Books: VR, Neural Networks, and More
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Books: VR, Neural Networks, and More
22 March, 2019
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Top 10

Our next set of books features some great reads on Virtual Reality, Neural Networks, Cloth Simulation, and more.

Virtual Reality and Virtual Environments in 10 Lectures

This first book is based on the material originally developed for the course on Virtual Reality taught at Tampere University of Technology, as well as course on Virtual Environments prepared for the University for Advancing Studies at Tempe, Arizona. It gives an introduction to 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 for readers in order to establish a good starting point from which they could go on and explore any of these issues in detail.”

A Guide to Convolutional Neural Networks for Computer Vision

The next one will help you understand the theory behind CNNs and gain hands-on experience on the application of CNNs in computer vision. It is said to provide a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. “The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision.”

Virtual Material Acquisition and Representation for Computer Graphics

Have a look at a guide to the concepts, models, and technologies for realistic rendering of material appearance. The book provides a complete and thorough overview of reflectance models and acquisition setups, along with providing a selection of the available tools to explore, visualize, and render the reflectance data.

Extreme Value Theory-Based Methods for Visual Recognition

The fourth begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. “In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features.”

Cloth Simulation for Computer Graphics

The final book is focused on physics-based cloth simulation. Start with background information and a range of applications, continue with explanations of multiple cloth simulation techniques. “More specifically, we start with the most simple explicitly integrated mass-spring model and gradually work our way up to more complex and commonly used implicitly integrated continuum techniques in state-of-the-art implementations.” The book gives an intuitive explanation of the techniques and gives additional information on how to efficiently implement them on a computer.

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