PROCESSING A DATA STREAM OF SCANS CONTAINING SPATIAL INFORMATION PROVIDED BY A 2D OR 3D SENSOR CONFIGURED TO MEASURE DISTANCE BY USING A CONVOLUTIONAL NEURAL NETWORK (CNN)

摘要

The present invention relates to a device (1) for processing a data stream of scans containing spatial information provided by a 2D or 3D sensor (2) configured to measure distance, wherein the device (1) is configured to employ a Convolutional Neural Network (3), CNN, in an inference phase. The CNN comprises a first layer (L1) and one or more further layers (L2a, L2b) following the first layer (L1) and one or more first buffers (4a) for storing an output tensor of a respective preceding layer (L1; L2). The device (1) is further configured to input data of a current scan provided by the 2D or 3D sensor (2) in the form of a current tensor (epc(ti)) into the CNN (3); and perform, at each further layer (L2a; L2b), one or more convolutional operations on the basis of a current output tensor (a1(ti); a2(ti)) of the preceding layer (L1; L2a) originating from the data of the current scan and a previous output tensor (al (ti-1); a2(ti-1)) of the preceding layer (L1, L2a). The previous output tensor (al(ti-1), a2(ti-1)) of the preceding layer (L1, L2a) is the newest tensor stored in the respective first buffer (4a) of the one or more first buffers (4a) and originates from data of a previous scan inputted to the CNN directly before the data of the current scan. Furthermore, the device (1) is configured to store the current output tensor (a1(ti), (a2(ti)) of the preceding layer (L1, L2a) as the newest tensor in the respective first buffer (4a).