Continental Teves, Ag and Company Ohg

Claudio Heller

Claudia Loy

Christopher Bayer

Alexey Abramov

A method of detecting lanes includes the steps: capturing (S1) a camera image (K) of a vehicle environment by a camera device (2) of a vehicle (5); determining (S2) feature points (P1 to P15) in the camera image (K), which feature points correspond to regions of possible lane boundaries (M1, M2); generating (S3) image portions of the captured camera image (K) respectively around the feature points (P1 to P15); analyzing (S4) the image portions using a neural network to classify the feature points (P1 to P15); and determining (S5) lanes in the vehicle environment taking account of the classified feature points (P1 to P15).

Method and device for detecting lanes, driver assistance system and vehicle

A method for automatically establishing extrinsic parameters of a camera of a vehicle includes repeatedly establishing the extrinsic parameters of the camera during a measurement run, wherein sensor data are generated by a sensor each time the extrinsic parameters of the camera are established. The established parameters and the associated sensor data respectively are stored in a database. A convolutional neural network is trained based on the extrinsic parameters stored in the database and based on the sensor data. The extrinsic parameters of the camera are subsequently determined online by utilizing the trained convolutional neural network.

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Munich, Germany

Claudio Heller