Universität Zu Lübeck

Euroimmun Medizinische Labordiagnostika Ag

Universitat Zu Lubek

Gestigon Gmbh

Thomas Martinetz

Erhardt Barth

Martin Haker

Christopher Krause

Sascha Klement

Kristian Ehlers

Fabian Timm

Stöcker Winfried

Hendrik Fauer

Winfried STÖCKER

The invention relates to a real time-capable analysis of a sequence of electronic images for estimating the pose of a movable object captured by means of the images. The invention further relates to implementing the invention in software and, in this connection, to a computer-readable medium that stores commands, the execution of which causes the method according to the invention to be carried out. The invention proceeds from a skeleton model, which is described by a small number of nodes in 3D space and permits a good data compression of the image information when the co-ordinates of the nodes describe at any time the position of predetermined parts of the moving object. The skeleton model simultaneously represents previous knowledge of the object, by defining e.g. node pairs and optionally also node triplets in the skeleton model that describe cohesive object parts or optionally object surfaces, which are contained in the measured 2&#xbd;-D image information, i.e. are visible to the camera. The skeleton model is to be fitted quickly and accurately into the image information. The fitting is effected between two images of an image sequence by the continuous displacement of the nodes and the continuous updating of the skeleton model.

Method and apparatus for estimating a pose

The invention relates to a method for the real-time-capable, computer-assisted analysis of an image sequence of an object consisting of elements that can be moved relative to each other and are interconnected, said sequence containing a variable pose, wherein the individual images of the image sequence are recorded by way of a time-of-flight (TOF) camera such that said images can be processed by a computer, and contain brightness and distance data as functions of the pixel coordinates of the camera for each image of the sequence, comprising the following steps: a. Capturing the pixels of an individual image forming the object, b. calculating a three-dimensional (3D) point cloud in a virtual space, said point cloud representing the surface of the object that is visible to the camera, by a computational projection of object-depicting pixels in such a space, while taking captured distance data to the object into consideration, c. fitting a model of the object consisting of nodes and edges into the computer-generated 3D point cloud for the individual images, wherein the nodes represent a selection of elements of the object and the edges represent the connections of said elements amount each other, d. iteratively updating all node positions by applying a learning rule for training a self-organizing map having a previously defined number of randomly selected dots of the point cloud, e. repeating steps a. to d. for each subsequent individual image of the sequence, wherein for the fitting in step c. the result of step e. of the preceding image is used in each case, and f. determining the varying pose from the positions of predetermined nodes of the model which have been captured in at least representative images of the image sequence.

Method for the real-time-capable, computer-assisted analysis of an image sequence containing a variable pose

The invention relates to a method for optimizing the automatic fluorescence pattern recognition in immunodiagnosis. In this method, in addition to or together with the fluorescence dye, one or more other indicator dyes for the identification of relevant structures are incubated before an image is taken with a camera.

Method for optimizing automatic fluorescence pattern recognition in immunodiagnosis

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Lübeck, Germany

Thomas Martinetz