Discrimination of abandoned and stolen object based on active contours

In this paper we propose an approach based on active contours to discriminate previously detected static foreground regions between abandoned and stolen. Firstly, the static foreground object contour is extracted. Then, an active contour adjustment is performed on the current and the background frames. Finally, similarities between the initial contour and the two adjustments are studied to decide whether the object is abandoned or stolen. Three different methods have been tested for this adjustment. Experimental results over a heterogeneous dataset show that the proposed method outperforms state-of-art approaches and provides a robust solution against non-accurate data (i.e., foreground static objects wrongly segmented) that is common in complex scenarios.