COMPARISON OF MULTI_EPISODE VIDEO SUMMARISATION ALGORITHMS.pdf

COMPARISON OF MULTI_EPISODE VIDEO SUMMARISATION ALGORITHMS Itheri Yahiaoui – Bernard Merialdo – Benoit Huet Institut Eurecom Departement Communication Multimedia BP 193 – 06904 Sophia – Antipolis- France {Itheri.Yahiaoui,Bernard.Merialdo,Benoit.Huet}@eurecom.fr Abstract This paper presents a comparison of some methodologies for the automatic construction of video summaries. The work is based on the Simulated User Principle to evaluate the quality of a video summary in a way, which is automatic, yet related to users perception. The method is studied for the case of multi-episode video. Where we don’t only describe what is important in a video, but rather what distinguishes this video from the others. Experimental results are presented to support the proposed ideas. 1 INTRODUCTION RELATED WORK The ever-growing availability of multimedia data, creates a strong requirement for efficient tools to manipulate and present data in an effective manner. Automatic video summarization tools aim at creating with little or no human interaction short versions which contains the salient information of original video. The key issue here is to select what should be kept in the summary and how can this relevant information be automatically extracted. To perform this task we consider several algorithms and compare their performance to define the most appropriate one for our application. A number of approaches have been proposed to define and identify what is the most important content in a video. However, most have two major limitations. First, evaluation is difficult, in the sense that it is hard to judge the quality of a summary, or, when a performance measure is available, it is hard to understand what is its interpretation. Secondly, while summarization of a single video has received increasing attention [1,2,3,4,5,6], little work has been devoted to the problem of multi-episode video summarization [7,8] which raises other interesting difficultie