Robert Boschgmbh

Jie Yu

Hartmut Loos

Julia Ebling

Nicolas Cebron

Dirk Farin

A method for recognizing an object () in an image (), in which the recognition of the object () comprises a first scaling stage of a scaling region of the image (), and at least a further scaling stage of the scaling region of the image (); and in which the image () is subdivided into at least one image segment (); a first decision being taken for the at least one image segment () on the first scaling stage of the scaling region as to whether the at least one image segment () is considered on the at least one further scaling stage of the scaling region for the recognition of the object ().

Accelerated object recognition in an image

The invention relates to a device, method, computer program, and a computer program product for monitoring objects, in particular for monitoring scenes of objects captured on video. An object is thereby repeatedly detected and tracked, wherein a tracking device is fed back to a device for object model selection, so that when detected repeatedly, considering tracking parameters determined when tracking the object, the tracking parameters are fed to the selection device and can be considered for detecting.

Device and method for monitoring video objects

A method for detection and/or tracking of objects in motionin a scene under surveillance, in which besides the objects in motion, interfering objects and/or interfering regions&#x2014;both hereinafter called interfering factors&#x2014;can occur, is proposed, in which the scene under surveillance, a plurality of regions are defined that are divided up into various region classes; and a first region class Dincludes sensitive regions, in which no and/or only insignificant interfering factorsare located and/or are to be expected; and for detection and/or tracking of the objects in motionin the sensitive regions, a sensitive content analysis is performed, and a second region class Dincludes semi-sensitive regions, in which interfering factorsare located and/or are to be expected, and for detection and/or tracking of the objects in motionin the semi-sensitive regions, a semi-sensitive content analysis is performed, which is limited and/or modified compared to the sensitive content analysis.

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Hildesheim, Germany

Jie Yu