A Survey on Visual Content-Based Video Indexing and Retrieval
Chinese Academy of Sciences · Institute of Automation · +1 more institution
Abstract
Video indexing and retrieval have a wide spectrum of promising applications, motivating the interest of researchers worldwide. This paper offers a tutorial and an overview of the landscape of general strategies in visual content-based video indexing and retrieval, focusing on methods for video structure analysis, including shot boundary detection, key frame extraction and scene segmentation, extraction of features including static key frame features, object features and motion features, video data mining, video annotation, video retrieval including query interfaces, similarity measure and relevance feedback, and video browsing. Finally, we analyze future research directions.
Citation impact
- FWCI
- 35.05
- Percentile
- 100%
- References
- 333
Authors
5- WHWeiming HuCorresponding
Chinese Academy of Sciences, Institute of Automation
- NXNianhua Xie
Institute of Automation, Chinese Academy of Sciences
- LLLi Li
Institute of Automation, Chinese Academy of Sciences
- XZXianglin Zeng
Institute of Automation, Chinese Academy of Sciences
- SJStephen J. Maybank
Birkbeck, University of London
Topics & keywords
- Computer science
- Search engine indexing
- Information retrieval
- Key frame
- Video browsing
- Video tracking
- Frame (networking)
- Video retrieval
- Quality Education