A conceptual model for surveillance video content and event-based indexing and retrieval

Abstract

This paper addresses the need for a semantic video-object approach for efficient storage and manipulation of video data to respond to the needs of several classes of potential applications when efficient management and deductions over voluminous data are involved. We present the VIGILANT conceptual model for content and event-based retrieval of video images and clips using automatic annotation and indexing of contents and events representing the extracted features and recognised objects in the images captured by a video camera in a car park environment. The underlying video-object model combines Object-Oriented modelling (OO) techniques and Description Logics (DLs) Knowledge representation. The OO technique models the static aspects of video clips and instances and their indexes will be stored in an Object-Oriented Database. The DLs model will extend the 00 model to cater for the inherent dynamic content descriptions of the video, as events tend to spread over a sequence of frames. © 2002 Springer-Verlag Berlin Heidelberg.