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

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 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: 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: 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 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 object tracking system that includes a first sensor and a second sensor that are each configured to capture frames of at least a portion of a global plane for a space. The system is configured to identify a pixel location for a marker within a frame from the first sensor and to determine an (x,y) coordinate for the marker using a first homography. The system is further configured to identify a pixel location for a different marker in a frame from the second sensor and to determine an (x,y) coordinate for the marker using a second homography. The system is further configured to determine a distance difference between the computed distance between the (x,y) coordinates and an actual distance. The system is further configured to recompute the first homography and/or the second homography in response to determining that the distance difference exceeds a difference threshold level.

Abstract: A rack for a scalable tracking system includes weight sensors disposed on shelves that hold items. The weight sensors detect the weight of the items and communicates signals indicating that weight to a circuit board positioned in the rack. The circuit board communicates these detected weights to a weight server that determines, based on these weights, whether items were removed from the shelves.

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 includes a camera subsystem, a weight subsystem, and a central server. The camera subsystem includes cameras that capture video of a space, camera clients that determine local coordinates of objects in the captured videos, and a camera server that determines the physical positions of objects in the space based on the determined local coordinates. The weight subsystem determines when items were removed from shelves. The central server determines which object in the space removed the items based on the physical positions of the objects in the space and the determination of when items were removed.

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 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 photo acoustic non-destructive measurement apparatus and method for quantitatively measuring texture of a liquid. The apparatus includes a laser generating tool, an acoustic capturing device, and a data processing unit. The laser generating tool directs a laser towards a surface of a liquid contained in a container and creates pressure waves that propagate through the air 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 processes 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. Textures of liquids are quantitatively measured with the quantitative acoustic model.

Abstract: A scalable tracking system includes a camera subsystem, a weight subsystem, and a central server. The camera subsystem includes cameras that capture video of a space, camera clients that determine local coordinates of people in the captured videos, and a camera server that determines the physical positions of people in the space based on the determined local coordinates. The weight subsystem determines when items were removed from shelves. The central server determines which person in the space removed the items based on the physical positions of the people in the space and the determination of when items were removed.

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 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 an object in a frame from the first feed. The subsystem determines a first pixel position of the object. The subsystem determines 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 system includes a sensor and a tracking subsystem. The tracking subsystem receives an image feed of top-view images generated by the sensor. The tracking subsystem detects an event associated with an item being removed from a rack. 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: 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 object tracking system includes a first sensor, a second sensor, and a tracking system. The first sensor is configured to capture a first frame of a global plane for at least a first portion of a space. The second sensor is configured to capture a second frame of at least a second portion of the space. The tracking system is configured to determine the object is within an overlap region with the second sensor based on a first pixel location. The tracking system is further configured to determine a first coordinate in the global plane for the object, to determine a second pixel location in the second frame for the object based on the first coordinate, and to store the second pixel location with an object identifier a tracking list associated with the second sensor.

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.