扩展教学视频的分割、索引和可视化
Segmentation, Indexing, and Visualization of Extended Instructional Videos
摘要：
我们提出了一种新的分割方法，和一个新的用户界面的索引和可视化，扩展的教学视频的语义内容。给定视频中的一系列关键帧，我们通过根据媒体类型和视觉相似性对帧进行聚类来生成数据的浓缩视图。使用各种视觉过滤器，关键帧首先被分配一个媒体类型（板，类，计算机，插图，讲台和工作表）。然后，通过具有近线性成本的算法基于内容对媒体类型板和片材的关键帧进行聚类。一个新颖的用户界面，两个用户研究的结果，显示相关的主题使用图标链接拓扑，允许用户快速定位语义相关的视频部分。我们分析了17个教学视频的分割工具的准确性，每个视频的持续时间从75到150分钟（共40小时）;分类准确率超过96%。
英文摘要：
We present a new method for segmenting, and a new user interface for indexing and visualizing, the semantic content of extended instructional videos. Given a series of key frames from the video, we generate a condensed view of the data by clustering frames according to media type and visual similarities. Using various visual filters, key frames are first assigned a media type (board, class, computer, illustration, podium, and sheet). Key frames of media type board and sheet are then clustered based on contents via an algorithm with near-linear cost. A novel user interface, the result of two user studies, displays related topics using icons linked topologically, allowing users to quickly locate semantically related portions of the video. We analyze the accuracy of the segmentation tool on 17 instructional videos, each of which is from 75 to 150 minutes in duration (a total of 40 hours); the classification accuracy exceeds 96%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
