A multiple-processor system for a multiple-lens camera is disclosed. The system comprises multiple processor components (PCs) and multiple links. Each PC comprises multiple I/O ports and a processing unit. The multiple-lens camera captures a X-degree horizontal field of view and a Y-degree vertical field of view, where X<=360 and Y<180. Each link connects one of the I/O ports of one of the PCs to one of the I/O ports of another one of the PCs such that each PC is connected by two or more respective links to one or two neighboring PCs. Each link is configured to transfer data in one direction.

Methods and systems for detecting and monitoring memory card performance characteristics. A method for detecting memory card performance characteristics includes obtaining at least one memory card performance characteristic from a memory card when the memory card is inserted in an image capture device, determining whether the at least one memory card performance characteristic meets a defined image capture device requirement, and providing an alert when the at least one memory card performance characteristic fails to match the defined image capture device requirement.

A processor-implemented method with calibration includes: detecting a preset pattern comprised in a surface of a road from a driving image of a vehicle; transforming image coordinates in an image domain of the pattern into world coordinates in a world domain; determining whether to calibrate a camera capturing the driving image by comparing a size predicted based on the world coordinates of the pattern and a reference size of the pattern; in response to a determination to calibrate the camera, determining relative world coordinates of the pattern with respect to a motion of the camera, using images captured by the camera at different time points; transforming the relative world coordinates of the pattern into absolute world coordinates of the pattern; and calibrating the camera using a corresponding relationship between the absolute world coordinates of the pattern and the image coordinates of the pattern.

A method for creating a camera model for a camera of a surgical microscope includes positioning a calibration object in an initial pose in an observation region of the camera, determining a pose delta for reaching a first pose for the calibration object in a measurement space of the camera starting from the initial pose, positioning the calibration object in the first pose in accordance with the determined pose delta, making a recording of the calibration object in the first pose with the camera, positioning the calibration object in at least one further pose, making a recording of the calibration object in the at least one further pose, and creating a camera model based on the recordings made, the first pose and the at least one further pose being chosen with a distribution in the measurement space such that a camera model is obtained which represents the entire measurement space.

An image acquisition method and apparatus are provided. By controlling a motion device, at least one of an image acquisition device or a photographed target object moves under the driving of the motion device, so that a sample image including the target object can be acquired in a preset designated acquisition pose after movement, thereby improving the accuracy of a relative pose between the image acquisition device and the target object during acquisition, reducing human intervention during acquisition, improving the automation degree, and providing the possibility for subsequent services that need to be performed according to sample images captured with relatively high shooting pose accuracy.

Implementations set forth herein relate to a camera calibration system for generating various types of calibration data by maneuvering a camera through a variety of different calibration test systems. The calibration data generated by the camera calibration system can be transmitted to the camera, which can locally store the calibration data. The calibration data can include spatial frequency response value data, which can be generated according to a spatial frequency response test that is performed by the camera calibration system. The calibration data can also include field of view values and distortion values that are generated according to a distortion test that is also performed by the camera calibration system. The camera calibration system can maneuver the camera through a variety of different calibration tests, as well as transmit any resulting calibration data to the camera for storage.

Systems and methods are disclosed for identifying a dirty camera in a monocular camera comprising n cameras. For each of one or more cycles, a dirty counter variable for each of the n cameras is set to 0. For each of the n cameras, an image is captured from the camera and an image metric is determined for the image, e.g. brightness and/or contrast. If the image metric is 10% greater, or 10% less, than the image metric for any of the other n−1 cameras in the monocular camera, then that camera is determined to be dirty and a corrective action is taken, such as sending an alarm to an occupant the vehicle or initiating a cleaning operation. If the dirty condition persists for a camera that has been cleaned within a threshold period of time (i.e., recently), then an alarm is sent to an operator of the vehicle.

A stereo camera calibration method includes: controlling a stereo camera assembly to capture a sequence of stereo image pairs; simultaneously with each capture in the sequence, activating a rangefinder; responsive to each capture in the sequence, updating calibration data for point cloud generation by: detecting matching features in the stereo image pair, and updating a first portion of the calibration data based on the matched features; updating an alignment of the rangefinder relative to the stereo camera assembly, based on the updated first portion of the calibration data, and a detected position of a beam of the rangefinder in a first image of the stereo image pair; and updating a second portion of the calibration data based on the detected position of the beam of the rangefinder in the first image of the stereo image pair, the updated rangefinder alignment, and a depth measurement captured by the rangefinder.

An apparatus includes an interface and a processor. The interface may be configured to receive pixel data representing respective fields of view of two or more cameras arranged to obtain a predetermined field of view, where the respective fields of view of each adjacent pair of the two or more cameras overlap. The processor may be configured to process the pixel data arranged as video frames and perform a fixed pattern calibration for facilitating multi-view stitching. The fixed pattern calibration may comprise applying a pose calibration process to the video frames. The pose calibration process generally uses (i) intrinsic parameters, a respective translate vector, a respective rotation matrix, and distortion parameters for each lens of the two or more cameras and (ii) a calibration board to obtain configuration parameters for the respective fields of view of the two or more cameras. The pose calibration process may comprise changing a z value of the respective translate vector for each lens of the two or more cameras to at least one of a middle distance value and a long distance value while maintaining the respective rotation matrix for each lens of the two or more cameras unchanged.

An improved method, system, and apparatus is provided to perform camera calibration, where cameras are mounted onto a moving conveyance apparatus to capture images of a multi-planar calibration target. The calibration process is optimized by reducing the number of images captured while simultaneously preserving overall information density.