  Evaluation of automatic video summaries is a challenging problem. In the past
years, some evaluation methods are presented that utilize only a single feature
like color feature to detect similarity between automatic video summaries and
ground-truth user summaries. One of the drawbacks of using a single feature is
that sometimes it gives a false similarity detection which makes the assessment
of the quality of the generated video summary less perceptual and not accurate.
In this paper, a novel method for evaluating automatic video summaries is
presented. This method is based on comparing automatic video summaries
generated by video summarization techniques with ground-truth user summaries.
The objective of this evaluation method is to quantify the quality of video
summaries, and allow comparing different video summarization techniques
utilizing both color and texture features of the video frames and using the
Bhattacharya distance as a dissimilarity measure due to its advantages. Our
Experiments show that the proposed evaluation method overcomes the drawbacks of
other methods and gives a more perceptual evaluation of the quality of the
automatic video summaries.
