Ecole Polytechnique Federale De Lausanne

Aisapack Holding Sa

Francois Fleuret

Pascal Fua

Engin Türetken

Florent Monay

Leonard Medico

Alexandre Gallet

Pierre Bruno Baqué

Salim Kayal

Xinchao Wang

The present invention generally relates to a method, a system and a computer program for shape optimisation of a technical device adapted to be exposed to a fluid flowing around a contour of said device with respect to its fluid dynamic parameters. In order to provide an improved method for shape optimisation of a technical device with respect to its fluid dynamic parameters which is faster, a method is provided comprising discretizing the shape of the technical device into a plurality of points along the contour of the technical device or into a surface mesh, and inputting the plurality of points or the surface mesh into a Convolutional Neural Network (CNN) for computing a prediction of the at least one fluid dynamic parameter.

Shape optimisation of technical devices via gradient descent using convolutional neural network proxies

Systems and methods for tracking interacting objects may acquire, with a sensor, and two or more images associated with two or more time instances. A processor may generate image data from the two or more images. The processor may apply an extended Probability Occupancy Map (POM) algorithm to the image data to obtain probability of occupancy for a container class of potentially interacting objects, probability of occupancy for a containee class of the potentially interacting objects, and a size relationship of the potentially interacting objects, over a set of discrete locations on a ground plane for each time instance. The processor may estimate trajectories of an object belonging to each of the two classes by determining a solution of a tracking model on the basis of the occupancy probabilities and a set of rules describing the interaction between objects of different or the same classes.

Systems and methods for tracking interacting objects

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Yverdon, Switzerland

Francois Fleuret