Feature Extraction in Scanning Laser Range Data Using Invariant Parameters: Application to Vehicle Detection

This paper presents a feature extraction method in scanning laser range data. Many authors have studied this problem by proposing solutions that rely on a modeling of the scene in Cartesian coordinates. These methods are based on the computation of the interscan distance between two consecutive measurements, which, in practice, is not very easy to estimate. Our proposed method, i.e., segmentation using invariant parameters (SIP), deals with laser measurements in natural coordinates, which avoids any preprocessing stage that could modify the measurement noise statistics. This approach is founded on the use of an invariant description of the feature and leads to the definition of a criterion of line-segment detection that only depends on the sensor intrinsic parameters.