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“Video Search and Mining” ed. by Dan Schonfeld, Caifeng Shan, Dacheng Tao, and LiangWang

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"Video Search and Mining" ed. by Dan Schonfeld, Caifeng Shan, Dacheng Tao, and LiangWang
Studies in Computational Intelligence, 287
Springer | 2010 | ISBN: 3642128998 9783642129001 9783642128998 | 386 pages | PDF | 7 MB
This book provides an overview of emerging new approaches to video search and mining based on promising methods being developed in the computer vision and image analysis community. The objective of this book is to present the latest advances in video search and mining covering both theoretical approaches and practical applications.

“Video Search and Mining” ed. by Dan Schonfeld, Caifeng Shan, Dacheng Tao, and LiangWang
Video search and mining is a rapidly evolving discipline whose aim is to capture interesting patterns in video data. It has become one of the core areas in the data mining research community. In comparison to other types of data mining (e.g. text), video mining is still in its infancy.
The book provides researchers and practitioners a comprehensive understanding of the start-of-the-art in video search and mining techniques and a resource for potential applications and successful practice.
This book can also serve as an important reference tool and handbook for researchers and practitioners in video search and mining.

Contents
Preface
Object Trajectory Analysis in Video Indexing and Retrieval Applications
Trajectory Clustering for Scene Context Learning and Outlier Detection
Motion Trajectory-Based Video Retrieval, Classification, and Summarization
Three Dimensional Information Extraction and Applications to Video Analysis
Statistical Analysis on Manifolds and Its Applications to Video Analysis*
Semantic Video Content Analysis
Video Genre Inference Based on Camera Capturing Models
Visual Concept Learningfrom Weakly Labeled Web Videos
Face Recognition and Retrieval in Video
A Human-Centered Computing Framework to Enable Personalized News Video Recommendation
A Holistic, In-Compression Approach to Mininglndependent Motion Segments for Massive Surveillance Video Collections
Video Repeat Recognition and Mining by Visual Features
Mining TV Broadcasts 24/7 for Recurring Video Sequences
YouTube Scale, Large Vocabulary Video Annotation
Author Index
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