Mining Images in Publicly-Available Cameras for Homeland Security

AI Technologies for Homeland Security

Volume

Papers from the 2005 AAAI Spring Symposium

Contents

A dramatic increase or decrease in the number of people appearing at a location can be an indicator that something has happened that may be of interest to law-enforcement, public health, or security. This work demonstrates how low quality camera images can be used to automatically alert when an unusual number of people are absent or present at a location. We report on experiments using publicly available, inexpensive cameras already operational over the Web. A "historical database" (H) for each camera is constructed by capturing images at regular time intervals and applying a face detection algorithm to store the number of faces appearing in each image ("face count"). Later, given an image X having timestamp t, if the face count of X is significantly higher or lower than the expectation inferred from H for time t, an unusual number of people are considered to be present in the image.