Medical video mining for efficient database indexing, management and access

Xingquan Zhu*, Walid G. Aref, Jianping Fan, Ann C. Catlin, Ahmed K. Elmagarmid

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

27 Citations (Scopus)

Abstract

To achieve more efficient video indexing and access, we introduce a video database management framework and strategies for video content structure and events mining. The video shot segmentation and representative frame selection strategy are first utilized to parse the continuous video stream into physical units. Video shot grouping, group merging, and scene clustering schemes are then proposed to organize the video shots into a hierarchical structure using clustered scenes, scenes, groups, and shots, in increasing granularity from top to bottom. Then, audio and video processing techniques are integrated to mine event information, such as dialog, presentation and clinical operation, from the detected scenes. Finally, the acquired video content structure and events are integrated to construct a scalable video skimming tool which can be used to visualize the video content hierarchy and event information for efficient access. Experimental results are also presented to evaluate the performance of the proposed framework and algorithms.

Original languageEnglish
Pages569-580
Number of pages12
DOIs
Publication statusPublished - 2003
Externally publishedYes
EventNineteenth International Conference on Data Ingineering - Bangalore, India
Duration: 5 Mar 20038 Mar 2003

Conference

ConferenceNineteenth International Conference on Data Ingineering
Country/TerritoryIndia
CityBangalore
Period5/03/038/03/03

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