Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Examples provide transaction validation through currency verification via computer vision and machine learning performed on images of non-currency and currency items from image capture devices associated with a currency environment. The results may be delivered by augmented reality (AR). Automation of currency verification and transaction validation during a transaction concludes the transaction more efficiently than manual verification and validation, increasing the amount of transactions per unit time. Examples using AR features can verify currency tendered and change made in real-time and identify foreign and counterfeit currency for removal. Examples incorporating AR features increase efficiency for fully-sighted providers and customers, while utilizing audio or braille output accommodates the visually impaired. Examples may indicate both what types and amounts of currency must be requested or discarded.

Abstract: 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.

Abstract: Detecting a tool used on a touch screen. In accordance with a method embodiment of the present invention, a cell value is accessed for each cell of a touch sensing device. The cell value indicates a force applied to the cell. A touch area sample count is determined as a count of how many of the cells have a cell value above a noise floor. A touch area weight is determined as a sum of all cell values for the cells having a cell value above the noise floor. An object touching the touch sensing device is identified based on the touch area sample count and the touch area weight. The object's touch indication may be rejected if the object is not identified. The identity of the object may be reported to a software application.

Abstract: Detecting a tool used on a touch screen. In accordance with a method embodiment of the present invention, a cell value is accessed for each cell of a touch sensing device. The cell value indicates a force applied to the cell. A touch area sample count is determined as a count of how many of the cells have a cell value above a noise floor. A touch area weight is determined as a sum of all cell values for the cells having a cell value above the noise floor. An object touching the touch sensing device is identified based on the touch area sample count and the touch area weight. The object's touch indication may be rejected if the object is not identified. The identity of the object may be reported to a software application.

Abstract: A system and method for assigning employees that are schedule to work at a brick and mortar retail store location to coverage areas within the retail store and/or tasks associated with those coverage areas. The system and method takes into account the required coverage area times of each coverage area within the store location, the master schedule of employees available to work within a defined time period that is provided by a schedule management system, and management's preferences regarding coverage area priorities for or associated with certain employees, and then automatically assigns coverage to the scheduled employees based on all those variables. The system and method identifies individuals whose scheduled work shift overlaps with required coverage area times and who are preferred to work in the coverage area and assigns such individuals to work in the coverage area during the overlapping time period (or a portion thereof).