Kategoria BISAC: Computers >> Image Processing

Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book, the authors discuss...

Integrating Hadoop leverages the discipline of data integration and applies it to the Hadoop open-source software framework for storing data on clusters of commodity hardware. It is packed with the need-to-know for managers, architects, designers, and developers responsible for populating Hadoop in the enterprise, allowing you to harness big data and do it in such a way that the solution:

• Complies with (and even extends) enterprise standards
• Integrates seamlessly with the existing information infrastructure
• Fills a critical role...

Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recognize objects, track and recover their shape and spatial layout.

This unique text/reference presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of the three main areas in computer vision: reconstruction, registration, and recognition. The book provides an in-depth overview of challenging areas, in addition to descriptions of novel...

A principal aim of computer graphics is to generate images that look as real as photographs. Realistic computer graphics imagery has however proven to be quite challenging to produce, since the appearance of materials arises from complicated physical processes that are difficult to analytically model and simulate, and image-based modeling of real material samples is often impractical due to the high-dimensional space of appearance data that needs to be acquired.

This book presents a general framework based on the inherent coherency in the appearance data of materials to make...

This book studies how technological solutions can be used to alleviate the current state of legal systems, with their clogged up courtrooms and inefficient conflict resolution methods. It reviews the shortcomings and disadvantages of traditional and alternative conflict resolution methods and turns to Artificial Intelligence for problem-solving techniques and solutions. The book is divided into four parts. The first part presents a general and systematic analysis of the current state of the legal systems, identifying the main problems and their causes. It then moves on to present UM Court:...

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender...

Skeletonization: Theory, Methods and Applications is a comprehensive reference on skeletonization, written by the world's leading researchers in the field. The book presents theory, methods, algorithms and their evaluation, together with applications. Skeletonization is used in many image processing and computer vision applications such as shape recognition and analysis, shape decomposition and character recognition, as well as medical imaging for pulmonary, cardiac, mammographic applications.

Part I includes theories and methods unique to skeletonization. Part II includes...

The 39 revised full papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in topical sections on document analysis; pattern analysis and machine learning; image analysis; biomedical image analysis; biometrics.