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Street object classification via LIDARs with only a single or a few layers

LIDAR sensors are part of the sensor system of several intelligent vehicles and transportation systems providing both object and free-space detection capabilities. In this paper a recognition method is proposed for LIDARs with only a few detection planes. Our method is especially useful in the case when angular resolution of the scan is sufficient, but in the vertical direction the planes are far from each other. The proposed method uses new features including Fourier based descriptor, deep learning classification and exploits additional 3D information if it is available. We tested the method on ten thousands of samples from a large public database. This paper gives an effective solution for a hard problem of LIDAR based recognition problems, namely the far-object detection in case of mobile LIDARs of limited or poor vertical resolution.