“Déjà vu” – Visual Search for Efficient Reidentification of Pedestrians in Huge Surveillance Databases
Csaba Beleznai (1) , Martin Winter (2), Martin Hirzer (2), Horst Bischof (2), Josef Birchbauer (3)
(1) Austrian Research Centers GmbH – ARC, Vienna, Austria
(2) Institute for Computer Graphics and Vision, Graz University of Technology, Austria
(3) Siemens Corporate Technology Central Eastern Europe, Siemens AG Austria
(1) Austrian Research Centers GmbH – ARC, Vienna, Austria
(2) Institute for Computer Graphics and Vision, Graz University of Technology, Austria
(3) Siemens Corporate Technology Central Eastern Europe, Siemens AG Austria
Abstract
We demonstrate an interactive visual search method that finds a given pedestrian in a huge archive of other camera views efficiently. A user-selected pedestrian image or sequence is used to obtain initial discriminative features and an initial ranked list of hypothetical matches. A discriminative pedestrian recognition model is learned in an on-line manner by user interaction assigning positive and negative labels to the initially retrieved results and on-line boosting for feature selection. This enables that the best discriminative features for the current query are selected. The framework typically retrieves the correct match after a few iterations. The individual steps of the search process are illustrated in the following slides: