Techniques are disclosed for providing vehicular radiometric calibration systems and methods. In one example, a method includes capturing, by an array of infrared sensors mounted on a vehicle, a thermal image of a scene during navigation of the vehicle and/or while the vehicle is stationary. The thermal image comprises a plurality of pixel values. Each infrared sensor of the array is associated with a respective one of the plurality of pixel values. The method further includes determining temperature data associated with a portion of the scene, where the portion is associated with a subset of the plurality of pixel values. The method further includes generating a correction value based on the thermal image and the temperature data. Related systems, vehicles, and devices are also provided.

A method for determining a safe state for a vehicle includes disposing a camera at a vehicle and disposing an electronic control unit (ECU) at the vehicle. Image data is captured via the camera and provided to the ECU. An image processor of the ECU processes captured image data. A condition is determined via processing at the image processor of the ECU captured image data. The condition comprises a shadow present in the field of view of the camera within ten frames of captured image data or a damaged condition of the imager within two minutes of operation of the camera. The condition is indicative of a condition where processing of captured image data degrades in performance. The ECU determines a safe state for the vehicle responsive to determining the condition.

An illuminated sensor target includes a light source. Actuating the light source illuminates the sensor target. The illuminated sensor target is recognized by one or more sensors of a vehicle during a calibration process, and is used to calibrate the one or more sensors of the vehicle during the calibration process. The illuminated sensor target is illuminated during at least part of the calibration process, which may involve rotation of the vehicle about a turntable, with the illuminated sensor target positioned within a range of the turntable along with other sensors targets, which may also be illuminated.

Embodiments describe a method for positioning a hinged vehicle including a primary part and a secondary part coupled to the primary part at a project site. The method includes receiving, from an image capturing device, digital image data representing one or more features of the secondary part; performing image analysis on the digital image data to identify positions of the one or more features of the secondary part; identifying an angle of at least a portion of the secondary part; calculating a current position of the secondary part based on the angle; calculating a positional difference between a correct position at the project site for the secondary part and a current position of the secondary part at the project site; and initiating a change in a position of the primary part to compensate for the positional difference and to position the secondary part on the correct position.

A vehicular camera calibration system includes a camera disposed at a vehicle, and an electronic control unit (ECU). The camera calibration system uses structure-from-motion during processing at the ECU of multiple frames of image data captured with the vehicle driven in a normal manner with turns involved. The camera calibration system uses a kinematic model of motion of the vehicle that is derived at least in part from vehicle data provided to the ECU. The camera calibration system, responsive to processing of multiple frames of captured image data, and based at least in part on (i) an intrinsic parameter of the camera and (ii) the kinematic model of motion of the vehicle, determines misalignment of the camera without use of a fiducial marker in a field of view of the camera and without use of reference points on the vehicle.

An apparatus includes: a first camera configured to view an environment outside a vehicle; and a processing unit configured to receive images generated at different respective times by the first camera; wherein the processing unit is configured to identify objects in front of the vehicle based on the respective images generated at the different respective times, determine a distribution of the identified objects, and determine a region of interest based on the distribution of the identified objects in the respective images generated at the different respective times.

Vehicle headlamp for illuminating a light distribution and for detecting an obstacle in front of the headlamp, the headlamp including: (i) a housing and cover lens, (ii) an obstacle detection device including a camera, disposed inside the housing, for capturing images, and (iii) a camera calibration system for automatically calibrating the spatial orientation of the camera, the system being configured to keep the camera in a predetermined target position and including (a) an adjustment device for adjusting the spatial orientation of the camera within the housing, (b) a reference mark arranged in the housing, wherein each image has a constant predetermined reference mark position sector (PRMPS), and wherein the camera is in the target position when the reference mark is arranged within the PRMPS of the images, and (c) a control device connected to the camera and the adjustment device, the control device being configured to receive the images captured by the camera and to control the adjustment device to remove the deviation from the target position when the reference mark is outside the PRMS of the images in a non-target position.

A method of calibrating a multi-camera vision system includes moving a vehicle along a vehicle assembly line having targets at respective side regions, with each target including a longitudinal line and a plurality of tick marks that extend laterally from the longitudinal line. As the vehicle moves along the vehicle assembly line it is equipped with a plurality of cameras and an image processor. As the vehicle moves along the vehicle assembly line, the target at a respective side region of the vehicle assembly line is present within the fields of view of front, side and rear cameras. Image data is captured by the cameras and processed to detect the targets and to determine misalignment of at least one of the cameras. The vehicular multi-camera vision system is calibrated by adjusting processing by the image processor of image data captured by the at least one misaligned camera.

A method and system for determining a distance and direction between a video camera secured on a vehicle and a target point relies on an electronic control unit. The system maps and stores grid points representing a world coordinate grid onto a screen coordinate grid and displays the video image on a display using the screen coordinate grid. The system obtains a target point of an object in the video image and determines a locus of four closest grid points of the screen coordinate grid that encircle the target point. The system determines screen distances from the target point to each of the four grid points and maps the four grid points onto the world coordinate grid. The electronic control unit interpolates the location of the target point in the world coordinate grid as weighted by the screen distances. Using the video camera location in world coordinates and the target point location in world coordinates, the system determines a distance between the video camera and the target point.

An in-vehicle camera calibrator is provided. The in-vehicle camera calibrator includes a targeted camera selector for selecting a targeted camera requiring the calibration, an intermediate camera selector for selecting an intermediate camera which is the in-vehicle camera that intervenes between the targeted camera and a criterial camera, a first calibrator for, when the intermediate camera is not selected, calibrating the targeted camera based on a captured image of an overlapping region between the criterial camera and the targeted camera, and a second calibrator for, when the intermediate camera is selected, calibrating the intermediate camera based on a captured image of an overlapping region between the criterial camera and the targeted camera, and then calibrating the targeted camera based on a captured image between the calibrated intermediate camera and the targeted camera.