A travel amount estimation apparatus includes a vehicle travel amount calculation unit, a sensor travel amount calculation unit, an error cause determination unit, and a vehicle travel amount correction unit. The vehicle travel amount calculation unit acquires vehicle information and calculates a vehicle travel amount based on the vehicle information. The sensor travel amount calculation unit acquires sensor information from an external sensor and calculates a sensor travel amount based on the sensor information. The error cause determination unit determines an error cause of the vehicle travel amount. The vehicle travel amount correction unit corrects the vehicle travel amount by using the sensor travel amount in accordance with the error cause and estimates a travel amount of the vehicle on which it is mounted.

A parking assist apparatus of a vehicle includes an image recognition ECU and a vehicle control ECU. The image recognition ECU extracts characteristic points contained in an image of a surrounding region of the vehicle captured during a travel. The vehicle control ECU can register, as parking lot information, the position of a parking lot and a piece of information regarding characteristic points contained in an image of a scene of the entrance of the parking lot. The vehicle control ECU can automatically park the vehicle in the registered parking lot. The image recognition ECU extracts the characteristic points contained in the image of the surrounding region when the distance between the vehicle and the entrance of the registered parking lot is equal to or shorter than a threshold distance, and does not extract the characteristic points when the distance is longer than the threshold distance.

A control device for vehicle is provided, and includes a communicator configured to receive first image information from a camera device and a processor coupled to the communicator and configured to: extract label information in the first image information; perform edge detection on the label information and extract a total number of edges; normalize the total number of edges to form a first label clarity; and when the first label clarity is greater than or equal to a preset threshold, control the vehicle to move to a parking position according to the first image information. A control method for vehicle is also provided. The present disclosure can effectively reduce the number of starts and stops of the vehicle and shorten the parking time of the vehicle.

Provided is a technology that allows, inter alia, two different patrol-vehicles to be used to enforce parking regulations. Unique systems and methods, inter alia, allow a patrol vehicle or the like to collect parking data pertaining to parked vehicles, and to wirelessly transmit such parking data to a server. A later patrol vehicle or the like can wirelessly receive parking data related to parking events related to its parking enforcement situation and determine whether parking violations, such as overtime or permit sharing violations, are occurring using a combination of parking data generated locally and extraneous parking data collected by the previous patrol vehicle.

Provided is a technology that allows, inter alia, two different patrol-vehicles to be used to enforce parking regulations. Unique systems and methods, inter alia, allow a patrol vehicle or the like to collect parking data pertaining to parked vehicles, and to wirelessly transmit such parking data to a server. A later patrol vehicle or the like can wirelessly receive parking data related to parking events related to its parking enforcement situation and determine whether parking violations, such as overtime or permit sharing violations, are occurring using a combination of parking data generated locally and extraneous parking data collected by the previous patrol vehicle.

A control device for an automated valet parking lot includes: a travel route determining unit configured to determine a travel route to a parking space; a travel route transmission unit configured to transmit the travel route to a vehicle; a position acquiring unit configured to acquire, from the vehicle, a position of the vehicle that is estimated by the vehicle; and a positional accuracy calculation unit configured to calculate a positional estimation accuracy, which is an accuracy of the position of the vehicle acquired by the position acquiring unit, prior to performing automated driving of the vehicle in accordance with the travel route.

A method of tracking a mobile device comprising at least one camera in a real environment comprises the steps of receiving image information associated with at least one image captured by the at least one camera, generating a first geometrical model of at least part of the real environment based on environmental data or mobile system state data acquired in an acquisition process by at least one sensor of a mobile system, which is different from the mobile device, and performing a tracking process based on the image information associated with the at least one image and at least partially according to the first geometrical model, wherein the tracking process determines at least one parameter of a pose of the mobile device relative to the real environment. The invention is also related to a method of generating a geometrical model of at least part of a real environment using image information from at least one camera of a mobile device

A system includes an imaging device configured to capture image data of a monitored area and a computing device having at least one processor. The computing device processor is configured to receive first image data from the imaging device and second image data from a satellite imagery system, where the second image data relates to the monitored area. The processor is also configured to determine a first set of points of interest in the first image data and a second set of points of interest in the second image data, wherein members of each set of points of interest are represented by a respective vector. The processor is further configured to generate a homography matrix based on the two vectors and determine, using the homography matrix, latitude and longitude coordinates of at least one object represented in the first image data but not the second image data.

The present disclosure provides various approaches for smart area monitoring suitable for parking garages or other areas. These approaches may include ROI-based occupancy detection to determine whether particular parking spots are occupied by leveraging image data from image sensors, such as cameras. These approaches may also include multi-sensor object tracking using multiple sensors that are distributed across an area that leverage both image data and spatial information regarding the area, to provide precise object tracking across the sensors. Further approaches relate to various architectures and configurations for smart area monitoring systems, as well as visualization and processing techniques. For example, as opposed to presenting video of an area captured by cameras, 3D renderings may be generated and played from metadata extracted from sensors around the area.

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.