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Structuring Lecture Videos by Automatic Projection Screen Localization and Analysis

机译:通过自动投影屏幕本地化和分析来构建演讲视频

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摘要

We present a fully automatic system for extracting the semantic structure of a typical academic presentation video, which captures the whole presentation stage with abundant camera motions such as panning, tilting, and zooming. Our system automatically detects and tracks both the projection screen and the presenter whenever they are visible in the video. By analyzing the image content of the tracked screen region, our system is able to detect slide progressions and extract a high-quality, non-occluded, geometrically-compensated image for each slide, resulting in a list of representative images that reconstruct the main presentation structure. Afterwards, our system recognizes text content and extracts keywords from the slides, which can be used for keyword-based video retrieval and browsing. Experimental results show that our system is able to generate more stable and accurate screen localization results than commonly-used object tracking methods. Our system also extracts more accurate presentation structures than general video summarization methods, for this specific type of video.
机译:我们提供了一种用于提取典型学术演示视频语义结构的全自动系统,该系统可通过诸如平移,倾斜和缩放等丰富的摄像机动作来捕获整个演示阶段。只要在视频中可见,我们的系统就会自动检测并跟踪投影屏幕和演示者。通过分析跟踪的屏幕区域的图像内容,我们的系统能够检测幻灯片进度,并为每张幻灯片提取高质量,无遮挡,几何补偿的图像,从而生成可重建主要演示文稿的代表性图像列表结构体。之后,我们的系统识别文本内容并从幻灯片中提取关键字,这些关键字可用于基于关键字的视频检索和浏览。实验结果表明,与常用的对象跟踪方法相比,我们的系统能够生成更稳定,更准确的屏幕定位结果。对于这种特定类型的视频,我们的系统还提取了比常规视频摘要方法更准确的表示结构。

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