A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.

A warning device according to the present invention includes an image acquisition unit configured to acquire an image group including a plurality of images taken in succession, a detection unit configured to perform detection of an object on each of images in the image group, a determination unit configured to compare detection results of the object in the image group in chronological order and determine a degree of movement of the object, and a warning unit configured to issue a warning in accordance with the determined degree of movement, wherein the image acquisition unit acquires a plurality of image groups respectively based on a plurality of filter characteristics and the determination unit compares corresponding images between the plurality of image groups and thereby selects an image with high detection accuracy for each time period, compares the selected images in chronological order, and determines the degree of movement of the object.

A driver assistance system has a periphery monitoring device, a drive recorder, and an illuminance detecting section. The periphery monitoring device includes an imaging section that is mounted at a vehicle and captures images of a vehicle periphery, a memory, a processor that is coupled to the memory and that serves as a color tone correction processing section that corrects color tone of an image captured by the imaging section, and a display portion that displays an image having color tone that has been corrected by the color tone correction processing section. The drive recorder includes the imaging section, the memory, the processor that serves as the color tone correction processing section, and a recording section that records an image having color tone that has been corrected by the color tone correction processing section. The processor is configured so as to, in case in which an illuminance that is detected by the illuminance detecting section at a time of imaging by the imaging section is less than a predetermined reference value, correct color tone of an image captured by the imaging section such that color tone correction that is executed for recording in the recording section is color tone correction that is dark as compared with color tone correction that is executed for display at the display portion, and, in a case in which the illuminance that is detected by the illuminance detecting section at the time of imaging by the imaging section is greater than or equal to the predetermined reference value, correct the color tone of the image captured by the imaging section such that color tone correction that is executed for recording in the recording section is color tone correction that is bright as compared with color tone correction that is executed for display at the display portion.

Systems and methods for fisheye camera calibration and BEV image generation in a simulation environment. This fisheye camera calibration enables the extrinsic and intrinsic parameters of the fisheye camera to be computed in the simulation environment, where data is readily available, collectible, and manipulatable. Given a surround vision system, with multiple fisheye cameras disposed around a vehicle, and these extrinsic and intrinsic parameters, undistorted and BEV images of the surroundings of the vehicle can be generated in the simulated environment, for simulated fisheye camera testing and validation, which may then be extrapolated to real-world fisheye camera testing and validation, as appropriate. Because the simulation tool can be used to create and readily manipulate the simulated fisheye camera, the vehicle, its surroundings, obstacles, targets, markers, and the like, the entire calibration and image generation process is streamlined and may be automated.

A virtual visor system is disclosed that includes a visor having a plurality of independently operable pixels that are selectively operated with a variable opacity. A camera captures images of the face of a driver or other passenger and, based on the captured images, a controller operates the visor to automatically and selectively darken a limited portion thereof to block the sun or other illumination source from striking the eyes of the driver, while leaving the remainder of the visor transparent. The virtual visor system advantageously detects whether the driver of other passenger is performing particular head gestures and updates the optical state of the visor using suitable modified procedures that accommodate the intent or goals of the driver or other passenger that are inferred from the predefined head gesture. In general, the modified procedures reduce distracting or frustrating updates to the optical state of the visor.

A method of processing an image using a camera of a vehicle includes: a first operation of controlling a road wheel of the vehicle according to an imaging mode selected by a user from among a plurality of imaging modes, and a second operation of generating an image according to the imaging mode selected by the user by using the camera while the road wheel of the vehicle is controlled.

Methods and systems measure a vehicle body parameter; e.g., a wheel alignment parameter such as ride height. Embodiments include a system having a target attachable to a vehicle body, and an image sensor for viewing the target and capturing image data thereof. A processor processes the image data, determines an initial spatial position of the target based on the processed image data, compares the initial spatial position of the target with a reference position, and prompts a user to align the target to an adjusted spatial position when the initial spatial position differs from the reference position more than a threshold amount. The vehicle body parameter value is determined based on the target's adjusted spatial position. In certain embodiments, the adjusted spatial position differs from the reference position by a position error value, and the processor mathematically corrects the vehicle body parameter value based on the position error value.

A vehicle driving support device performs extraneous matter notification for notifying an occupant of a vehicle that extraneous matter is adhered to a viewing-angle window part which is a part of a window of the vehicle in a viewing angle range of an onboard camera which is mounted in the vehicle such that an outside view from the vehicle is imaged from the inside of the vehicle or a camera lens which is a lens of the onboard camera, performs a process of detecting the extraneous matter adhering to the viewing-angle window part or the camera lens when the vehicle is stopped, and does not perform the extraneous matter notification even if the extraneous matter adhering to the viewing-angle window part or the camera lens is detected when the vehicle is stopped and is not in a state in which the vehicle is predicted to be about to start traveling.

A vehicular vision system includes a plurality of cameras including a rear camera disposed at a rear portion of a vehicle and having at least a rearward field of view and a front camera disposed at a front portion of the vehicle and having at least a forward field of view. Responsive to processing at an electronic control unit of provided vehicle data, the vehicular vision system determines a vehicle motion vector during maneuvering of the vehicle. Responsive to image processing at the electronic control unit of frames of captured image data, the vehicular vision system determines an object present in the field of view of a camera of the plurality of cameras and determines movement of the object relative to the vehicle. The vehicular vision system compares the determined relative movement of the object to the determined vehicle motion vector to determine misalignment of the camera.

A vehicular camera module includes a camera housing, an imager printed circuit board and a processor printed circuit board. An imager is disposed at a first side of the imager printed circuit board. A heat transfer element is accommodated in the camera housing and is in thermal conductive contact with an active cooling element and with a second side of the imager printed circuit board or the processor printed circuit board. Circuitry of the camera module is electrically connected to electrical connecting elements that electrically connect to a wire harness of a vehicle when the vehicular camera module is disposed at the vehicle. With the electrical connecting elements electrically connected to the wire harness of the vehicle, heat generated by operation of the vehicular camera module is drawn from the imager printed circuit board to the camera housing via the heat transfer element.