Abstract: A method and device for determining an ego-motion of a vehicle are disclosed. Respective sequences of consecutive images are obtained from a front view camera, a left side view camera, a right side view camera and a rear view camera and merged. A virtual projection of the images to a ground plane is provided using an affine projection. An optical flow is determined from the sequence of projected images, an ego-motion of the vehicle is determined from the optical flow and the ego-motion is used to predict a kinematic state of the car.

Abstract: The application provides a method of calibrating a camera of a vehicle. The vehicle has a reference frame. The method comprises taking an image of a scene by the camera. The ground plane of the vehicle is then determined according to features of the image. An origin point of the vehicle reference frame is later defined as being located on the determined ground plane. A translation of a reference frame of the camera is afterward determined for aligning the camera reference frame with the vehicle reference frame.

Abstract: A method and a device for image stabilization of an image sequence of one or more cameras of a vehicle are disclosed. Images of the surroundings of the vehicle are recorded and image points of the recorded images are projected to a unit sphere, where the projection includes applying a lens distortion correction. For each of the one or more cameras, a vanishing point is calculated using the projected image points on the unit sphere and a motion of the vanishing point on the unit sphere is tracked. The motion of the vanishing point is used to calculate a corrected projection to a ground plane.

Abstract: Image data is retrieved from the camera and an image of a neighbouring vehicle is acquired. A vehicle model is derived from the image data and the vehicle model is used to retrieve dimensional information from an onboard database. The dimensional information is correlated with the image data and the correlation is used to determine extrinsic camera parameters.

Abstract: The application provides a method of calibrating a camera of a vehicle. The vehicle has a reference frame. The method comprises taking an image of a scene by the camera. The ground plane of the vehicle is then determined according to features of the image. An origin point of the vehicle reference frame is later defined as being located on the determined ground plane. A translation of a reference frame of the camera is afterward determined for aligning the camera reference frame with the vehicle reference frame.

Abstract: A method and a device for image stabilization of an image sequence of one or more cameras of a vehicle are disclosed. Images of the surroundings of the vehicle are recorded and image points of the recorded images are projected to a unit sphere, where the projection includes applying a lens distortion correction. For each of the one or more cameras, a vanishing point is calculated using the projected image points on the unit sphere and a motion of the vanishing point on the unit sphere is tracked. The motion of the vanishing point is used to calculate a corrected projection to a ground plane.

Abstract: A method and device for determining an ego-motion of a vehicle are disclosed. Respective sequences of consecutive images are obtained from a front view camera, a left side view camera, a right side view camera and a rear view camera and merged. A virtual projection of the images to a ground plane is provided using an affine projection. An optical flow is determined from the sequence of projected images, an ego-motion of the vehicle is determined from the optical flow and the ego-motion is used to predict a kinematic state of the car.

Abstract: The invention relates to a method for recognizing a covered state of a camera (4) of a motor vehicle (1) by providing an image of an environmental region of the motor vehicle (1) by means of the camera (4), determining respective brightness values of pixels within at least one image region of the image, determining a number of pixels within the at least one image region, which satisfy a preset criterion with respect to the brightness values, and checking whether the camera (4) is covered or not covered depending on the number.