Robust Panning Analysis for Slideshow Detection in Video Databases

Zbigniew Zdziarski, Rozenn Dahyot
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Abstract

We present an algorithm for slideshow detection in video databases such as YouTube or Blip.TV. Our solution is based around feature tracking to extract movement between sequentially captured frames. This movement is then analysed through the use of the Hough Transform and compared against behaviour commonly exhibited by slideshows: still and panning static images. We show experimentally the effectiveness of this novel idea and approach.
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视频数据库中幻灯片检测的鲁棒平移分析
我们提出了一种用于视频数据库(如YouTube或Blip.TV)中幻灯片检测的算法。我们的解决方案是基于特征跟踪来提取连续捕获帧之间的运动。然后,通过使用霍夫变换分析这种运动,并将其与幻灯片通常表现出的行为进行比较:静止和平移静态图像。我们通过实验证明了这种新思想和方法的有效性。
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