Fraunhofer-gesellschaft Zur Foerderung Der Angewandten Forschung E.v.

Braun Gmbh

Andreas Ernst

Jens-Uwe Garbas

Tobias Ruf

Tobias Bergen

Anton Papst

Hansjörg Reick

Ingo Vetter

Thomas Wittenberg

Jörn Thielecke

Daniel Krenzer

Michael John Parnham

Christian Muenzenmayer

Frederik Zilly

Carl Stückrath

András Kátai

Christian Münzenmayer

Jochen Seitz

Michaela Benz

Albrecht Hess

Javier Mora

Christian Kueblbeck

Andreas Weigert

Mateusz Putyrski

Mathis Hoffmann

Dominik Seuss

Teena Chakkalayil Hassan

Johannes Wollenberg

Malte Avenhaus

Christian Wiede

Felix Lautenschlager

Marcus Bocksch

Joem Thielecke

Bernhard Brüne

Carl Stuckrath

Christian MÜNZENMAYER

Christian KÜBLBECK

An inhibitor of IL-38 is useful for treating and/or preventing cancer in a subject. A pharmaceutical composition can include an inhibitor of IL-38. A method for treating and/or preventing cancer is carried out by administering an inhibitor of IL-38 in a therapeutically effective amount. Another method is useful for identifying an inhibitor of IL-38.

Antibody inhibitors of IL-38 and methods of use thereof for treating or reducing the likelihood of cancer in a subject

A method for detecting a known pattern having homogeneous areas includes the steps of taking an image of the known pattern or, of at least a portion of the known pattern, and performing detection. Detection includes an initial detection of a first region of the image and the detection of a feature of the known pattern within a second region of the image. The second region is arranged adjacent to the first region. The initial detection is aimed at estimating at least one region parameter, such as a position of the region of the pattern, and/or orientation of the region or distortion of same. Starting from this, the second region can be selected in which a feature, such as a corner of the checkerboard is detectable. This second detection step is aimed at obtaining at least one region parameter such as the position of a feature within the second region.

Pattern detection

Image processing device for producing in real-time a digital composite image from a sequence of digital images recorded by a camera device, in particular an endoscopic camera device, the image processing device including a selecting unit, a key point detection unit, a transforming unit and a joining unit, wherein the key point detection unit includes a maximum detection unit configured for executing following steps separately for the filter response for the reference image and for the filter response for the further image, wherein a variable threshold is used:i) creating blocks by dividing the respective filter response,ii) calculating the variable threshold for each of the blocks,iii) discarding those blocks of the blocks from further consideration, in which the respective filter response at a reference point of the respective block is less than the respective variable threshold.

Image processing device and method for producing in real-time a digital composite image from a sequence of digital images

An apparatus for determining a body portion of a user treated by the user using a personal hygienic device. The apparatus includes a camera configured to capture the user to obtain a pictorial representation of the user while treating the body portion using the personal hygienic device; an interface configured to receive sensor data from at least one inertial sensor residing in the personal hygienic device; and an analyzer configured to analyze the pictorial representation and the sensor data to determine the body portion.

Determination of a currently treated body portion of a user

A device includes an input to sequential data associated to a face; a predictor configured to predict facial parameters; and a corrector configured to correct the predicted facial parameters on the basis of input data, the input data containing geometric measurements and other information. A related method and a related computer program are also disclosed.

Determining facial parameters

A 2D image analyzer includes an image scaler, an image generator and a pattern finder. The image scaler is configured to scale an image according to a scaling factor. The image generator is configured to produce an overview image including a plurality of copies of the received and scaled image, wherein every copy is scaled about a different scaling factor. Thereby, the respective position can be calculable by an algorithm, which considers a gap between the scaled images in the overview image, a gap of the scaled image towards one or more borders of the overview image and/or other predefined conditions. The pattern finder is configured to perform a feature transformation and classification of the overview image in order to output a position at which an accordance of the searched pattern and the predetermined pattern is maximal. A post-processing unit for smoothening and correcting the position of local maxima in the classified overview image may also be provided.

2D image analyzer

An apparatus for providing object information based on an image sequence including a plurality of images is provided. The apparatus includes an object detector for conducting object detection on three or more images of the plurality of images of the image sequence to obtain the object information, wherein each image of the image sequence on which object detection is conducted, is an object-detected image of the image sequence, and wherein each image of the image sequence on which object detection is not conducted, is not an object-detected image of the image sequence. Moreover, the apparatus includes an object tracker for conducting object tracking on one or more images of the image sequence to obtain the object information.

Apparatus and method for resource-adaptive object detection and tracking

Apparatus for determining model parameters, the apparatus comprising an object model transformer, a region comparator, and a model parameter determiner. The object model transformer is configured to receive an object model of a known object and to transform the object model based on a set of model parameters from a first frame of reference to a second frame of reference, and is further configured to determine as result of this transformation a transformed object model comprising at least one region that is associated to an object region of the object. The region comparator is configured to receive the transformed object model and an image depicting the object, to determine for a selected region of the transformed object model a region-related similarity measure. The model parameter determiner is configured to determine an updated set of model parameters on the basis of the region-related similarity measure and an optimization scheme.

Determining model parameters based on transforming a model of an object

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Weiden, Germany

Andreas Ernst