

37,09€ + 10% CARD

 Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / Classification / Spectral Mixture Analysis / Estimation of Physical Parameters
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Biomedical Image Analysis - Tracking

by Nilanjan Ray e Scott T. Acton

37,09€ + 10% CARD

 In biological and medical imaging applications, tracking objects in motion is a critical task. This book describes the state-of-the-art in biomedical tracking techniques. We begin by detailing methods for tracking using active contours, which have been highly successful in biomedical applications. The book next covers the major probabilistic methods for tracking. Starting with the basic Bayesian model, we describe the Kalman filter and conventional tracking methods that use centroid and correlation measurements for target detection. Innovations such as the extended Kalman filter and the interacting multiple model open the door to capturing complex biological objects in motion. A salient highlight of the book is the introduction of the recently emerged particle filter, which promises to solve tracking problems that were previously intractable by conventional means. Another unique feature of Biomedical Image Analysis: Tracking is the explanation of shape-based methods for biomedical image analysis. Methods for both rigid and nonrigid objects are depicted. Each chapter in the book puts forth biomedical case studies that illustrate the methods in action.
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The Structure And Properties Of Color Spaces And The Representation Of Color Images

by Eric Dubois

37,09€ + 10% CARD

 This lecture describes the author's approach to the representation of color spaces and their use for color image processing. The lecture starts with a precise formulation of the space of physical stimuli (light). The model includes both continuous spectra and monochromatic spectra in the form of Dirac deltas. The spectral densities are considered to be functions of a continuous wavelength variable. This leads into the formulation of color space as a three-dimensional vector space, with all the associated structure. The approach is to start with the axioms of color matching for normal human viewers, often called Grassmann's laws, and developing the resulting vector space formulation. However, once the essential defining element of this vector space is identified, it can be extended to other color spaces, perhaps for different creatures and devices, and dimensions other than three. The CIE spaces are presented as main examples of color spaces. Many properties of the color space are examined. Once the vector space formulation is established, various useful decompositions of the space can be established. The first such decomposition is based on luminance, a measure of the relative brightness of a color. This leads to a direct-sum decomposition of color space where a two-dimensional subspace identifies the chromatic attribute, and a third coordinate provides the luminance. A different decomposition involving a projective space of chromaticity classes is then presented. Finally, it is shown how the three types of color deficiencies present in some groups of humans leads to a direct-sum decomposition of three one-dimensional subspaces that are associated with the three types of cone photoreceptors in the human retina. Next, a few specific linear and nonlinear color representations are presented. The color spaces of two digital cameras are also described. Then the issue of transformations between different color spaces is addressed. Finally, these ideas are applied to signal and system theory for color images. This is done using a vector signal approach where a general linear system is represented by a three-by-three system matrix. The formulation is applied to both continuous and discrete space images, and specific problems in color filter array sampling and displays are presented for illustration. The book is mainly targeted to researchers and graduate students in fields of signal processing related to any aspect of color imaging.
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Modern Image Quality Assessment

by Alan C. Bovik e Zhou Wang

37,09€ + 10% CARD

 This Lecture book is about objective image quality assessmentâ€"where the aim is to provide computational models that can automatically predict perceptual image quality.

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