Object classification based on behaviour patterns

With the recent explosion of surveillance videos, media management has gained n increasing popularity. Addressing this challenge, in this paper, we propose a Surveillance Media Management framework for object detection and classification based on behaviour patterns. The objectives of the paper are: (i) demostrating the discriminative power of behaviour features for object recognition and classification, (ii) proposing a behavioural fuzzy classifier which progressively discriminate objects by including different degrees of uncertainty in the classification process and (iii) presenting a Surveillance Media Management system to extract semantic media information and provide unsupervised object classification from raw surveillance videos. The performance of the proposed system has been thoroughly evaluated on AVSS 2007 surveillance dataset and as the results indicate the proposed technique enhances object classification performance. (6 pages)