Authors:
- Overviews all the aspects of feature coding, from motivation, mathematical representation to applications in practice
- Review the state-of-the-art and explore the evolvement of various algorithms
- Categorize the existing typical feature coding algorithms and summarize the characteristics
- Provide the suggestions of employing feature coding in practice and forecast potential directions of this area
- Supplies supplementary materials such as source codes of the algorithm framework and all related feature coding algorithms at the associated website, http://www.openpr.org.cn/index.php/All/92-Evaluation-toolkit/View-details.html
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
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Table of contents (8 chapters)
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Front Matter
About this book
Authors and Affiliations
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Institute of Automation Chinese Academy of Sciences, Beijing, China
Yongzhen Huang, Tieniu Tan
About the authors
Yongzhen Huang received his B.E. degree from Huazhong University of Science and Technology in 2006 and his Ph.D. degree from Institute of Automation, Chinese Academy of Sciences (CASIA) in 2011. In July 2011, he joined the National Laboratory of Pattern Recognition (NLPR), CASIA, where he is currently an Associate Professor. He has published more than 30 papers in the areas of computer vision and pattern recognition at international journals and conferences such as IEEE TPAMI, TSMC-B, CVPR, NIPS, ICPR and ICIP. In 2010 and 2011, he and this team won the champion of the PASCAL VOC competition on object detection, and their system of object classification was ranked the 2ndin 2011. His current research interests include pattern recognition, computer vision and machine learning.
Tieniu Tan received his BSc degree from Xi'an Jiaotong University, China, in 1984 and his MSc and PhD degrees from the Imperial College of Science, Technology and Medicine, London, in 1986 and 1989, respectively. In 1989, he joined the Computational Vision Group, Department of Computer Science, University of Reading, United Kingdom, where he worked as a research fellow, a senior research fellow, and a lecturer. In 1998, he joined the National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA) in Beijing, where he is currently a Professor and the Director of the Center for Research on Intelligent Perception and Computing (CRIPAC). Prof. Tan has co-authored and edited multiple books with Springer, and has published more than 300 research papers in refereed journals and conference proceedings in the areas of image processing, computer vision, and pattern recognition. His current research interests include biometrics, image and video understanding, information hiding, and information forensics. He is the first vice president of the Inter. Assoc. for Pattern Recognition (IAPR) and a founding chair of the IAPR/IEEE International Conference on Biometrics (ICB) and the IEEE International Workshop on Visual Surveillance. He is a fellow of the IEEE and the IAPR, and an academician of the Chinese Academy of Sciences.
Bibliographic Information
Book Title: Feature Coding for Image Representation and Recognition
Authors: Yongzhen Huang, Tieniu Tan
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-662-45000-0
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature 2014
Softcover ISBN: 978-3-662-44999-8Published: 22 January 2015
eBook ISBN: 978-3-662-45000-0Published: 05 January 2015
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: XIII, 74
Number of Illustrations: 4 b/w illustrations, 32 illustrations in colour
Topics: Pattern Recognition, Image Processing and Computer Vision, Artificial Intelligence, Algorithm Analysis and Problem Complexity