Automated Intruder Detection from Image Sequences using Minimum Volume Sets

Abstract

We propose a new algorithm based on machine learning techniques for automatic intruder detection in surveillance networks. The algorithm is theoretically founded on the concept of minimum volume sets. Through application to image sequences from two different scenarios and comparison with some existing algorithms, we show that it is possible for our proposed algorithm to easily obtain high detection accuracy with low false alarm rates.