Automated analysis and annotation of basketball video

Drew D. Saur; Yap-Peng Tan; Sanjeev R. Kulkarni; Peter J. Ramadge

doi:10.1117/12.263406

15 January 1997 Automated analysis and annotation of basketball video

Drew D. Saur, Yap-Peng Tan, Sanjeev R. Kulkarni, Peter J. Ramadge

Proceedings Volume 3022, Storage and Retrieval for Image and Video Databases V; (1997) https://doi.org/10.1117/12.263406
Event: Electronic Imaging '97, 1997, San Jose, CA, United States

Abstract

Automated analysis and annotation of video sequences are important for digital video libraries, content-based video browsing and data mining projects. A successful video annotation system should provide users with useful video content summary in a reasonable processing time. Given the wide variety of video genres available today, automatically extracting meaningful video content for annotation still remains hard by using current available techniques. However, a wide range video has inherent structure such that some prior knowledge about the video content can be exploited to improve our understanding of the high-level video semantic content. In this paper, we develop tools and techniques for analyzing structured video by using the low-level information available directly from MPEG compressed video. Being able to work directly in the video compressed domain can greatly reduce the processing time and enhance storage efficiency. As a testbed, we have developed a basketball annotation system which combines the low-level information extracted from MPEG stream with the prior knowledge of basketball video structure to provide high level content analysis, annotation and browsing for events such as wide- angle and close-up views, fast breaks, steals, potential shots, number of possessions and possession times. We expect our approach can also be extended to structured video in other domains.

Citation Download Citation

Drew D. Saur, Yap-Peng Tan, Sanjeev R. Kulkarni, and Peter J. Ramadge "Automated analysis and annotation of basketball video", Proc. SPIE 3022, Storage and Retrieval for Image and Video Databases V, (15 January 1997); https://doi.org/10.1117/12.263406

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