Iterative active querying for surveillance data retrieval in crime detection and forensics

Large sets of visual data are now available both, in real time and off line, at time of investigation in multimedia forensics, however passive querying systems often encounter difficulties in retrieving significant results. In this paper we propose an iterative active querying system for video surveillance and forensic applications based on the continuous interaction between the user and the system. The positive and negative user feedbacks are exploited as the input of a graph based transductive procedure for iteratively refining the initial query results. Experiments are shown using people trajectories and people appearance as distance metrics.