A New Hybrid Approach to Video Organization for Content-Based Indexing

Abstract

Video organization is a key step in the content-based indexing of video archives. The objective of video organization is to capture the semantic structure of a video in a form which is meaningful to the user. We present a hybrid approach to video organization which automatically processes video, creating a video table of contents (VTOC), while providing easy-to-use interfaces for verification, correction and augmentation of the automatically extracted video structure. Algorithms are developed to solve the sub-problems of shot detection, shot grouping and VTOC generation without making very restrictive assumptions about the structure or content of the video. We use a nonstationary time series model of difference metrics for shot boundary detection, color and edge similarities for shot grouping and observations about the structure of a wide class of videos for the generation of the VTOC. The use of automatic processing in conjunction with input from the user allows us to produce meaningful video organization efficiently.