Eads Deutschland Gmbh

Pilz Gmbh & Co Kg.

Rainer Ott

Helmuth Eggers

Lars Krueger

Christian Woehler

Ulrich Kressel

Werner Progscha

Lars Krüger

Henrik Baur

Franz Kummert

Joachim Schmidt

Gerhard Sagerer

A method for observing a person in an industrial environment using a multicamera system to acquire image data about the position and alignment of a person, including a person's body parts. These image data are then examined with regard to the imaging of a person so that whenever a person has been detected in the image data, an articulated virtual 3D model of the human body is matched to this person hypothesis. Subsequently, this virtual body model is continuously matched to the movement behavior of the person detected in the image data. A hazard potential is determined using knowledge of the position and the movement behavior of the virtual body model in space. The hazard potential thus determined is subjected to a threshold value comparison in order to act upon the movement control of the machine or the machine part in the event of this threshold value being exceeded.

Method for observation of a person in an industrial environment

Method for at least one of model-based classification and target recognition of an object. The method includes recording an image of an inanimate object, determining a feature that represents a part of the inanimate object, determining at least one condition associated with the feature that indicates an applicability of the feature based on at least one of geometry of the object, distance of the object from a camera, illumination conditions, contrast, speed of the object, height of the object, and relative position of the object to a camera, and carrying out the at least one of classification and target recognition of the object by recording the feature when the at least one condition indicates the applicability of the feature. At least one of object classification and target recognition is carried out for a feature of the object that is visible and recordable according to the position of the object. The recording, the determining the feature, the determining the at least one condition, and the carrying out are implemented on a computer.

Model-based object classification and target recognition

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Ulm, Germany

Rainer Ott