Cover image for Semantic-based visual information retrieval
Semantic-based visual information retrieval
Title:
Semantic-based visual information retrieval
Author:
Zhang, Yu-Jin, 1954-
ISBN:
9781599043722
Personal Author:
Publication Information:
Hershey, Pa. : IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), c2007.
Physical Description:
electronic texts (xiii, 368 p. : ill.) : digital files.
Contents:
Toward High-Level Visual Information Retrieval / Yu-Jin Zhang -- The Impact of Low-Level Features in Semantic-Based Image Retrieval / Konstantinos Konstantinidis, Antonios Gasteratos, Ioannis Andreadis -- Shape-Based Image Retrieval by Alignment / Enver Sangineto -- Statistical Audio-Visual Data Fusion for Video Scene Segmentation / Vyacheslav Parshin, Liming Chen -- A Novel Framework for Image Categorization and Automatic Annotation / Feng Xu, Yu-Jin Zhang -- Automatic and Semi-Automatic Techniques for Image Annotation / Biren Shah ... [et al.] -- Adaptive Metadata Generation for Integration of Visual and Semantic Information / Hideyasu Sasaki, Yasushi Kiyoki -- Interaction Models and Relevance Feedback in Image Retrieval / Daniel Heesch, Stefan Rüger -- Semi-Automatic Ground Truth Annotation for Benchmarking of Face Detection in Video / Dzmitry Tsishkou, Liming Chen, Eugeny Bovbel -- An Ontology-Based Framework for Semantic Image Analysis and Retrieval / Stamatia Dasiopoulou ... [et al.] -- A Machine Learning-Based Model for Content-Based Image Retrieval / Hakim Hacid, Abdelkader Djamel Zighed -- Neural Networks for Content-Based Image Retrieval / Brijesh Verma, Siddhivinayak Kulkarni -- Semantic-Based Video Scene Retrieval Using Evolutionary Computing / Hun-Woo Yoo -- Managing Uncertainties in Image Databases / Antonio Picariello, Maria Luisa Sapino --

A Hierarchical Classification Technique for Semantics-Based Image Retrieval / Mohammed Lamine Kherfi, Djemel Ziou -- Semantic Multimedia Information Analysis for Retrieval Applications / João Magalhães, Stefan Rüger.
Abstract:
Semantic-based visual information retrieval is one of the most challenging research directions of content-based visual information retrieval. It provides efficient tools for access, interaction, searching, and retrieving from collected databases of visual media. Building on research from over 30 leading experts from around the world, This book presents state-of-the-art advancements and developments in the field, and also brings a selection of techniques and algorithms about semantic-based visual information retrieval. It covers many critical issues, such as: multi-level representation and description, scene understanding, semantic modeling, image and video annotation, human-computer interaction, and more. It also explains detailed solutions to a wide range of practical applications. Researchers, students, and practitioners will find this comprehensive and detailed volume to be a roadmap for applying suitable methods in semantic-based visual information retrieval.
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