ClassMiner: Mining Medical Video Content Structure and Events Towards Efficient Access and Scalable Skimming

Xingquan Zhu, Jianping Fan, Walid G. Aref, Ahmed K. Elmagarmid
2002 Workshop on Research Issues on Data Mining and Knowledge Discovery  
To achieve more efficient video indexing and access, we introduce a video content structure and event mining framework. A video shot segmentation and key-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,
more » ... audio and video processing techniques are integrated to mine event information, such as dialog, presentation and clinical operation, among 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 algorithms. * The support of NSF under Grants IIS-0093116, IIS-9974255, EIA-9972883, and EIA-9983249 are gratefully acknowledged.
dblp:conf/dmkd/ZhuFAE02 fatcat:sayluw5d3ze27mtvn6rbwvgfjq