International Journal of Digital Multimedia Broadcasting

Video Analysis, Abstraction and Retrieval: Techniques and Applications


Publishing date
01 Mar 2010
Status
Published
Submission deadline
01 Sep 2009

Lead Editor

1Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands

2Philips Research Laboratories, 5656 AA Eindhoven, The Netherlands

3CycloMedia/Eindhoven University of Technology, 4180 BB Waardenburg, The Netherlands

4Ryerson University, Toronto, ON, Canada M5B 2K3


Video Analysis, Abstraction and Retrieval: Techniques and Applications

Description

The proliferation of TV broadcast channels and programs has led to an explosion of digital video content, which results in large personal and public video databases. However, the rapidly increasing availability of video data has not yet been accompanied by an increase in its accessibility. This is due to the situation that video data are naturally different to traditional forms of data, which can be easily accessed and searched based on text. Therefore, how to efficiently organize broadcast video, such as TV news and sports, into more compact forms and extract semantically meaningful information becomes more and more important. In the past ten years, the majority of research has gradually converged to three fundamental areas, namely, video analysis, video abstraction, and video retrieval. Video analysis is utilized to extract both general and domain-specific visual features, such as color, texture, shape, human faces, and human motion. Video abstraction is to generate a representation of visual information, which is similar to the extraction of keywords or summaries in text document processing. Basically, video abstraction is associated with key-frame detection, shot clustering, and the extraction of domain knowledge of the targeted video source. The content attributes found in video analysis and abstraction processes are often referred to as metadata. In many information systems, we need fast schemes and tools to use content metadata to query, search, and browse large video databases. Although a lot of efforts have been devoted into this area, both computational cost and accuracy of the existing systems are still far from satisfactory.

This special issue aims at capturing the latest advances of the research community working in video analysis, abstraction, and retrieval for broadcasting applications. The objectives of this special issue are twofold: (1) publishing novel fundamental techniques, and (2) showcasing robust systems to treat popular broadcast videos, such as TV news and sports video. Topics of interest include, but are not limited to:

  • Feature extraction and description from broadcast video
  • Object detection, tracking, and recognition in broadcast video
  • Shot boundary detection and scene segmentation
  • Key frame extraction and video summarization
  • Efficient methods for video indexing and concepts modeling
  • Semantic content understanding and recognition
  • Video browsing/visualization tools for the broadcast video
  • Semantic annotations of video content
  • Metadata Standards for Video Analysis, Abstraction and Retrieval
  • Multimodal data generation and fusion
  • User interface for media browsing and search
  • General framework for video retrieval
  • Evaluation techniques and methodologies for video abstraction and retrieval
  • Robust systems: TV news, sports, and so forth.

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/ijdmb/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/, according to the following timetable:


Articles

  • Special Issue
  • - Volume 2010
  • - Article ID 348914
  • - Editorial

Video Analysis, Abstraction, and Retrieval: Techniques and Applications

Jungong Han | Ling Shao | ... | Ling Guan
  • Special Issue
  • - Volume 2010
  • - Article ID 539796
  • - Research Article

Unsupervised Segmentation Methods of TV Contents

Elie El-Khoury | Christine Sénac | Philippe Joly
  • Special Issue
  • - Volume 2010
  • - Article ID 486487
  • - Research Article

Multimodal Indexing of Multilingual News Video

Hiranmay Ghosh | Sunil Kumar Kopparapu | ... | Meghna Pandharipande
  • Special Issue
  • - Volume 2010
  • - Article ID 836357
  • - Research Article

Personalized Sports Video Customization Using Content and Context Analysis

Chao Liang | Changsheng Xu | Hanqing Lu
  • Special Issue
  • - Volume 2010
  • - Article ID 920121
  • - Research Article

Flexible Human Behavior Analysis Framework for Video Surveillance Applications

Weilun Lao | Jungong Han | Peter H. N. de With
  • Special Issue
  • - Volume 2010
  • - Article ID 153160
  • - Research Article

Automatic TV Broadcast Structuring

Gaël Manson | Sid-Ahmed Berrani
  • Special Issue
  • - Volume 2010
  • - Article ID 856761
  • - Research Article

A Video Browsing Tool for Content Management in Postproduction

Werner Bailer | Wolfgang Weiss | ... | Werner Haas
  • Special Issue
  • - Volume 2010
  • - Article ID 864123
  • - Research Article

An Optimized Dynamic Scene Change Detection Algorithm for H.264/AVC Encoded Video Sequences

Giorgio Rascioni | Susanna Spinsante | Ennio Gambi
  • Special Issue
  • - Volume 2010
  • - Article ID 352060
  • - Research Article

ipProjector: Designs and Techniques for Geometry-Based Interactive Applications Using a Portable Projector

Thitirat Siriborvornratanakul | Masanori Sugimoto
  • Special Issue
  • - Volume 2010
  • - Article ID 709161
  • - Research Article

Statistical Skimming of Feature Films

Sergio Benini | Pierangelo Migliorati | Riccardo Leonardi
International Journal of Digital Multimedia Broadcasting
 Journal metrics
Acceptance rate45%
Submission to final decision66 days
Acceptance to publication137 days
CiteScore1.200
Impact Factor-
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