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Technical Program
Paper Detail
| Paper: | MA-L5.1 |
| Session: | Content Summarization and Clustering |
| Time: | Monday, October 9, 09:40 - 10:00 |
| Presentation: |
Lecture
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| Title: |
HIERARCHICAL SUMMARIZATION OF DIAGNOSTIC HYSTEROSCOPY VIDEOS |
| Authors: |
Jacob Scharcanski; Universidade Federal do Rio Grande do Sul | | | | | Wilson Gavião; Universidade Federal do Rio Grande do Sul | | |
| Abstract: |
Usually, diagnostic video hysteroscopies are recorded without interruptions (i.e. continuous). However, only a few video segments are relevant from the diagnosis/prognosis point of view, and need to be evaluated and referenced later. This paper proposes a hierarchical technique to identify clinically relevant segments in diagnostic hysteroscopy videos, and their associated key-frames, creating a rich video summary. The proposed summarization approach is adaptive to video contents, and represents the clinically relevant video segments hierarchically to facilitate fast video browsing. The preliminary experimental results indicate that our method produces video summaries that contain no false negatives (i.e. all video segments known to be clinically relevant appear in the summaries). Also, compared to other methods published in the literature, our method produces less false positives. |
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