Abstract

Video indexing is a central component necessary to facilitate efficient content-based retrieval and browsing of visual information stored in large multimedia databases. This thesis presents work towards a unified framework for automated video indexing. To create an efficient index, a set of representative key frames are selected which capture and encapsulate the entire video content. This is achieved by, firstly, segmenting the video into its constituent shots and, secondly, selecting an optimal number of frames between the identified shot boundaries. The segmentation algorithm is designed to detect both abrupt shot transitions, or cuts, and gradual transitions, such as dissolves and fades. This is achieved by means of a two-component frame differencing metric taking both image structure and colour distributions into account. The application of hierarchical block-based normalised correlation and local colour histogram differences leads to a method which is both accurate and robust.

Citations