Abstract: Object detection in a scene is based on lidar data and radar data of the scene. The lidar data and the radar data are transformed to a common coordinate system. Different radar point clusters are extracted from the radar data. Different lidar point clusters are extracted from the lidar data and each lidar point cluster is associated with a target object. A target object's velocity is estimated based on the movement of the respective lidar point cluster between consecutive lidar images. The estimated target object's velocity is compared with velocity information of a corresponding radar point cluster to identify corresponding radar and lidar point clusters.

Abstract: A method for a vehicle obtains camera sensor data of a camera of the vehicle. The method further obtains lidar sensor data of a lidar sensor of the vehicle. The method determines information related to a motion of the vehicle. The method determines a combined image of the camera sensor data and the lidar sensor data based on the information related to the motion of the vehicle.

Abstract: Object detection in a scene is based on lidar data and radar data of the scene. The lidar data and the radar data are transformed to a common coordinate system. Different radar point clusters are extracted from the radar data. Different lidar point clusters are extracted from the lidar data and each lidar point cluster is associated with a target object. A target object's velocity is estimated based on the movement of the respective lidar point cluster between consecutive lidar images. The estimated target object's velocity is compared with velocity information of a corresponding radar point cluster to identify corresponding radar and lidar point clusters.

Abstract: A method for a vehicle obtains camera sensor data of a camera of the vehicle. The method further obtains lidar sensor data of a lidar sensor of the vehicle. The method determines information related to a motion of the vehicle. The method determines a combined image of the camera sensor data and the lidar sensor data based on the information related to the motion of the vehicle.

Abstract: A vehicle movement parameter, such as ego-speed, is estimated using real-time images captured by a single camera. The captured images may be analyzed by a pre-trained convolutional neural network to estimate vehicle movement based on monocular video data. The convolutional neural network may be pre-trained using filters from a synchrony autoencoder that were trained using unlabeled video data captured by the vehicle's camera while the vehicle was in motion. A parameter corresponding to the estimated vehicle movement may be output to the driver or to a driver assistance system for use in controlling the vehicle.

Abstract: A vehicle movement parameter, such as ego-speed, is estimated using real-time images captured by a single camera. The captured images may be analyzed by a pre-trained convolutional neural network to estimate vehicle movement based on monocular video data. The convolutional neural network may be pre-trained using filters from a synchrony autoencoder that were trained using unlabeled video data captured by the vehicle's camera while the vehicle was in motion. A parameter corresponding to the estimated vehicle movement may be output to the driver or to a driver assistance system for use in controlling the vehicle.