Video Cataloguing: Structure Parsing and Content Extraction, 1st Edition (Paperback) book cover

Video Cataloguing

Structure Parsing and Content Extraction, 1st Edition

By Guangyu Gao, Chi Harold Liu

CRC Press

320 pages

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Paperback: 9781138894136
pub: 2020-01-10
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pub: 2015-10-27
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pub: 2015-10-27
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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.

Table of Contents


Introduction to Movie and Teleplay Cataloguing

Related Research State and Progress

Main Research Work

Visual Features Extraction


Scale-Invariant Feature Transform

Gabor Feature

Histogram of Oriented Gradients (HOG)

Maximally Stable Extremal Regions

Local Binary Pattern (LBP)

Feature Learning


Accelerating Shot Boundary Detection


Related Work

Frame Difference Calculation

Temporal Redundant Frame Reduction

Corner Distribution-Based MCFB Removal

Experimental Results


Key Frame Extraction


Size of the Key Frame Set

Categories of Key Frame Extraction Methods

Key Frame Extraction Using a Panoramic Frame


Multimodality Movie Scene Detection


Related Work

KCCA and Feature Fusion-Based Method

Experiment and Results


Video Text Detection and Recognition


Implementation of Video Text Recognition


‘‘Where" Entity: Video Scene Recognition


Related Work


Video Segmentation

Representative Feature Patch Extraction

Scene Classification Using Latent Dirichlet Analysis

Enhanced Recognition Based on VSC Correlation

Experimental Results


‘‘Who" Entity: Character Identification


Related Work

Overview of Adaptive Learning

Adaptive Learning with Related Samples



Audiovisual Information-Based Highlight Extraction


Framework Overview

Unrelated Scene Removal

Experimental Results


Demo System of Automatic Movie or Teleplay Cataloguing


General Design of the Demo



About the Authors

Guangyu Gao is an assistant professor at the School of Software, Beijing Institute of Technology, China. He earned his PhD degree in computer science and technology from the Beijing University of Posts and Telecommunications, China, in 2013, and his MS degree in computer science and technology from Zhengzhou University, Henan Province, China, in 2007. He was also a government-sponsored joint PhD student at the National University of Singapore, from July 2012 to April 2013. His current research interests include applications of multimedia, computer vision, video analysis, machine learning, and Big Data.

As an author, he received the Electronic Information and Science Technology Prize, awarded by the Chinese Institute of Electronics. He has published dozens of prestigious conference and journal papers and is a member of both the Association for Computing Machinery and the China Computer Federation.

Chi Harold Liu is a full professor at the School of Software, Beijing Institute of Technology, China. He is also the director of the IBM Mainframe Excellence Center (Beijing), the IBM Big Data Technology Center, and the National Laboratory of Data Intelligence for China Light Industry. He holds a PhD degree from Imperial College, London, UK, and a BEng degree from Tsinghua University, Beijing, China. Before moving to academia, he joined IBM Research–China as a staff researcher and project manager, after working as a postdoctoral researcher at Deutsche Telekom Laboratories, Berlin, Germany, and a visiting scholar at IBM T. J. Watson Research Center, Hawthorne, New York.

His current research interests include the Internet-of-Things (IoT), Big Data analytics, mobile computing, and wireless ad hoc, sensor, and mesh networks. He received the Distinguished Young Scholar Award in 2013, IBM First Plateau Invention Achievement Award in 2012, and IBM First Patent Application Award in 2011 and was interviewed by as the featured engineer in 2011. He has published more than 60 prestigious conference and journal papers and owned more than 10 EU/U.S./China patents.

Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Database Management / Data Mining
COMPUTERS / Information Technology
COMPUTERS / Machine Theory