Video Shot Boundary Detection using Visual Bag-of-Words

Recently, convergence of techniques used in image analysis and video processing has occurred. Many computation and memory intensive image analysis methods have become available for per frame processing of videos due to increased computing power of desktop computers and efficient implementations on multiple cores and graphical processing units (GPUs). As our main contribution in this work, we solve the problem of shot boundary detection using a popular image analysis (object detection) approach: visual bag-of-words (BoW). The baseline approach for the shot boundary detection has been colour histogram and it is at the core of many top methods, but our BoW method of similar complexity in the terms of parameters clearly outperforms colour histograms. Interestingly, an “AND-combination” of colour and BoW histogram detection is clearly superior indicating that colour and local features provide complimentary information for video analysis.