The electronic apparatus includes a sensing unit including at least one sensor, a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory to identify an object located near the vehicle, by using the at least one sensor, generate risk information of the object, the risk information including a type of the identified object, adjust a size of a bounding box generated to include at least a part of the identified object, based on the risk information of the object, and control a driving operation of the vehicle, based on the adjusted bounding box.

There is provided a method for searching a plurality of information sources using a multimedia element, the method may include receiving at least one multimedia element; generating, by a signature generator, for the at least one multimedia element at least one signature that is unidirectional, and yields compression; generating at least one textual search query using the at least one signature; wherein the generating of the textual search query comprises: (a) searching for at least one matching stored signature that matches one or more of the at least one signature; and (b) using a mapping between stored signatures and textual search queries, selecting at least one textual search query mapped to at least one matching stored signature; searching the plurality of information sources using the at least one textual search query; and causing a display of search results retrieved from the plurality of information sources.

An apparatus and method for compensating for an error of a vehicle sensor for enhancing performance for identifying the same object are provided. The apparatus includes a rotation angle error calculator that calculates a rotation angle error between sensor object information and sensor fusion object information. A position error calculator calculates a longitudinal and lateral position error between the sensor object information and the sensor fusion object information. A sensor error compensator calculates a sensor error based on the calculated rotation angle and a position error. In calculating the rotation angle error, the sensor error compensator corrects an error of the sensor object information based on the rotation angle error, and compensates for the sensor error based on the longitudinal and lateral position error between the corrected sensor object information and the sensor fusion object information.

A method for intelligently measuring vehicle speed based on a binocular stereo vision system includes: training a Single Shot Multibox Detector neural network to obtain a license plate recognition model; calibrating the binocular stereo vision system to acquire parameters of two cameras; detecting the license plates in the captured video frames with the license plate recognition model, locating the license plate position; performing feature point extraction and stereo matching by a feature-based matching algorithm; screening and eliminating the matching point pairs, and reserving the coordinates of the matching point pair closest to the license plate center; performing stereo measurement on the screened matching point pair to get the spatial coordinates of the position; calculating and obtaining the speed of the target vehicle. The present invention is easy to install and adjust, could simultaneously recognize multiple trained features automatically, and better suit the intelligent transportation networks and IoT (Internet of Things).

Disclosed are techniques for performing object detection and tracking. In some implementations, a process for performing object detection and tracking is provided. The process can include steps for obtaining, at a tracking object, an image comprising a target object, obtaining, at the tracking object, a first set of messages associated with the target object, determining a bounding box for the target object in the image based on the first set of messages associated with the target object, and extracting a sub-image from the image. In some approaches, the process can further include steps for detecting, using an object detection model, a location of the target object within the sub-image. Systems and machine-readable media are also provided.

Devices and methods for improving the flow of traffic at an intersection are disclosed, such as a traffic light assistance system comprising a light emitter, a light-directing device, a vehicle sensor, a traffic signal detector, and a control unit. The traffic light assistance system can be configured to detect a vehicle and direct projected light toward said vehicle to indicate a change of status of a traffic light. Such devices and methods can alert an operator of a vehicle to a change of status of a traffic light, such as a traffic signal turning green, and indicating that the operator should accelerate the vehicle. By providing means to alert otherwise distracted or inattentive drivers, time spent in traffic can be reduced.

A vehicle recognition unit of an information presenting device specifies a position of each of a plurality of vehicles, based on images captured by a plurality of imaging devices installed at a construction site. A vehicle designating unit receives designation of a designated vehicle, among the plurality of specified vehicles. A display control unit outputs a signal for displaying in an overlapping manner a proximity plot representing a position of another vehicle whose distance from the designated vehicle is less than a threshold on an overhead image of the construction site.

An electric vehicle charging system and an operation method thereof are provided. The electric vehicle charging system may include a controller, a camera configured to capture a vehicle that is present in a charging station and transmit image information about the vehicle to the controller, a guide unit configured to receive guidance from the controller and output the guidance, and a plurality of chargers provided in the charging station and communicably connected to the controller. The controller may analyze information about the vehicle based on the image information received from the camera, may guide a member vehicle registered to receive charging service to move to a charger for members, may guide a nonmember vehicle to move to a charger for nonmembers, and may adjust a ratio of the number of chargers for members to the number of chargers for nonmembers according to an estimated waiting time for charging of the vehicle. The electric vehicle charging system may transmit and receive a wireless signal on a mobile communication network constructed according to 5th generation (5G) communication.

The present disclosure relates generally to methods, systems and computer program products for classifying and identifying input data using neural networks and displaying results (e.g., images of vehicles, vehicle artifacts and geographical locations dating from the 1880s to present day and beyond). The results may be displayed on displays or in virtual environments such as on virtual reality, augmented reality and/or mixed-reality devices.

In a method for reconstruction of a feature in an environmental scene of a road, a 3D point cloud of the scene and a sequence of 2D images of the scene are generated. A portion of candidates of 3D points of the 3D point cloud is identified by projecting the 3D points to each of the 2D images, determining a plurality of candidates of the 3D points of the 3D point cloud representing the feature by semantic segmentation in each of the images, projecting the candidates of the 3D points on a plane of the road in each of the 2D images, and selecting those candidates of the 3D points staying in a projection range on the road in each of the 2D images. The selected candidates of the 3D points are merged for determining estimated locations of the feature. The feature can be modeled by generating a fitting curve along the estimated locations.