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Video Cataloguing: Structure Parsing and Content Extraction

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Actual ISBN
9781482235777
Book Title
Video Cataloguing: Structure Parsing and Content Extraction
ISBN
9781482235777
Subject Area
Computers, Performing Arts
Publication Name
Video Cataloguing : Structure Parsing and Content Extraction
Publisher
CRC Press LLC
Item Length
9.5 in
Subject
Machine Theory, Film / Guides & Reviews, Databases / Data Mining, Information Technology
Publication Year
2015
Type
Textbook
Format
Hardcover
Language
English
Item Height
0.6 in
Author
Chi Harold Liu, Guangyu Gao
Item Weight
14.4 Oz
Item Width
6.4 in
Number of Pages
160 Pages

About this product

Product Information

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1482235773
ISBN-13
9781482235777
eBay Product ID (ePID)
211793766

Product Key Features

Number of Pages
160 Pages
Language
English
Publication Name
Video Cataloguing : Structure Parsing and Content Extraction
Publication Year
2015
Subject
Machine Theory, Film / Guides & Reviews, Databases / Data Mining, Information Technology
Type
Textbook
Subject Area
Computers, Performing Arts
Author
Chi Harold Liu, Guangyu Gao
Format
Hardcover

Dimensions

Item Height
0.6 in
Item Weight
14.4 Oz
Item Length
9.5 in
Item Width
6.4 in

Additional Product Features

Intended Audience
College Audience
LCCN
2016-429300
Illustrated
Yes
Lc Classification Number
Z695.64
Table of Content
Introduction Introduction to Movie and Teleplay Cataloguing Related Research State and Progress Main Research Work Visual Features Extraction Introduction Scale-Invariant Feature Transform Gabor Feature Histogram of Oriented Gradients (HOG) Maximally Stable Extremal Regions Local Binary Pattern (LBP) Feature Learning Summary Accelerating Shot Boundary Detection Introduction Related Work Frame Difference Calculation Temporal Redundant Frame Reduction Corner Distribution-Based MCFB Removal Experimental Results Summary Key Frame Extraction Introduction Size of the Key Frame Set Categories of Key Frame Extraction Methods Key Frame Extraction Using a Panoramic Frame Summary Multimodality Movie Scene Detection Introduction Related Work KCCA and Feature Fusion-Based Method Experiment and Results Summary Video Text Detection and Recognition Introduction Implementation of Video Text Recognition Summary ''Where" Entity: Video Scene Recognition Introduction Related Work Overview Video Segmentation Representative Feature Patch Extraction Scene Classification Using Latent Dirichlet Analysis Enhanced Recognition Based on VSC Correlation Experimental Results Summary ''Who" Entity: Character Identification Introduction Related Work Overview of Adaptive Learning Adaptive Learning with Related Samples Experiments Summary Audiovisual Information-Based Highlight Extraction Introduction Framework Overview Unrelated Scene Removal Experimental Results Summary Demo System of Automatic Movie or Teleplay Cataloguing Introduction General Design of the Demo References Index
Copyright Date
2015

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