Agt International Gmbh

Roel Heremans

Markus Schlattmann

Marco Huber

Christian Debes

Michael Leigsnering

Henning Hamer

Peter Weidenkaff

Arsenii Sawchuk

Juergen Hahn

Andreas Merentitis

Agoston Torok

According to one aspect of the presently disclosed subject there is provided a computerized method for scoring performance of a move of a trainee in a trainee frame input in relation to a move of a trainer in a trainer video wherein the trainer move includes at least one trainer keyframe. The method comprising obtaining a trainee frame input comprising a trainee move, the trainee move comprising a plurality of trainee frames, based on the at least one trainer keyframe, processing the plurality of trainee frames to provide a move performance score, indicative of the performance of the trainee move in relation to the trainer move, with respect to at least one aspect of the performance. In some examples, the aspects can be one of a similarity aspect, a timing aspect, or a motion dynamics aspect or a combination thereof.

Method of scoring a move of a user and system thereof

A method for automatic spatial calibration of a network of cameras along a road includes, processing a frame that is obtained from each camera of the network to automatically identify an image of a pattern of road markings that have a known spatial relationship to one another. The identified images are used to calculate a position of each camera relative to the pattern of road markings that is imaged by that camera. Geographical information is applied to calculate an absolute position of a field of view of each camera. A global optimization is applied to adjust the absolute position of the field of view of each camera of the camera network relative to an absolute position of the fields of view of other cameras of the camera network.

Automatic spatial calibration of camera network

An object-recognition method and system employing Bayesian fusion algorithm to reiteratively improve probability of correspondence between captured object images and database object images by fusing probability data associated with each of plurality of object image captures.

Fusion-based object-recognition

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Darmstadt, Germany

Roel Heremans