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This textbook offers advanced content on computer vision (basic content can be found in its prerequisite textbook, “2D Computer Vision: Principles, Algorithms and Applications”), including the basic principles, typical methods and practical techniques. It is intended for graduate courses on related topics, e.g. Computer Vision, 3-D Computer Vision, Graphics, Artificial Intelligence, etc. The book is mainly based on my lecture notes for several undergraduate and graduate classes I have offered over the past several years, while a number of topics stem from my research publications co-authored with my students. This book takes into account the needs of learners with various professional backgrounds, as well as those of self-learners. Furthermore, it can be used as a reference guide for practitioners and professionals in related fields. To aid in comprehension, the book includes a wealth of self-test questions (with hints and answers). On the one hand, these questions help teachers to carry out online teaching and interact with students during lectures; on the other, self-learners can use them to assess whether they have grasped the key content.

The amount of digitized information available on the Internet, in digital libraries, and other forms of information systems grows at an exponential rate, while becoming more complex and more dynamic. As a consequence, information organization, information retrieval and the presentation of retrieval results have become more and more difficult. Information visualization offers a unique method to reveal hidden patterns and contextual information in a visual presentation and allows users to seek information in an intuitive way. Jin Zhang provides a systematic explanation of the latest advancements in information retrieval visualization from both theoretical and practical perspectives. He reviews the main approaches and techniques available in the field, explains theoretical relationships between information retrieval and information visualization, and presents major information retrieval visualization algorithms and models. He then takes a detailed look at the theory and applications of information retrieval visualization for Internet traffic analysis, and Internet information searching and browsing. The author also addresses challenges such as ambiguity, metaphorical applications, and system evaluation in information retrieval visualization environments. Finally, he compares these information retrieval visualization models from the perspectives of visual spaces, semantic frameworks, projection algorithms, ambiguity, and information retrieval, and discusses important issues of information retrieval visualization and research directions for future exploration. Readers of this book will gain an in-depth understanding of the current state of information retrieval visualization. They will be introduced to existing problems for researchers and professionals, along with technical and theoretical findings and advances made by leading researchers. The book also provides practical details for the implementation of an information retrieval visualization system.