Robust Panning Analysis for Slideshow Detection in Video Databases
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.