Provided are systems and methods for detecting a vehicle with sensors that are not calibrated properly and calibrating such sensor in real-time. In one example, a method may include iteratively capturing sensor data of a road while the vehicle is travelling on the road; monitoring a calibration of the sensors of the vehicle based on the sensor data, determining that the sensors of the vehicle are not calibrated properly based on the monitoring, generating a calibration target of an object on the road based on the sensor data, and adjusting a calibration parameter of the one or more sensors of the vehicle based on the generated calibration target.

Disclosed are a vehicle path restoration system through sequential image analysis which includes: an image capturing unit that acquires sequential images from the front camera installed in the subject vehicle; an image analysis unit for generating multiple lanes that can be recognized from the sequential images of the video file acquired by the image capturing unit and multi-paths calculated using the geometric characteristics of the lanes recognized at the current time and the speed of the subject vehicle, that restores the path of the subject vehicle and restores the path of the front vehicle driving in front of the subject vehicle; a memory for storing path data of the subject vehicle and the front vehicle restored by the image analysis unit; and a display unit that expresses the path data of the subject vehicle and the front vehicle stored in the memory in the form of a top view.

A motion detecting section detects a change in relative position relation between a subject and an image capturing section performing a rolling shutter operation. A thinning-out setting section sets a thinning-out amount of a line thinning-out operation of the image capturing section according to the detection result obtained by the motion detecting section. A recognition processing section performs subject recognition in an image obtained by the image capturing section, by using a recognizer corresponding to the thinning-out amount set by the thinning-out setting section. The change in relative position relation is detected based on motion of a moving body on which the image capturing section is mounted, an image capturing scene, an image obtained by the image capturing section, and the like. Line thinning-out is performed during the rolling shutter operation, and the thinning-out amount is set according to the detection result obtained by the motion detecting section.

An image detection method determines a target object. A plurality of original images of a scene in front of a vehicle are obtained. An object in one original image is detected, and a degree of similarity between the object in the original image and the target object in a preset image is calculated. If the degree of similarity is greater than a preset similarity threshold, it is determined that the original image is a target image and the object is the target object. A position of the target object relative to the vehicle is determined and output. The method can recognize objects of interest in front of a driver.

In various examples, surface profile estimation and bump detection may be performed based on a three-dimensional (3D) point cloud. The 3D point cloud may be filtered in view of a portion of an environment including drivable free-space, and within a threshold height to factor out other objects or obstacles other than a driving surface and protuberances thereon. The 3D point cloud may be analyzed—e.g., using a sliding window of bounding shapes along a longitudinal or other heading direction—to determine one-dimensional (1D) signal profiles corresponding to heights along the driving surface. The profile itself may be used by a vehicle—e.g., an autonomous or semi-autonomous vehicle—to help in navigating the environment, and/or the profile may be used to detect bumps, humps, and/or other protuberances along the driving surface, in addition to a location, orientation, and geometry thereof.

A stereo camera apparatus includes a first imaging unit including a first imaging optical system provided with a plurality of lens groups, and a first actuator configured to change a focal length by driving at least one of the plurality of lens groups of the first imaging optical system; a second imaging unit including a second imaging optical system provided with a plurality of lens groups, and a second actuator configured to change a focal length by driving at least one of the plurality of lens groups of the second imaging optical system; a focal length controller configured to output synchronized driving signals to the first and second actuators; and an image processing unit configured to calculate a distance to a subject by using images captured by the first imaging unit and the second imaging unit.

Systems, methods, and non-transitory computer-readable media can perform operations comprising determining visual geometry detections (e.g., lane line detections) associated with geometry corresponding with a map; aligning the visual geometry detections with the geometry based on transformations associated with selected degrees of freedom; and determining a pose of a vehicle based on alignment of the visual geometry detections with the geometry.

Provided are a detection device (1) and a detection method that can detect a state of a surface of an object while reducing a constraint of a distance from the object, with a simple device configuration and easy processing. The detection device (1) includes a light source (2) that irradiates an object (10) with light (L1, L2), an image acquisition unit that acquires an image of the object, and a detection unit that detects, based on the image, a state of a surface of the object including a retro reflective material (11) on the surface.

Techniques for performing a sensor calibration using sequential data is disclosed. An example method includes receiving, from a first camera located on a vehicle, a first image comprising at least a portion of a road comprising lane markers, where the first image is obtained by the camera at a first time; obtaining a calculated value of a position of an inertial measurement (IM) device at the first time; obtaining an optimized first extrinsic matrix of the first camera by adjusting a function of a first actual pixel location of a location of a lane marker in the first image and an expected pixel location of the location of the lane marker; and performing autonomous operation of the vehicle using the optimized first extrinsic matrix of the first camera when the vehicle is operated on another road or at another time.

A method, performed by an electronic device installed in a vehicle, of switching a view of an image displayed on a camera monitoring system (CMS) side display, and an electronic device are provided. The disclosure includes an electronic device for displaying, on a camera monitoring system (CMS) side display, a first image representing a surrounding environment image, detecting a lane change signal of the vehicle, and, in response to the detected lane change signal, switching the first image displayed on the CMS side display to a second image representing a top view image showing locations of the vehicle and a surrounding vehicle in a virtual image as looking down from above the vehicle, and displaying the second image, and displaying a lane change user interface (UI) indicating information about whether a lane change is possible on the second image, and an operation method thereof.