Video Content Representation, Indexing, and Matching in Video Information Systems

Abstract

Changing between frames is one of the most obvious information in video data. This frame-by-frame time series data is essential to many application areas. However, how to extract and compare video contents in a video information system is still an important problem to be solved. In this paper, we focus on the problem of design a fast searching method in a video information system to locate video segments that match a content-based query, approximately by time series feature values. The idea is to extract video contents via low-level feature extraction and/or high level semantic retrieval mechanisms according to a specific point of view, then segment video contents into bounding boxes via a box segmentation mechanism by their time series feature values. Video content indexing is constructed by the characteristics of prominent points that accompany bounding boxes. We also propose an efficient and effective video content matching algorithm to find similar sequences. With the help of the video indexing and matching mechanisms, several high level box-to-box and low level point-to-point query types can be requested. The implementation and performance evaluation of our video information prototype system is described.