Microvision, Inc.

Ibeo Automotive Systems Gmbh

Christian Fellenberg

Julia Nitsch

Hanno Holzhüter

Frederik Lange

Thorbjörn Posewsky

Jennifer Erdmann

Cornelia Hofsäss

Cornelia HofsÄß

Hanno Holzhuter

A method for classifying targets is proposed, which comprises the extraction of features from measurement data of one or several receiving elements of a sensor by means of a neuronal network or by means of a Gaussian Mixture Model, wherein the respective measurement data of the at least one receiving element of the sensor involve at least one section of a photon histogram, and wherein the neuronal network involves a fully connected neuronal network or a convolutional neuronal network.

Method and device for classifying targets

What is proposed is a method for optically measuring distances, in the case of which a first plurality of measuring pulses is emitted during a first measuring interval by means of a transmitting element of a transmitting unit at first emitting times, and wherein a second plurality of measuring pulses is emitted during a second measuring interval by means of the transmitting element of the transmitting unit at second emitting times. The method comprises the reception of reflected measuring pulses by means of a receiving element of a receiving unit assigned to the transmitting element at receiving times. The method further comprises the determining of a first amount of times-of-flight for each received measuring pulse, wherein the first amount of times-of-flight is determined by using the first emitting times.

Method and device for optically measuring distances

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Hamburg, Germany

Christian Fellenberg