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Multimedia surveillance: content-based retrieval with multicamera people tracking

Multimedia surveillance relates to the exploitation of multimedia tools for retrieving information from surveillance data, for emerging applications such as video post-analysis for forensic purposes. Searching for all the sequences in which a certain person was present is a typical query that is carried out by means of example images. Unfortunately, surveillance cameras often have low resolution, making retrieval based on appearance difficult. This paper proposes to exploit a two-step retrieval process that merges similarity-based retrieval with multicamera tracking-based retrieval able to create consistent traces of a person from different views and, thus, different resolutions. A mixture model is used to summarize these traces into a single prototype on which retrieval is performed. Experimental results demonstrate the accuracy of the retrieval process also in the case of varying illumination conditions.