Agt International Gmbh

Robert Boschgmbh

Didier Stricker

Markus Schlattmann

Stephan Krauss

Jan Hirzel

Sebastian Hohmann

Sebastian Palacio

Jens Ackermann

Thomas Geiler

Oliver Wasenmueller

A camera () for monitoring a monitored area (), including a camera sensor () for generating at least one unmasked surveillance image () of the monitored area () and/or of a subarea of the monitored area (), the camera sensor () being configured for providing raw data, the raw data encompassing the at least one unmasked surveillance image (), and including an integrated evaluation unit (), the evaluation unit () encompassing an input interface () for receiving the raw data and encompassing an output interface () for providing output image data.

Camera for monitoring a monitored area and monitoring device, and method for monitoring a monitored area

A method and system of identifying in an image captured by a second camera a target object captured by a first camera is disclosed. The method comprises using image captured by the 1camera for generating a first set of objects comprising the target object and other objects; classifying each object to generate a reference group of attribute values characterizing the objects; using image captured by the 2camera for generating second sets of objects; classifying each object in each second set to generate, for each second set, a corresponding group of attribute values characterizing the objects in the corresponding second set; selecting the second set of objects corresponding to the group of attribute values best matching the reference group of attribute values; and identifying the target object in the selected second set of objects in accordance with a position of the target object in the first set of objects.

Multi-camera vehicle identification system

A target object captured by a first camera is identified in images captured by a second camera. A reference platoon comprising the target object and other objects is generated using first camera images. A reference group characterizing the objects in the reference platoon is generated by running a first set of trained classifiers over the reference platoon, the first set of trained classifiers trained to characterize objects captured by the first camera. Candidate platoons are generated using second camera images. Candidate groups characterizing objects in the candidate platoons are obtained by running an independently trained second set of classifiers over the candidate platoons, the second set characterizing objects captured by the second camera. Candidate groups are compared to the reference group, and a best matching candidate platoon is selected. The target object is identified in the selected candidate platoon based on the object's position in the reference platoon.

Growing community of inventors

Kaiserslautern, Germany

Didier Stricker