Left-Luggage Detection from Finite-State-Machine Analysis in Static-Camera Videos

We present an abandoned object detection system in this paper. A finite-state-machine model is introduced to extract stationary foregrounds in a scene for visual surveillance, where the state value of each pixel is inferred via the cooperation of short-term and long-term background models constructed in the proposed approach. To identify the left-luggage event, we then verify whether the static foregrounds are abandoned objects through the analysis of owner´s moving trajectory back-tracked to the static foreground locations. Experimental results reveal that the proposed approach tackles the problem well on publicly available datasets.