Models for motion-based video indexing and retrieval

Abstract

With the rapid proliferation of multimedia applications that require video data management, it is becoming more desirable to provide proper video data indexing techniques capable of representing the rich semantics in video data. In real-time applications, the need for efficient query processing is another reason for the use of such techniques. We present models that use the object motion information in order to characterize the events to allow subsequent retrieval. Algorithms for different spatiotemporal search cases in terms of spatial and temporal translation and scale invariance have been developed using various signal and image processing techniques. We have developed a prototype video search engine, PICTURESQUE (pictorial information and content transformation unified retrieval engine for spatiotemporal queries) to verify the proposed methods. Development of such technology will enable true multimedia search engines that will enable indexing and searching of the digital video data based on its true content.