Techniques are disclosed. The techniques include receiving, from a camera, an image showing a portion of a physical topography and target object. The techniques include determining, based on the image, a location of the target object shown in the image and a physical characteristic of the target object shown in the image, the physical characteristic being common with at least another target object. The techniques then include determining a three dimensional (3D) position of the target object in a 3D representation of the portion of the physical topography, the 3D position determined based on (i) the location of the target object, and (ii) the physical characteristic. Based on detecting a cluster of 3D positions of target objects (over several images), the techniques involve generating a 3D boundary of a zone of a portion of the physical topography.

A vehicular trailer hitching assist system includes a camera disposed at a rear portion of a vehicle and having a field of view exterior of the vehicle, the field of view encompassing at least a portion of a trailer rearward of the vehicle. The camera captures image data representative of the trailer rearward of the vehicle. A control includes a processor operable to process image data captured by the camera. The control, responsive to processing of image data captured by the camera, detects a trailer hitch coupler of the trailer rearward of the vehicle. The control, responsive to detecting the trailer hitch coupler, estimates an initial height and an initial location of the detected trailer hitch coupler. The ECU tracks the position of the trailer hitch coupler in subsequent frames and the ECU selects a current frame and a previous frame of captured image data to refine the initial height.

A self position estimation method is provided which is capable of accurately estimating, when executing automatic parking to a parking target position using a stored surrounding situation, a position of a host vehicle or a target in the surrounding situation stored in a storage device. The method includes a step that presents the stored surrounding situation, a step that receives an operation of setting a positional relationship between the stored surrounding situation, and at least one of the host vehicle and the targets existing around the host vehicle, and a step that sets a position of at least one of the host vehicle and the target in the stored surrounding situation based on the operation.

A detection system implemented in a vehicle to detect free parking space is disclosed. The system comprises an input unit for imaging perspective view around the vehicle and a processing unit to receive a sequence of images from the at least one image sensor and detect at least one polygon pertaining to a parking slot in at least one image of the sequence of images, transform the at least one image into a bird's-eye-view image using a homography matrix, detect at least one quadrilateral pertaining to a parking slot, transform the bird's-eye-view image comprising the at least one quadrilateral, into corresponding image pertaining to perspective view around the vehicle using an inverse homography matrix, to analyse real world co-ordinates of the parking slot, and determine type of the parking slot by computing real world dimensions based on analysis of the real world co-ordinates of the parking slot.

A parking enforcement device can be secured to a surface adjacent to the area designated as NO PARKING. The enforcement device can include a camera aimed towards the area designated as NO PARKING and monitor this area for the entry of a vehicle. A parking violation is determined to have occurred upon determining that the vehicle has entered the area designated as NO PARKING, and image data of the entry of a vehicle into the NO PARKING area that was captured by the camera can be relayed to a remote computing system. The parking enforcement device can be provided as a bollard that includes a camera secured to a center pole extending vertically upwards inside of the bollard. The camera can be located along the center pole so that the camera views outward from the bollard via a window section of the bollard.

An image processing device includes a sideline detector configured to detect sidelines of boundary lines of parking sections next to each other in a vehicle width direction by an edge detection process to an image, each of the sidelines being a pair of a rising edge and a falling edge, and to acquire an end point of each of the sidelines at which the pair is not detected, a rear-end edge identifying part configured to identify a rear-end edge of the parking section based on an end point away from the vehicle among the end points acquired by the sideline detector, and a parking frame setting portion configured to identify the parking section based on the two sidelines detected by the sideline detector and the rear-end edge identified by the rear-end edge identifying part, and to set a parking frame based on the parking section.

A system, comprising a computer having a processor and a memory storing instructions executable by the processor to identify a height of a curb that is at least one of within or bordering a parking area having a specified length and width. The instructions include instructions to identify a location of the curb. The instructions include instructions to determine a parking position within the parking area based on the height of the curb and the location of the curb. The instructions include instructions to park a vehicle at the parking position within the parking area.

The present disclosure relates to an indoor positioning method for operating an indoor positioning system and an indoor positioning apparatus by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm in a 5G environment connected for the Internet of Things. The indoor positioning method according to an embodiment of the present disclosure includes receiving map data and map information data of an indoor map in response to a presence of the indoor map of an indoor space, acquiring an image of the indoor space at a device camera, comparing image information of the indoor map with the acquired image information of the indoor space based on the map data and the map information data of the indoor space, and performing indoor localizing of the indoor space based on a result of the comparing.

A data management system includes an information processing device and a data management device. The information processing device acquires an overall map from a storage in the data management device, estimates a location of the moving object at the time of capturing each of peripheral images that are determined to correspond to any of the key frame images which are stored in the storage among the peripheral images, and generate a local map representing each of the peripheral images which are determined as the key frame image. The management device updates a portion, corresponding to the local map, of the overall map stored in the storage based on the local map.

A vehicle parking assist apparatus acquires a camera image when the vehicle stops by a non-determined parking lot and acquires feature points of a ground of an entrance of the non-determined parking lot as non-compared entrance feature points from the camera image. The vehicle parking assist apparatus determines whether the non-determined parking lot is a registered parking lot by comparing information on the non-compared entrance feature points with registered entrance feature point information. The vehicle parking assist apparatus executes a parking assist control with using the currently-acquired parking lot information and the registered parking lot information when the vehicle parking assist apparatus determines that the non-determined parking lot is the registered parking lot.