Query Focused Video Summarization: A Review

Abstract

AbstractRapid development in video technologies and easy availability of video capturing devices produces voluminous data which need to handle efficiently to increase the usability of it. Automatic video summarization is a solution to traverse through this data and gives a concise view of it, which is useful in many applications. However, traditional video summarization produces succinct videos without notably qualitative and quantitative loss of information contained in videos. It considers only the important information from the video while generating a summary independent of user interest. Video summarization is a highly subjective task which is not handled by traditional methods and people are more interested in personalized Summary. The solution to handle this problem is multi-model video summarization which helps to produce user-interested summaries by taking two inputs i.e. video and user queries. Different techniques have been explored in previous work based on conventional video summarization. This study presents the reviews of the state-of-the-art query focused video summarization methods to generate the personalized video summary which has not been investigated before. This paper discusses the demand of query-based video summarization in various applications, performance of existing methods and put forward future directions to help the research community to work in this domain.KeywordsVideo summarizationDeep learningQuery-focused video summarizationMulti-model