A consistent two-level metric for evaluation of automated abandoned object detection methods

Scientific interest in automated abandoned object detection algorithms using visual information is high and many related systems have been published in recent years. However, most evaluation techniques rely only on statistical evaluation on the object level. Therefore and due to benchmarks with commonly only few abandoned objects and a non-standardized evaluation procedure, an objective performance comparison between different methods is generally hard. We propose a new evaluation metric which is focused on an end-user application case and an evaluation protocol which eliminates uncertainties in previous performance assessments. Using two variants of an abandoned object detection method, we show the features of the novel metric on multiple datasets proving its advantages over previously used measures.