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Abstract The integration of high data transmission rates and the recent digital multimedia technology, paves the way to access a huge amount of video over the internet, in seconds. Additionally, uploading videos to different websites is no more confined to expert software professionals resulting in duplication of video data which led to exorbitant growth of multimedia information in cyberspace in a short span of time. This necessitates the development of efficient data management techniques including storage, searching and annotation mechanism. Automatic shot boundary detection is considered to be the first and foremost step towards such management. It is a booming area of research gaining attention in the domain of image processing, computer vision and pattern recognition. In this review paper, we present a detailed description of the methods and algorithms of shot boundary detection, reported in the last two decades. This review shows that using multiple features performs well in comparison to using only a single feature in the shot boundary detection problem although it leads to higher complexity. The major sources of disturbance in the boundary detection are the sudden illumination variation and presence of high motion in the video. An adaptive threshold outperforms a single global threshold in the boundary detection problem and the threshold requirement can be avoided through learning based strategies at the cost of larger training data and higher computation time. Moreover the present review includes a critical analysis of relative merits and demerits of existing algorithms and finally opens promising research directions in the area.
Kar et al. (Sat,) studied this question.