Video Search and Mining / Edition 1

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More About This Textbook

Overview

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. 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 objective of this book is to present the latest advances in video search and mining covering both theoretical approaches and practical applications. 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.
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Product Details

  • ISBN-13: 9783642128998
  • Publisher: Springer Berlin Heidelberg
  • Publication date: 5/21/2010
  • Series: Studies in Computational Intelligence Series , #287
  • Edition description: 2010
  • Edition number: 1
  • Pages: 388
  • Product dimensions: 6.30 (w) x 9.30 (h) x 1.00 (d)

Table of Contents

Motion Trajectory Analysis.- 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.- High-Dimensional Video Representation.- Three Dimensional Information Extraction and Applications to Video Analysis.- Statistical Analysis on Manifolds and Its Applications to Video Analysis.- Semantic Video Analysis.- Semantic Video Content Analysis.- Video Genre Inference Based on Camera Capturing Models.- Visual Concept Learning from Weakly Labeled Web Videos.- Personalized Video.- Face Recognition and Retrieval in Video.- A Human-Centered Computing Framework to Enable Personalized News Video Recommendation.- Video Mining.- A Holistic, In-Compression Approach to Mining Independent 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.
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