Bibframe Work

This book presents a systematic study of visual pattern discovery, from unsupervised to semi-supervised manner approaches, and from dealing with a single feature to multiple types of features. Furthermore, it discusses the potential applications of discovering visual patterns for visual data analytics, including visual search, object and scene recognition. It is intended as a reference book for advanced undergraduates or postgraduate students who are interested in visual data analytics, enabling them to quickly access the research world and acquire a systematic methodology rather than a few isolated techniques to analyze visual data with large variations. It is also inspiring for researchers working in computer vision and pattern recognition fields. Basic knowledge of linear algebra, computer vision and pattern recognition would be helpful to readers.

Table Of Contents

1. Introduction

2. Context-Aware Discovery of Visual Co-occurrence Patterns

3. Hierarchical Sparse Coding for Visual Co-occurrence Discovery

4. Feature Co-occurrence for Visual Labeling

5. Visual Clustering with Minimax Feature Fusion

6. Conclusion

Authorized Access Point

Wang, Hongxing Visual Pattern Discovery and Recognition

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Status: new

Date: 2017-06-15