Conference Paper

A two-stage approach to detect abandoned baggage in public places.

DOI: 10.1117/12.849215 Conference: Visual Information Processing XIX, 6 April 2010, Orlando, Florida, USA
Source: DBLP

ABSTRACT Baggage abandoned in public places can pose a serious security threat. In this paper a two-stage approach that works on video sequences captured by a single immovable CCTV camera is presented. At first, foreground objects are segregated from static background objects using brightness and chromaticity distortion parameters estimated in the RGB colour space. The algorithm then locks on to binary blobs that are static and of 'bag' sizes; the size constraints used in the scheme are chosen based on empirical data. Parts of the background frame and current frames covered by a locked mask are then tracked using a 1-D (unwrapped) pattern generated using a bi-variate frequency distribution in the rg chromaticity space. Another approach that uses edge maps instead of patterns generated using the fragile colour information is discussed. In this approach the pixels that are part of an edge are marked using a novel scheme that utilizes four 1-D Laplacian kernels; tracking is done by calculating the total entropy in the intensity images in the sections encompassed by the binary edge maps. This makes the process broadly illumination invariant. Both the algorithms have been tested on the iLIDS dataset (produced by the Home Office Scientific Development Branch in partnership with Security Service, United Kingdom) and the results obtained are encouraging.

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