Disclosed are techniques for estimating a 3D bounding box (3DBB) from a 2D bounding box (2DBB). Conventional techniques to estimate 3DBB from 2DBB rely upon classifying target vehicles within the 2DBB. When the target vehicle is misclassified, the projected bounding box from the estimated 3DBB is inaccurate. To address such issues, it is proposed to estimate the 3DBB without relying upon classifying the target vehicle.

The present disclosure relates to a distance measurement method, an intelligent control method and apparatus, an electronic device, and a storage medium. The method includes: obtaining a detection bounding box of a target object in an image photographed by a current object; determining at least one distance measurement point according to the shape of the detection bounding box; and determining a distance between the target object and the current object based on the distance measurement point.

A method for training a machine learning system, in which image data are fed into a machine learning system with processing of at least a part of the image data by the machine learning system. The method includes synthetic generation of at least a part of at least one depth map that includes a plurality of depth information values. The at least one depth map is fed into the machine learning system with processing of at least a part of the depth information values of the at least one depth map. The machine learning system is then trained based on the processed image data and based on the processed depth information values of the at least one depth map, with adaptation of a parameter value of at least one parameter of the machine learning system, the adapted parameter value influencing an interpretation of input data by the machine learning system.

A vehicle control device that controls a vehicle, the vehicle control device comprising: an acquisition unit configured to acquire surrounding information of the vehicle; a recognition unit configured to recognize another vehicle traveling in surroundings of the vehicle, based on the surrounding information; a calculation unit configured to calculate a visual recognition ratio of a steering wheel of the other vehicle to a perfect circle; and a control unit configured to control the vehicle, based on the visual recognition ratio.

A vehicle control device according to an embodiment includes an imager configured to image surroundings of a host vehicle, a recognizer configured to recognize a surroundings situation of the host vehicle, a driving controller configured to control one or both of speed and steering of the host vehicle, and a controller configured to control the driving controller, wherein the controller determines a lane to which the object belongs, based on a positional relationship between left and right demarcation lines defining a host lane in which the host vehicle travels and left and right edges of an object present around the host vehicle, which are present on a two-dimensional image captured by the imager, and determines the lane to which the object belongs, based on the positional relationship between the recognized demarcation line and the edge of the object when one of the left and right demarcation lines is not recognized.

A vehicle control device according to an embodiment includes an imager configured to image surroundings of a host vehicle, a recognizer configured to recognize a surroundings situation of the host vehicle, a driving controller configured to control one or both of speed and steering of the host vehicle on the basis of a result of the recognition of the recognizer, and a controller configured to control the driving controller on the basis of imaging content of the imager, and the controller sets relative position information with respect to the host vehicle for an object around the host vehicle present on a two-dimensional image captured by the imager, and corrects the recognition result of the recognizer on the basis of the set relative position information.

An image processing apparatus and an image processing method for processing far-infrared ray images are provided. Specific temperature ranges constituted by pixels having values falling within a temperature range characteristic of a specific target are extracted from a far-infrared ray image captured of the same target. Of the specific temperature ranges, those having motion vectors close to each other are integrated so as to generate integrated ranges. The integrated ranges having motion vectors close to a global motion vector indicative of the motion of the image as a whole are excluded to obtain excluded integrated ranges. Visible light ranges corresponding to the specific temperature ranges in the excluded integrated ranges are extracted from the visible light image to generate visible light motion ranges. The positions of the visible light motion ranges are corrected on the basis of the motion vector of the excluded integrated ranges as a whole.

A vehicle control apparatus including a camera, a detector acquiring position information of a target based on reflected wave and a microprocessor. The microprocessor is configured to perform estimating a position of the target, based on position information acquired by the camera and the detector, controlling an actuator based on the estimated position, and detecting a predetermined gradient state in which a gradient of a road surface in front of a subject vehicle is an upward gradient of a predetermined degree or more with respect to a road surface at a current position of the subject vehicle and is configured to perform the estimating including estimating the position of the target by lowering a reliability of position information acquired by the camera among position information of the target captured on the road surface in the predetermined gradient state when the predetermined gradient state is detected.

In an object detection device to be installed to a vehicle and detect an object outside the vehicle, a position calculator sets multiple candidate points representing a candidate position of the object, based on positions of feature points extracted from a first image captured at a first time. The multiple candidate points are set to be denser within a detection range set based on a distance to the object detected by the ultrasonic sensor than outside the detection range. The position calculator estimates positions of the multiple candidate points at a second time which is after the first time, based on the positions of the multiple candidate points and movement information of the vehicle, and calculates the position of the object by comparing the estimated positions of the multiple candidate points at the second time and the positions of the feature points extracted from a second image captured at the second time.

A processing system including at least one processor may gather first imaging data associated with an infrastructure item via at least a first imaging device, where the first imaging data represents a first condition of the infrastructure item, and gather second imaging data associated with the infrastructure item via at least a second imaging device, where at least one of the at least the first imaging device or the at least the second imaging device is mounted on a vehicle, and where the infrastructure item is visible from a road on which the vehicle operates. The processing system may then determine a second condition of the infrastructure item in accordance with the second imaging data, where the second condition comprises a potentially unsafe condition of the infrastructure item, and generate a report of the potentially unsafe condition of the infrastructure item in response to the determining.