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: