A Comparative based study of Different Video - Shot Boundary Detection algorithms

A shot in a digital video sequence may be defined as a set of images (frames) from a single camera. A shot boundary is determined when one shot changes to another shot. A scene is a collection of one or more shots focusing on one or more objects of interest. Video shot boundary detection is a fundamental step for content based video analysis. Various methods have been proposed and developed to detect boundaries in video sequence which uses information from feature extraction, color histogram, boundary histogram, pixel differences, motion features. Some novel shot boundary methods have developed which use features above and can detect cut and gradual shot simultaneously and distinguish them. More recent algorithms designed explicitly to detect specific complex editing operations such as fades and dissolves are taken into account, and their ability to classify the types and locate the boundaries of such edits are examined. The algorithms’ performance is measured in terms of hit rate, number of false hits, and miss rate for hard cuts, fades, and dissolves over a large and diverse set of video sequences This paper gives introduction and a comparative study of all those algorithms.