An image processing device includes a brightness image creating portion configured to create a brightness image showing a brightness distribution in a color image captured by a camera, a saturation image creating portion configured to create a saturation image showing a saturation distribution in the color image, and an analyzed image creating portion configured to create an analyzed image for detecting a predetermined target by synthesizing the brightness image and the saturation image.

Embodiments of the disclosure provide methods and systems for predicting a trajectory of a vehicle. An exemplary system includes a communication interface configured to receive a map of an area in which the vehicle is traveling and sensor data acquired associated with the vehicle. The system includes at least one processor configured to position the vehicle in the map and identify one or more objects surrounding the vehicle based on the positioning of the vehicle. The at least one processor is further configured to extract features of the vehicle and the one or more objects from the sensor data. The at least one processor is also configured to determine a plurality of candidate trajectories, determine a probability for each candidate trajectory based on the extracted features, and identify the candidate trajectory with the highest probability as the predicted trajectory of the vehicle.

A method for monitoring headway to an object performable in a computerized system including a camera mounted in a moving vehicle. The camera acquires in real time multiple image frames including respectively multiple images of the object within a field of view of the camera. An edge is detected in in the images of the object. A smoothed measurement is performed of a dimension the edge. Range to the object is calculated in real time, based on the smoothed measurement.

A method and an apparatus for the evaluation of detection results of components for road detection, of the road estimated by a road estimation, and/or of the planned trajectory of the driver assistance systems of an ego-transportation vehicle, wherein the detection results, the estimated road, and the planned trajectory are designated a hypothesis. To evaluate the components, the road estimation, or the driver assistance system, use is made of a metric based on the manually covered trajectory of the ego-transportation vehicle, wherein the deviation between the manually traveled trajectory and the hypothesis is determined for predefined reference points at a predefined interval from a starting point in a transportation vehicle-based x-y coordinate system and by using the evaluation, it is determined whether the hypothesis of the components for road detection, the road estimation, and/or the driver assistance system fulfill predefined criteria.

A line detection device (10) includes a first detection unit (100) and a second detection unit (200). The first detection unit (100) extracts a pixel located in a range having a predetermined color from an image including a traveling path on which a mobile object travels, and specifies a line of a first color included in the image using a distribution of the extracted pixel in the image. After execution by processing by the first detection unit (100), the second detection unit (200) extracts a pixel located in a luminance range having a predetermined luminance from the image and specifies a line of a second color which is included in the image and is different from the first color using a distribution of the extracted pixel in the image.

Disclosed herein is a vehicle control apparatus, vehicle control system and image sensor. The vehicle control apparatus includes a first sensor configured to be disposed on the vehicle to have a view to the outside of the vehicle and capture image data and a controller configured to include at least one processor to process the image data captured by the first sensor, wherein the controller recognizes a roundabout based on the processing result of the image data, sets a region of interest in front of the vehicle based on a state information of the roundabout obtained from the processing result of the image data, determines a target located in the region of interest based on information of the target location based on the processing result of the image data, and controls the vehicle based on the information of the target location in the region of interest. According to the embodiment of the disclosed invention, the vehicle may enter a roundabout safely.

Provided is a method and apparatus for detecting a vanishing point in a driving image of a vehicle. The method includes: receiving the driving image; generating a probability map, comprising probability information about a position of the vanishing point in the driving image, from the driving image; detecting a vanishing point on the driving image by applying smoothing regression, which softens a boundary region of the vanishing point, to the probability map; and processing a task for driving the vehicle by converting an orientation of the driving image based on the vanishing point.

A computing device is programmed to generate a plurality of raw 3D point clouds from respective sensors having non-overlapping fields of view, scale each of the raw point clouds including scaling real-world dimensions of one or more features included in the respective raw 3D point cloud, determine a first transformation matrix that transforms a first coordinate system of a first scaled 3D point cloud of a first sensor to a second coordinate system of a second scaled 3D point cloud of a second sensor, and determine a second transformation matrix that transforms a third coordinate system of a third scaled 3D point cloud of a third sensor to the second coordinate system of the second scaled 3D point cloud of the second sensor. The computing device is programmed, based on the first and second transformation matrices, upon detecting an object in a first or third camera field of view, determine location coordinates of the object relative to a coordinate system that is defined based on the second coordinate system; and output the determined location coordinates of the object.

A vehicle parking assistance device includes an image sensing device, an artificial intelligence learning device, and a controller connected with the image sensing device and the artificial intelligence learning device. The controller is configured to obtain an image using the image sensing device, detect at least one parking line pair in the obtained image, detect a parking slot based on deep learning, detect a parking area based on the detected parking slot and the at least one detected parking pair, detect an entrance point for the parking area, and generate parking information based on the parking area and the entrance point.

A navigation system for a host vehicle is provided. The system may comprise at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify at least one vehicle-induced occlusion zone in an environment of the host vehicle; and cause a navigational change for the host vehicle based, at least in part, on a size of a target vehicle that induces the identified occlusion zone.