Duration abnormality detection in sequences of human activity

Activity duration is an essential element in the accurate modelling of human behaviour. The application of a standard hidden Markov Model (HMM) for the detection of abnormality in sequences of human activity can create a situation in which highly unusual duration less than or greater than the duration normally observed can fail to be detected. In this paper1, we show how the application of the explicit state duration HMM can alleviate this problem, enabling us to distinguish between sequences of activity in which the order of observations is identical but the duration of activities is different and to identify the presence of abnormal activity duration. Experimental results highlight the improvement over the standard HMM for both abnormality detection and classification in certain anomalous situations.