Abstract: An object tracking system includes a sensor and a tracking system. The sensor is configured to capture a first frame of a global plane for at least a portion of a space. The tracking system is configured to receive a first coordinate in the global plane where a first marker is located in the space and to receive a second coordinate in the global plane where a second marker is located in the space. The tracking system is further configured to identify the first marker and the second marker within the first frame, to determine a first pixel location in the first frame for the first marker, to determine a second pixel location in the first frame for the second marker, and to generate a homography based on the first coordinate, the second coordinate, the first pixel location, and the second pixel location.

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: 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 sensors and a tracking subsystem. The subsystem tracks first and second objects in a space. Following a collision event between the first and second object, a top-view image of the first object is received from a first sensor. Based on the top-view image, a first descriptor is determined for the first object. The first descriptor is associated with an observable characteristic of the first object. If criteria are not satisfied for distinguishing the first object from the second object based on the first descriptor, a third descriptor is determined for the first object. The third descriptor is generated by an artificial neural network configured to identify objects in top-view images. The tracking subsystem uses the third descriptor to assign an identifier to the first object.

Abstract: A system includes sensors and a tracking subsystem. The subsystem tracks a first object and one or more other objects in a space. After determining that re-identification of the first object is needed, candidate identifiers are determined for the first object The candidate identifiers include a subset of the identifiers of all tracked objects in the space. The subset includes possible identifiers of the first object based on a history of movements of the first object and interactions of the first object with the other objects in the space. Based on a top-view image, a first descriptor is determined for the first object. The first descriptor is associated with a characteristic of the first object. Based on results of comparing the first descriptor to a set of predetermined descriptors, an updated identifier is determined for the first object.

Abstract: A system includes a first sensor and a sensor client. During an initial time interval, the sensor client receives top-view images generated by the first sensor and detects contours in the images. The sensor client determines, based on the contours, regions of the top-view images generated by the first sensor to exclude during object tracking. During a subsequent time interval, the sensor client receives a second top-view 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 apparatus includes an interface, display, memory, and processor. The interface receives a video feed including first and second camera feeds, each feed corresponding to a camera located in a store. The processor stores a video segment in memory, assigned to a person and capturing a portion of a shopping session. The video segment includes first and second camera feed segments, each segment corresponding to a recording of the corresponding camera feed from a starting to an ending timestamp. Playback of the first and second camera feed segments is synchronized, and a slider bar controls a playback progress of the camera feed segments. The processor displays the camera feed segments and copies of the slider bar on the display. The processor receives an instruction from at least one of the copies of the slider bar to adjust the playback progress of the camera feed segments and adjusts the playback progress.

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: 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. The first frame includes a region-of-interest (ROI) marker within the space. The system is further configured to identify pixel locations within the first frame corresponding with the ROI marker and to define a zone for subsequent frames from the sensor corresponding with the pixel locations. The system is further configured to receive a second frame from the sensor, to detect an object within the zone, and to identify the object. The system is further configured to determine a person is within the second frame and to modify a digital cart that is associated with the person based on the identified object.

Abstract: A system includes sensors and a tracking subsystem. The subsystem receives a first image feed from a first sensor and a second image feed from a second sensor. The field-of view of the second sensor at least partially overlaps with that of the first sensor. The subsystem detects, in a frame from the first feed, a first contour associated with an object. The subsystem determines, based on pixel coordinates of the first contour, a first pixel position of the object. The subsystem detects, in a frame from the second feed, a second contour associated with the same object. The subsystem determines, based on pixel coordinates of the second contour, a second pixel position of the object. Based on the first pixel position and the second pixel position, a global position for the object is determined in a space.

Abstract: A tracking system includes a set of cameras, a kiosk, and a tracking server. The kiosk receives a payment amount from a person. The tracking server extracts features of the person from an image feed received from the set of cameras. The tracking server generates a session identifier that is associated with the payment amount and a unique code. The unique code represents at least one of the payment amount and features of the person. The tracking server sends a message to the kiosk to provide a ticket corresponding to the payment amount and the unique code to the person. The tracking server receives a digital cart associated with the person comprising items and a total cash value of the items. The tracking server concludes a transaction by deducting the total cash value from the payment amount.

Abstract: An object tracking system that includes a plurality of sensors and a tracking system. A first sensor from the plurality of sensors is configured to capture a first frame of a global plane for at least a portion of the space. The tracking system is configured to determine a pixel location in the first frame for an object located in the space, and to apply a homography to the pixel location to determine a coordinate in the global plane. The homography is configured to translate between pixel locations in the first frame and coordinates in the global plane.

Abstract: A system includes a sensor, a weight sensor, and a tracking subsystem. The tracking subsystem receives an image feed of top-view images generated by the sensor and weight measurements from the weight sensor. The tracking subsystem detects an event associated with an item being removed from a rack in which the weight sensor is installed. The tracking subsystem determines that a first person or a second person may be associated with the event. In response to determining that the first or second person may be associated with the event, buffer frames are stored of top-view images generated by the sensor during a time period associated with the event. The tracking subsystem then determines, using at least one of the stored buffer frames and a first action-detection algorithm, whether an action associated with the event was performed by the first person or the second person.

Abstract: An object tracking system that includes a sensor, a weight sensor, and a tracking system. The sensor 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 identify a marker on an item within a predefined zone in the frame, and to identify the item associated with the identified marker. The tracking system is further configured to determine a pixel location for a person, to determine the person is within the predefined zone associated with the, and to add the identified item to a digital cart associated with the person.

Abstract: An apparatus includes a display, interface, and processor. The interface receives video from a camera located in a physical store and directed at a first physical rack. The camera captures video of the rack during a shopping session. The processor displays a first virtual rack that emulates the first physical rack and includes first and second virtual shelves. The virtual shelves include virtual items, which include graphical representations of physical items located on the physical rack. The processor displays the rack video, which depicts an event including the person interacting with the first physical rack. The processor also displays a virtual shopping cart. The processor receives information associated with the event, identifying the first virtual item. The rack video depicts that the person selected the first physical item while interacting with the first physical rack. The processor then stores the first virtual item in the virtual shopping cart.

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: A sensor mounting system that includes a sensor, a mounting ring, a faceplate support, and a faceplate. The mounting ring includes a first opening and a first plurality of threads that are disposed on an interior surface of the first opening. The faceplate support is disposed within the first opening of the mounting ring. The faceplate support includes a second plurality of threads that are configured to engage the first plurality of threads of the mounting ring and a second opening. The faceplate is disposed within the second opening of the faceplate support. The faceplate is coupled to the sensor and is configured to rotate within the second opening of the faceplate support.

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 further includes a position sensor that is configured to output (x,y) coordinates corresponding with the physical location of the sensor within the space. The system is configured to receive an (x,y) coordinate within the space for the sensor from the position sensor. The (x,y) coordinate corresponds with a new physical location of the sensor within the space. The system is further configured to determine translation coefficients for the sensor based on a difference between the (x,y) coordinate and a previous (x,y) coordinate for the sensor. The system is further configured to update a homography associated with the sensor by applying the translation coefficients to the homography and to store the updated homography.

Abstract: A system includes a sensor, a weight sensor, and a tracking subsystem. The tracking subsystem receives an image feed of top-view images generated by the sensor and weight measurements from the weight sensor. The tracking subsystem detects an event associated with an item being removed from a rack in which the weight sensor is installed. The tracking subsystem determines that a first person and a second person may be associated with the event. In response, the tracking subsystem dilates contours associated with the first and second person from a first depth to a second depth until the contours enter a zone adjacent to the rack. A number of iterations is determined for each contour to enter the zone adjacent to the rack. If the first person's contour enters the zone in fewer iterations, the item is assigned to the first person.

Abstract: A measurement apparatus and method for in-situ quantitative texture measurement of a food snack. The apparatus includes an acoustic capturing device and a data processing unit. The physical interaction in the mouth with saliva, when a human being eats/drinks a food snack, sends pressure waves that propagate through the ear bone and produce an acoustic signal. The acoustic capturing device records and forwards the signal to a data processing unit. The data processing unit further comprises a digital signal processing module that smoothens, transforms and filters the received acoustic signal. A statistical processing module further filters the acoustic signal from the data processing unit and generates a quantitative acoustic model for texture attributes such as hardness and fracturability. The quantitative model is correlated with a qualitative texture measurement from a descriptive expert panel. Another method includes a food snack fingerprinting using an in-situ quantitative food property measurement.