Abstract: The present disclosure relates to a method of selecting an accident image by using speed profile analysis, which can sufficiently secure an available capacity of a storage medium, can reduce the amount of transmission data and a fee therefor, and can prevent a loss of unnecessary management expenses, by selecting an actual accident image by using speed profile analysis before and after the occurrence of an impact event and deleting, from the storage medium, an image having a grade determined to have a low accident possibility or changing a state of the image into an overwriteable state or taking measures for preventing the transmission of the image to a cloud server.

Abstract: A driver anonymity-ensured shared vehicle-driving information management system includes a main camera, a sensor, an auxiliary camera, a memory unit, and a processor. The processor includes a driving record generation section configured to generate a driving record of the vehicle on the basis of an image taken by the main camera and sensing data detected by the sensor, a facial feature vector extraction section configured to extract a driver facial feature vector by irreversibly encoding the driver image taken by the auxiliary camera so that the driver image is not able to be restored to the original driver image, and an anonymous driver driving information storage section configured to match the driver facial feature vector with the driving record and stores the matched data in the memory unit.

Abstract: The present disclosure relates to a method of selecting an accident image using the results of the recognition of an obstacle on a road, which can distinguish between an actual accident image and a fake accident image by previously recognizing an obstacle on a road while a vehicle travels and determining an impact event to have a low accident possibility, the impact event occurring in a section in which the vehicle goes over the obstacle, or suppressing the impact event, and can secure a space of a storage medium by deleting the fake accident image or prevent a data usage fee and unnecessary management expenses by blocking the transmission of the fake accident image to a remote cloud server.

Abstract: The present disclosure relates to a system for predicting a near future location of an object, which predicts a near future location of a dynamic object, through learning for sampling a sample obtained by estimating a location of the dynamic object by learning an image at current timing, which is captured by a camera, based on artificial intelligence and for changing the sample of the dynamic object whose location has been estimated into a Gaussian mixture model (GMM) by using history data.

Abstract: The present disclosure relates to a method of selecting an accident image by using speed profile analysis, which can sufficiently secure an available capacity of a storage medium, can reduce the amount of transmission data and a fee therefor, and can prevent a loss of unnecessary management expenses, by selecting an actual accident image by using speed profile analysis before and after the occurrence of an impact event and deleting, from the storage medium, an image having a grade determined to have a low accident possibility or changing a state of the image into an overwritable state or taking measures for preventing the transmission of the image to a cloud server.

Abstract: The present disclosure relates to a method of selecting an accident image using the results of the recognition of an obstacle on a road, which can distinguish between an actual accident image and a fake accident image by previously recognizing an obstacle on a road while a vehicle travels and determining an impact event to have a low accident possibility, the impact event occurring in a section in which the vehicle goes over the obstacle, or suppressing the impact event, and can secure a space of a storage medium by deleting the fake accident image or prevent a data usage fee and unnecessary management expenses by blocking the transmission of the fake accident image to a remote cloud server.

Abstract: The present disclosure relates to a method of selecting an accident image by using speed profile analysis, which can sufficiently secure an available capacity of a storage medium, can reduce the amount of transmission data and a fee therefor, and can prevent a loss of unnecessary management expenses, by selecting an actual accident image by using speed profile analysis before and after the occurrence of an impact event and deleting, from the storage medium, an image having a grade determined to have a low accident possibility or changing a state of the image into an overwritable state or taking measures for preventing the transmission of the image to a cloud server.

Abstract: The present disclosure relates to a system for predicting a near future location of an object, which predicts a near future location of a dynamic object, through learning for sampling a sample obtained by estimating a location of the dynamic object by learning an image at current timing, which is captured by a camera, based on artificial intelligence and for changing the sample of the dynamic object whose location has been estimated into a Gaussian mixture model (GMM) by using history data.

Abstract: Disclosed is a lane departure warning determination method using driver state monitoring, which includes (a) recognizing a lane around a vehicle from an image photographed by a lane recognition camera and extracting lane information; (b) extracting facial feature points of a driver from an image photographed by a driver recognition camera; (c) determining from the lane information whether the vehicle is in a lane departure state or a lane approaching state; (d) when it is determined in step (c) that the vehicle is in the lane departure state, generating a warning when a face tilt of the driver exceeds a first angle; and (e) when it is determined in step (c) that the vehicle is in the lane approaching state, generating a warning when the face tilt of the driver exceeds a second angle.

Abstract: Disclosed is a lane departure warning determination method using driver state monitoring, which includes (a) recognizing a lane around a vehicle from an image photographed by a lane recognition camera and extracting lane information; (b) extracting facial feature points of a driver from an image photographed by a driver recognition camera; (c) determining from the lane information whether the vehicle is in a lane departure state or a lane approaching state; (d) when it is determined in step (c) that the vehicle is in the lane departure state, generating a warning when a face tilt of the driver exceeds a first angle; and (e) when it is determined in step (c) that the vehicle is in the lane approaching state, generating a warning when the face tilt of the driver exceeds a second angle.

Abstract: The present invention relates to a pedestrian recognition apparatus. A pedestrian recognition apparatus may comprises: an image receiving unit configured to sequentially receive a plurality of images from a camera; and a pedestrian determination unit configured to perform a pedestrian candidate object detection process of detecting a pedestrian candidate object from one or more objects in the images, a mobility determination process of determining whether the pedestrian candidate object is moving, using the plurality of images, and setting the pedestrian candidate object to a moving pedestrian candidate object, and a pedestrian possibility determination process of performing a predefined operation on the moving pedestrian candidate object, and setting the moving pedestrian candidate object to a pedestrian when a value calculated through the predefined operation is equal to or more than a threshold value.

Abstract: A side safety assistant device for a large vehicle may include: a rear camera module mounted at the rear of at least one side surface of a large vehicle and configured to image an object while facing the front of the large vehicle; a front camera module mounted at the front of at least one side surface of the large vehicle and configured to image an object while facing the rear of the large vehicle; one or more image recognition modules configured to receive an image taken by the rear and front camera modules, extract an object included in the image, determine whether the extracted object is a moving object, determine whether the moving object is located in a preset dangerous zone, and output a collision risk signal; a warning unit configured to output a visual or auditory warning signal; and a control unit configured to operate the warning unit.

Abstract: A moving object collision warning system for a large vehicle may include: a rear camera module mounted on the rear of at least one side of a large vehicle, and configured to take an image of an object while facing the front of the large vehicle; an image receiving unit configured to receive the image taken by the rear camera module; a moving object determination unit configured to recognize the image received by the image receiving unit, extract an object included in the image, and determine whether the extracted object is a moving object, wherein the moving object includes one or more of a bicycle, a two-wheeled vehicle and a pedestrian; a moving object collision possibility determination unit configured to determine whether the moving object determined by the moving object determination unit is located in a preset danger zone, and output a collision risk signal; a warning unit configured to output a visual or audible warning signal to a driver of the large vehicle; and a control unit configured to operate t

Abstract: A vanishing point correction method may include the steps of: (a) extracting a contour candidate point of an object considered as the forward vehicle from the image taken by the camera; (b) tracking a movement of the contour candidate point over time; (c) determining whether the contour candidate point belongs to the vehicle; (d) setting the contour candidate point to a vehicle contour point of the forward vehicle, when it is determined at the step (c) that the contour candidate point belongs to the vehicle; (e) calculating a variation in width between vehicle contour points at the same height among the vehicle contour points; and (f) calculating a variation of the vanishing point.

Abstract: Provided is a cold-storage heat exchanger. The cold-storage heat exchanger includes a pair of header tanks, and tubes which are arranged in three rows with respect to the direction of the flow of air and connected at opposite sides thereof to the header tanks. A cold-storage medium is stored in the tubes that are disposed in a middle row, and refrigerant circulates through the tubes that are disposed in front and rear rows. Therefore, the cold-storage medium can effectively store cold-energy transferred from the refrigerant. When the engine of a vehicle is stopping, the cold-storage heat exchanger can discharge the cold-energy that has been stored into the passenger compartment of the vehicle, thus preventing the temperature in the passenger compartment from rapidly increasing, thereby creating pleasant air-conditioned conditions for a user, and minimizing the energy and time required to re-cool the passenger compartment.

Abstract: A forward collision warning method may include the steps of: (a) extracting a contour candidate point of an object considered as the forward vehicle from an image taken by a camera; (b) tracking a movement of the contour candidate point over time; (c) determining whether the contour candidate point belongs to the vehicle; (d) setting the contour candidate point to a vehicle contour point of the forward vehicle, when it is determined at the step (c) that the contour candidate point belongs to the vehicle; (e) estimating a height of the vehicle contour point from the ground surface; (f) calculating a relative distance to the forward vehicle through Equation below; and (g) calculating a time to collision (TTC) using the relative distance: Z = ? ? ? h - Yc yc .

Abstract: A side safety assistant device for a large vehicle may include: a rear camera module mounted at the rear of at least one side surface of a large vehicle and configured to image an object while facing the front of the large vehicle; a front camera module mounted at the front of at least one side surface of the large vehicle and configured to image an object while facing the rear of the large vehicle; one or more image recognition modules configured to receive an image taken by the rear and front camera modules, extract an object included in the image, determine whether the extracted object is a moving object, determine whether the moving object is located in a preset dangerous zone, and output a collision risk signal; a warning unit configured to output a visual or auditory warning signal; and a control unit configured to operate the warning unit.

Abstract: A moving object collision warning system for a large vehicle may include: a rear camera module mounted on the rear of at least one side of a large vehicle, and configured to take an image of an object while facing the front of the large vehicle; an image receiving unit configured to receive the image taken by the rear camera module; a moving object determination unit configured to recognize the image received by the image receiving unit, extract an object included in the image, and determine whether the extracted object is a moving object, wherein the moving object includes one or more of a bicycle, a two-wheeled vehicle and a pedestrian; a moving object collision possibility determination unit configured to determine whether the moving object determined by the moving object determination unit is located in a preset danger zone, and output a collision risk signal; a warning unit configured to output a visual or audible warning signal to a driver of the large vehicle; and a control unit configured to operate t

Abstract: A forward collision warning method may include the steps of: (a) extracting a contour candidate point of an object considered as the forward vehicle from an image taken by a camera; (b) tracking a movement of the contour candidate point over time; (c) determining whether the contour candidate point belongs to the vehicle; (d) setting the contour candidate point to a vehicle contour point of the forward vehicle, when it is determined at the step (c) that the contour candidate point belongs to the vehicle; (e) estimating a height of the vehicle contour point from the ground surface; (f) calculating a relative distance to the forward vehicle through Equation below; and (g) calculating a time to collision (TTC) using the relative distance: Z=?h?Yc/yc ??Equation.

Abstract: The present invention relates to a pedestrian recognition apparatus. A pedestrian recognition apparatus may comprises: an image receiving unit configured to sequentially receive a plurality of images from a camera; and a pedestrian determination unit configured to perform a pedestrian candidate object detection process of detecting a pedestrian candidate object from one or more objects in the images, a mobility determination process of determining whether the pedestrian candidate object is moving, using the plurality of images, and setting the pedestrian candidate object to a moving pedestrian candidate object, and a pedestrian possibility determination process of performing a predefined operation on the moving pedestrian candidate object, and setting the moving pedestrian candidate object to a pedestrian when a value calculated through the predefined operation is equal to or more than a threshold value.