Abstract: A system includes sensors and a tracking subsystem. The subsystem receives frames of top-view images generated by the sensors. The subsystem tracks a first and second object, based on received frames. The subsystem detects that the first object is within a threshold distance of the second object. In response, the subsystem determines a probability that the first object switched identifiers with the second object and updates candidate lists accordingly for the first and second objects. The updated first candidate list includes a probability that the first object is associated with a first identifier and a probability that the first object is associated with a second identifier.

Abstract: A system includes a first sensor and a sensor client. During an initial time interval, the sensor client receives images generated by the first sensor and detects contours in the images. The sensor client determines, based on the contours, regions of the images generated by the first sensor to exclude during object tracking. During a subsequent time interval, the sensor client receives a second image generated by the first sensor and detects a contour in the image. The sensor client determines pixel coordinates of the second contour and determines whether at least a threshold percentage of the second pixel coordinates overlap with the region to exclude during object tracking. If at least the threshold percentage of the second pixel coordinates overlap with the region to exclude, a position for tracking the second contour is not determined.

Abstract: An object tracking system includes a sensor, a weight sensor, and a tracking system. The sensor is configured to capture a frame of at least a portion of a rack within a global plane for a space. The tracking system is configured to detect a weight decrease on the weight sensor. The tracking system is further configured to receive the frame of the rack, to determine a pixel location for a person, to determine the person is within a predefined zone associated with the rack. The tracking system is further configured to identify the item associated with the weight sensor and to add the identified item to a digital cart associated with the person.

Abstract: A system includes a sensor and a tracking subsystem. The tracking subsystem receives an image feed of top-view images generated by the sensor and detects an event associated with a portion of a person entering a zone adjacent to a rack. The tracking subsystem determines that a first and second person may be associated with the event. The subsystem tracks the item and calculates a velocity of the item as it is moved through the space. The subsystem identifies, based on the calculated velocity, a frame in which the velocity of the item is less than a threshold velocity. The subsystem determines whether the first or second person is nearer the item in the identified frame. If the first person is nearer, the item is assigned to the first person.

Abstract: An object tracking system includes a sensor and a tracking system. The sensor is configured to capture a frame of at least a portion of a physical space within a global plane for a space. The tracking system is configured to receive the frame, to detect an object within a zone of the frame, and to determine a pixel location for the object. The tracking system is further configured to identify a zone of the physical structure based on the pixel location, to identify an item based on the identified zone.

Abstract: A system that includes a fuel dispenser terminal and a remote controller. The fuel dispenser terminal is configured to generate a service request for a fuel purchase that includes card information, encrypt the service request, and send the encrypted service request to the remote controller. The fuel dispenser terminal is further configured to receive a personalized offer in response to sending the encrypted service request and display the personalized offer. The remote controller is configured to decrypt the service request to identify the card information associated with a customer and determine an identity of the customer based on the card information. The remote controller is further configured to generate a personalized offer for the customer based on their identity and send the personalized offer to the fuel dispenser terminal. The remote controller is further configured to re-encrypt the service request and send the re-encrypted service request to a service processor.

Abstract: An access control system that includes an access control device configured to receive transaction information that identifies a member identifier for a member and a purchased item. The access control device is configured to compare the purchased item to items in an item list and to determine whether the purchased item matches any items in the item list. The access control device is configured to store an authorization for the member identifier to access an augmented reality experience in response to a match.

Abstract: A device configured to receive a resource reservation request that identifies a user and a resource. The device is further configured to generate a resource allocation that includes an association between the user, location information for the resource, a resource identifier for the resource, and a token value. The device is further configured to associate the resource allocation with a time interval indicating a deadline for using the resource allocation. The device is further configured to receive a reservation verification request from a network device. The device is further configured to determine the location information for the network device is within a predetermined distance from the location information for the resource, to determine the resource identifier matches the resource identifier for the resource, and to determine a current time is within the time interval. The device is further configured to generate resource allocation instructions authorizing access to the resource.

Abstract: A tracking system includes a camera subsystem that includes cameras that capture vide of a space. Each camera is coupled with a camera client that determines local coordinates of people in the captured video. The camera clients generate frames that include color frames and depth frames labeled with an identifier number of the camera and their corresponding timestamps. The camera clients generate tracks that include metadata describing historical people detections, tracking identifications, timestamps, and the identifier number of the camera. The camera clients send the frames and tracks to cluster servers that maintain the frames and tracks such that they are retrievable using their corresponding labels. A camera server queries the cluster servers to receive the frames and tracks using their corresponding labels. The camera server determines the physical positions of people in the space based on the determined local coordinates.

Abstract: A device that includes a housing configured to couple to an interior of a vehicle. The device further includes a card reader and a user interface. The card reader is configured to receive payment card information for a payment card. The user interface is configured to receive a user input identifying a product, to determine a current location of the device, to determine a vending location where the product is available based on the current location of the device, and to modify a route to a final destination to include the vending location. The user interface is further configured to send an authorization request requests a purchase of the product, to receive an approval message, to generate an authorization token that authorizes a purchase to retrieve the products from the vending location, and output the authorization token.

Abstract: A scalable tracking system processes video of a space to track the positions of people within a space. The tracking system determines local coordinates for the people within frames of the video and then assigns these coordinates to time windows based on when the frames were received. The tracking system then combines or clusters certain local coordinates that have been assigned to the same time window to determine a combined coordinate for a person during that time window.

Abstract: A scalable tracking system processes video of a space to track the positions of objects within a space. The tracking system determines local coordinates for the objects within frames of the video and then assigns these coordinates to time windows based on when the frames were received. The tracking system then combines or clusters certain local coordinates that have been assigned to the same time window to determine a combined coordinate for an object during that time window.

Abstract: A system includes a sensor and a client. The client receives a set of frames of top-view depth images generated by the sensor. The client identifies a frame of the received frames in which a first contour associated with a first object is merged with a second contour associated with a second object. The client determines, at a first depth in the identified frame, a merged-contour region which is associated with the merged contours. The client detects a third contour at a second depth that is less than the first depth and determines a first region associated with the third contour. The client detects a fourth contour at the second depth and determines a second region associated with the fourth contour. If criteria are satisfied, the client associates the first region with a position of the first object and associates the second region with a position of the second object.

Abstract: An object tracking system that includes a sensor that is configured to capture frames of at least a portion of a global plane for a space. The system is configured to receive a first frame from the sensor, to identify a pixel location within the first frame, and to determine an estimated sensor location for the sensor by applying a homography to the pixel location. The homography includes coefficients that translate between pixel locations in a frame from the sensor and (x,y) coordinates in the global plane. The system is further configured to determine an actual sensor location for the sensor and to determine a location difference between the estimated sensor location and the actual sensor location. The system is further configured to compare the location difference to a difference threshold level and to recompute the homography in response to determining that the location difference exceeds the difference threshold level.

Abstract: An object tracking system that includes a sensor that is configured to capture frames of at least a portion of a global plane for a space. The system is configured to receive a first frame from the sensor and to identify a first pixel location and a second pixel location within the first frame. The system is further configured to determine (x,y) coordinates by applying a homography to the first pixel location and the second pixel location. The system is further configured to determine an estimated distance between the (x,y) coordinates, to determine an actual distance, and to determine a distance difference between the estimated distance and the actual distance. The system is further configured to compare the distance difference to a difference threshold level and to recompute the homography in response to determining that the distance difference exceeds the difference threshold level.

Abstract: A system includes a server and merchant device. The server receives product information for a product scanned by a mobile device. The server stores the product information for the product in a digital cart. The server receives a transaction request from the mobile device, determines that the product is associated with a validation requirement, and transmits a validation request to the merchant device. The server receives, from the merchant device, an indication that the validation requirement is satisfied, processes a transaction, and transmits, to the merchant device, an indication that the transaction is complete. The merchant device receives the validation request, determines that the validation requirement is satisfied, and transmits the indication that the validation requirement is satisfied to the server. The merchant device receives, from the server, the indication that the transaction is complete and displays the indication that the transaction on the display.

Abstract: A camera array for a scalable tracking system includes cameras that are communicatively coupled to camera clients. The cameras are arranged in a grid such that no camera is directly adjacent in the same row or column of the grid to another camera that is communicatively coupled to the same camera client. Cameras that are arranged along a diagonal of the grid are communicatively coupled to the same camera client.

Abstract: An item position tracking system includes weight sensors each associated with a weight board. Each weight sensor transmits sensor data indicative of a weight of an item to its corresponding weight board. Each weight board is configured to assign a particular address number to its corresponding weight sensor. The weight boards transmit the sensor data and the address numbers to a circuit board that transmits the sensor data and the address numbers to a weight server. The weight server determines from which weight sensor data is originated based on the address numbers, and whether items were removed from the weight sensors.

Abstract: A tracking system includes a camera subsystem that includes cameras that capture vide of a space. Each camera is coupled with a camera client that determines local coordinates of people in the captured video. The camera clients generate frames that include color frames and depth frames labeled with an identifier number of the camera and their corresponding timestamps. The camera clients generate tracks that include metadata describing historical people detections, tracking identifications, timestamps, and the identifier number of the camera. The camera clients send the frames and tracks to cluster servers that maintain the frames and tracks such that they are retrievable using their corresponding labels. A camera server queries the cluster servers to receive the frames and tracks using their corresponding labels. The camera server determines the physical positions of people in the space based on the determined local coordinates.

Abstract: An apparatus includes a memory and processor. The memory stores a machine learning algorithm configured to decide whether to use a virtual shopping cart to verify all or a portion of a transaction performed with an algorithmic shopping cart. The processor receives feedback for a decision made by the algorithm, indicating whether the algorithmic and virtual carts match. The processor assigns a reward to the feedback. A first positive reward is assigned when the virtual shopping cart is not used for verification, and the feedback indicates that the carts match. A second positive reward is assigned when the virtual cart is used for verification, and the feedback indicates that the carts do not match. A first negative reward is assigned when the virtual shopping cart is not used for verification, and the feedback indicates that the carts do not match. A second negative reward is assigned when the virtual cart is used for verification, and the feedback indicates that the carts match.