Understanding-Oriented Multimedia Content Analysis

Zechao Li (Autor)

Buch | Hardcover

156 Seiten

2017 | 1st ed. 2017
Springer Verlag, Singapore
978-981-10-3688-0 (ISBN)

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This book offers a systematic introduction to an understanding-oriented approach to multimedia content analysis. It integrates the visual understanding and learning models into a unified framework, within which the visual understanding guides the model learning while the learned models improve the visual understanding. More specifically, it discusses multimedia content representations and analysis including feature selection, feature extraction, image tagging, user-oriented tag recommendation and understanding-oriented multimedia applications. The book was nominated by the University of Chinese Academy of Sciences and China Computer Federation as an outstanding PhD thesis. By providing the fundamental technologies and state-of-the-art methods, it is a valuable resource for graduate students and researchers working in the field computer vision and machine learning.

Zechao Li is an associate professor at the School of Computer Science, Nanjing University of Science and Technology, China. He received his B.E. degree from the University of Science and Technology of China (USTC), Anhui Province, China, in 2008, and his Ph.D degree in Pattern Recognition and Intelligent Systems from the National Laboratory of Pattern Recognition, Institute of Automation, the Chinese Academy of Sciences in 2013. His research interests include machine learning, subspace learning and multimedia understanding. He is the recipient of the 2015 Excellent Doctoral Dissertation from the Chinese Academy of Sciences, the 2015 Excellent Doctoral Dissertation from the China Computer Federation and the 2013 Chinese Academy of Science President Scholarship. He also received the Top 10% Paper Award at MMSP 2015.

Introduction.- Understanding-oriented Unsupervised Feature Selection.- Understanding-oriented Feature.- Personalized Tag Recommendation.- Understanding-oriented Multimedia News Retrieval.- Understanding-oriented Multimedia News Summarization.- Conclusion.

Erscheinungsdatum	29.06.2017
Reihe/Serie	Springer Theses
Zusatzinfo	33 Illustrations, color; 3 Illustrations, black and white; XIX, 156 p. 36 illus., 33 illus. in color.
Verlagsort	Singapore
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
	Mathematik / Informatik ► Informatik ► Grafik / Design
	Informatik ► Software Entwicklung ► User Interfaces (HCI)
Schlagworte	Feature learning • Multimedia Analysis and Understanding • News Retrieval • subspace learning • Tag Recommendation • unsupervised feature selection
ISBN-10	981-10-3688-8 / 9811036888
ISBN-13	978-981-10-3688-0 / 9789811036880
Zustand	Neuware