文档介绍：An Expert System for Surveillance Picture
Understanding
Helman Stern, Uri Kartoun, Armin Shmilovici
Faculty of Engineering, Ben-Gurion University, 653, Be’er-Sheeva 84105, ISRAEL,
Fax: +972-8-6472958; Tel: +972-8-6477550, E-mail:(helman, kartoun,
armin)***@
Abstract: The last stage of any type of automatic surveillance system is the
interpretation of the acquired information from the sensors. This
work focuses on the interpretation of motion pictures taken from a
surveillance camera, .; image understanding. An expert system is
presented which can describe in a natural language like, simple
human activity in the field of view of a surveillance camera. The
system has three ponents: a pre-processing module for
image segmentation and feature extraction, an object identification
expert system (static model), and an action identification expert
system (dynamic temporal model). The system was tested on a video
segment of a pedestrian passageway taken by a surveillance camera.
Keywords: image understanding, picture segmentation, fuzzy expert systems,
surveillance video
1. INTRODUCTION
With the continuous decline in the price of imaging technology, there is a
surge in the use of automatic surveillance systems and closed circuit TV
(CCTV). Banks, ATM machines, schools, hospitals, transport walkways
employ automatic video recording of their surrounding environments. There
appears to be little human inspection (in real-time or otherwise) of these
surveillance videos, and thus the system is relegated to a simple deterrence
function (mainly for deterrence of possible felonies). However, in many
environments it is necessary to understand the contents of the video for
subsequent event detection, storage and retrieval. Extraction of the desired
events requires a high semantic level of human understanding and requires a
prohibitive amount of human processing.
Automatic processing of s