Abstract: Apparatus and methods are described for generating geometries for stripe-shaped objects. An image is identified that includes a roadway having one or more stripe-shaped objects. The stripe-shaped objects may include lane lines for road edges or lanes of the roadway. The stripe-shaped objects may include a barrier. At least one targeted region within the image is determined. The at least one targeted region is shaped to intersect the one or more stripe-shaped objects and includes a plurality of pixels. An image analysis is performed on the image to determine when the at least one target region includes a pixel in common with the one or more stripe-shaped objects. A geometry is constructed using the pixel in common. The geometry may be used to update a map or subsequently perform localization.

Abstract: Apparatus and methods are described for generating geometries for stripe-shaped objects. An image is identified that includes a roadway having one or more stripe-shaped objects. The stripe-shaped objects may include lane lines for road edges or lanes of the roadway. The stripe-shaped objects may include a barrier. At least one targeted region within the image is determined. The at least one targeted region is shaped to intersect the one or more stripe-shaped objects and includes a plurality of pixels. An image analysis is performed on the image to determine when the at least one target region includes a pixel in common with the one or more stripe-shaped objects. A geometry is constructed using the pixel in common. The geometry may be used to update a map or subsequently perform localization.

Abstract: A system for analysis of remotely sensed image data of parking facilities, storage lots, or road regions, for determining patterns over time and determine time-based information such as facility capacities or vehicle movement.

Abstract: A system for analysis of remotely sensed image data of parking facilities, storage lots, or road regions, for determining patterns over time and determine time-based information such as facility capacities or vehicle movement.

Abstract: Processing and analyzing at least one remotely-sensed image to automatically detect and identify parking lots within a region of the remotely-sensed image. This may include: (1) receiving a remotely-sensed image having zero or more parking lots; (2) identifying a set of pixels related to parking lot features within the remotely-sensed image; (3) identifying at least one parking row within the remotely-sensed image; and (3) identifying a parking lot based on the identified parking rows. Identifying at least one parking lot may further include using first, second, third, and fourth level modules, such as a concrete/asphalt detection module, a road marking detection module, a vehicle detection module, and a Hough aggregation for parking row detection module.

Abstract: A system for automated car counting comprises a satellite-based image collection subsystem; a data storage subsystem; and an analysis software module stored and operating on a computer coupled to the data storage subsystem. The satellite-based image collection subsystem collects images corresponding to a plurality of areas of interest and stores them in the data storage subsystem. The analysis module: (a) retrieves images corresponding to an area of interest from the data storage subsystem; (b) identifies a parking space in an image; (c) determines if there is a car located in the parking space; (d) determines a location, size, and angular direction of a car in a parking space; (e) determines an amount of overlap of a car with an adjacent parking space; (f) iterates steps (b)-(e) until no unprocessed parking spaces remain; and (g) iterates steps (a)-(f) until no unprocessed images corresponding to areas of interest remain.

Abstract: A system for oil storage tank monitoring, comprising an extraction module and an analysis module, wherein an extraction module is utilized to determine information from an oil storage tank image and an analysis module is utilized to perform operations on extracted information, such as for determining measurements or values of oil storage tanks.

Abstract: A system for automated car counting comprises a satellite-based image collection subsystem; a data storage subsystem; and an analysis software module stored and operating on a computer coupled to the data storage subsystem. The satellite-based image collection subsystem collects images corresponding to a plurality of areas of interest and stores them in the data storage subsystem. The analysis module: (a) retrieves images corresponding to an area of interest from the data storage subsystem; (b) identifies a parking space in an image; (c) determines if there is a car located in the parking space; (d) determines a location, size, and angular direction of a car in a parking space; (e) determines an amount of overlap of a car with an adjacent parking space; (f) iterates steps (b)-(e) until no unprocessed parking spaces remain; and (g) iterates steps (a)-(f) until no unprocessed images corresponding to areas of interest remain.

Abstract: Processing and analyzing at least one remotely-sensed image to automatically detect and identify parking lots within a region of the remotely-sensed image. This may include: (1) receiving a remotely-sensed image having zero or more parking lots; (2) identifying a set of pixels related to parking lot features within the remotely-sensed image; (3) identifying at least one parking row within the remotely-sensed image; and (3) identifying a parking lot based on the identified parking rows. Identifying at least one parking lot may further include using first, second, third, and fourth level modules, such as a concrete/asphalt detection module, a road marking detection module, a vehicle detection module, and a Hough aggregation for parking row detection module.

Abstract: A system for automated car counting comprises a satellite-based image collection subsystem; a data storage subsystem; and an analysis software module stored and operating on a computer coupled to the data storage subsystem. The satellite-based image collection subsystem collects images corresponding to a plurality of areas of interest and stores them in the data storage subsystem. The analysis module: (a) retrieves images corresponding to an area of interest from the data storage subsystem; (b) identifies a parking space in an image; (c) determines if there is a car located in the parking space; (d) determines a location, size, and angular direction of a car in a parking space; (e) determines an amount of overlap of a car with an adjacent parking space; (f) iterates steps (b)-(e) until no unprocessed parking spaces remain; and (g) iterates steps (a)-(f) until no unprocessed images corresponding to areas of interest remain.

Abstract: A system for oil storage tank monitoring, comprising an extraction module and an analysis module, wherein an extraction module is utilized to determine information from an oil storage tank image and an analysis module is utilized to perform operations on extracted information, such as for determining measurements or values of oil storage tanks.

Abstract: A system described herein includes a detector component that automatically determines location of a license plate in a digital image. The system further includes a blurrer component that automatically blurs the digital image at the determined location of the license plate, wherein blurring undertaken by the blurrer component is based at least in part upon confidence scores assigned to pixels in the digital image that correspond to the determined location of the license plate.