Abstract: A method for identifying an inventory item is provided. The method includes using first one or more sensors to produce first one or more outputs indicative of an inventory item, using second one or more sensors to produce second one or more outputs indicative of the inventory item, generating, based on the first one or more outputs and independent of the second one or more outputs, a first confidence level of the inventory item being a first inventory item, generating, based on the second one or more outputs and independent of the first one or more outputs, a second confidence level of the inventory item being a second inventory item, and identifying, based on the first confidence level and the second confidence level, the inventory item as one of the first inventory item or the second inventory item.

Abstract: Systems and techniques are provided for recalibrating cameras in a real space for tracking puts and takes of items by subjects. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. The first processing includes a process step to extract a plurality of feature descriptors from the images. The first processing also includes a process step to match one or more feature descriptors as extracted from the selected images with feature descriptors extracted from the set of calibration images that were used to calibrate the cameras previously. The feature descriptors correspond to points located at displays or structures that remain substantially immobile.

Abstract: A method of tracking subjects in an area. The method including receiving a plurality of sequences of images of corresponding fields of view in the area of real space, using a plurality of trained inference engines that process respective sequences of images in the plurality of sequences of images to locate features of subjects in the corresponding fields of view of the respective sequences, combining the located features from more than one of the trained inference engines which process respective sequences of images having overlapping fields of view to generate data locating subjects in three dimensions in the area of real space during identification intervals, and matching located subjects from a plurality of identification intervals to identify tracked subjects, including comparing located subjects with tracked subjects.

Abstract: A method is provided for monitoring status of subjects in an area for a system including a first data set identifying locations of subjects, a second data set identifying events in the area, and a third data set identifying whether accounts matched to the subjects exist. The method includes executing a graphical user interface including a map of at least part of the area including avatars identifying locations of subjects located on the map, and representing respective statuses assigned to the subjects located on the map, the statuses being assigned to the subjects based on one or more of the first, second and third data sets, wherein the assigning of the respective statuses to the subjects are assigned by utilizing at least one of the first, second and third data sets to determine that at least one subject of the subjects is a high risk of loss subject.

Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: Systems and techniques are provided for tracking inventory items in an area of real space. A plurality of cameras, or other sensors, produce respective sequences of images in corresponding fields of view in the real space. The field of view of each camera overlaps with the field of view of at least one other camera. The system is coupled to the plurality of cameras and uses the sequences of images produced by at least two cameras in the plurality of cameras to identify inventory events. The inventory event includes an item identifier, a location and a timestamp. A plurality of cells having coordinates in the area of real space are stored as a data set in the memory. The processing system calculates scores at a scoring time, for inventory items having locations matching particular cells using respective counts of inventory events.

Abstract: Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

Abstract: Systems and techniques are provided for tracking inventory events in an area of real space. A plurality of sensors produce respective sequences of frames in corresponding fields of view in the real space. The field of view of each sensor overlaps with the field of view of at least one other sensor. The processing system uses the sequences of frames produced by sensors in the plurality of sensors to identify gestures by detected subjects in the area of real space and produce inventory events. The inventory events include a subject identifier identifying a detected subject, a gesture type of the identified gesture by the detected subject, an item identifier identifying an inventory item linked to the gesture by the detected subject, a location of the gesture represented by positions in three dimensions of the area of real space and a timestamp.

Abstract: Systems and techniques are provided for tracking subjects in an area of real space. The system receives a plurality of sequences of images of corresponding fields of view in the real space. The system uses the sequences of images to locate subjects in the area of real space during identification intervals. The system compares a current set of located subjects from a current identification interval with previous sets of located subjects from a plurality of previous identification intervals to track locations of tracked subjects in the area.

Abstract: Systems and techniques are provided for monitoring status of subjects in an area of real space. The system includes a display having access to memory storing a first data set identifying locations of subjects in the area of real space over time, a second data set identifying item put and take events in the area of real space and a third data set identifying accounts matched to the subjects in the first data set. The system includes a graphical user interface logic that renders a map on the display of at least part of the area of real space including avatars having locations on the map corresponding to locations in the area of real space according to the first data set, and identifying respective statuses assigned to the subjects based on one or more of the first data set, the second data set and the third data set.

Abstract: Systems and techniques are provided for recalibrating cameras in a real space for tracking puts and takes of items by subjects. The method includes first processing one or more selected images selected from a plurality of sequences of images received from a plurality of cameras calibrated using a set of calibration images that were used to calibrate the cameras previously. The first processing includes a process step to extract a plurality of feature descriptors from the images. The first processing also includes a process step to match one or more feature descriptors as extracted from the selected images with feature descriptors extracted from the set of calibration images that were used to calibrate the cameras previously. The feature descriptors correspond to points located at displays or structures that remain substantially immobile.

Abstract: Systems and techniques are provided for determining an improved camera coverage plan including a number, a placement, and a pose of cameras that are arranged to track puts and takes of items by subjects in a three-dimensional real space. The method includes receiving an initial camera coverage plan including a three-dimensional map of a real space, an initial number and initial pose of a plurality of cameras and a camera model including characteristics of the cameras. The method can iteratively apply a machine learning process to an objective function of number and poses of cameras, and subject to a set of constraints, obtain an improved camera coverage plan. The improved camera coverage plan is provided to an installer to arrange cameras to track puts and takes of items by subjects in the three-dimensional real space.

Abstract: Systems and techniques are provided for linking subjects in an area of real space with user accounts. The user accounts are linked with client applications executable on mobile computing devices. A plurality of cameras are disposed above the area. The cameras in the plurality of cameras produce respective sequences of images in corresponding fields of view in the real space. A processing system is coupled to the plurality of cameras. The processing system includes logic to determine locations of subjects represented in the images. The processing system further includes logic to match the identified subjects with user accounts by identifying locations of the mobile computing devices executing client applications in the area of real space and matching locations of the mobile computing devices with locations of the subjects.

Abstract: Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

Abstract: Systems and techniques are provided for linking subjects in an area of real space with user accounts. The user accounts are linked with client applications executable on mobile computing devices. A plurality of cameras are disposed above the area. The cameras in the plurality of cameras produce respective sequences of images in corresponding fields of view in the real space. A processing system is coupled to the plurality of cameras. The processing system includes logic to determine locations of subjects represented in the images. The processing system further includes logic to match the identified subjects with user accounts by identifying locations of the mobile computing devices executing client applications in the area of real space and matching locations of the mobile computing devices with locations of the subjects.

Abstract: Systems and techniques are provided for tracking puts and takes of inventory items by sources and sinks in an area of real space. The system can include sensors producing a plurality of sequences of images of corresponding fields of view in the real space. The system can include image recognition logic, receiving sequences of images from the plurality of sequences. The image recognition logic processes the images in sequences to identify locations of sources and sinks over time represented in the images. The system can include logic to process the identified locations of sources and sinks over time to detect an exchange of an inventory item between sources and sinks.

Abstract: Systems and techniques are provided for tracking puts and takes of inventory items by subjects in an area of real space. A plurality of cameras with overlapping fields of view produce respective sequences of images of corresponding fields of view in the real space. In one embodiment, the system includes first image processors, including subject image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The first image processors process images to identify subjects represented in the images in the corresponding sequences of images. The system includes second image processors, including background image recognition engines, receiving corresponding sequences of images from the plurality of cameras. The second image processors mask the identified subjects to generate masked images. Following this, the second image processors process the masked images to identify and classify background changes represented in the images in the corresponding sequences of images.

Abstract: Systems and techniques are provided for tracking locations of inventory items in an area of real space including inventory display structures. A plurality of cameras are disposed above the inventory display structures. The cameras in the plurality of cameras produce respective sequences of images in corresponding fields of view in the real space. A memory stores a map of the area of real space identifying inventory locations on inventory display structures. The system is coupled to a plurality of cameras and uses the sequences of images produced by at least two cameras in the plurality of cameras to find a location of an inventory event in three dimensions in the area of real space. The system matches the location of the inventory event with an inventory location.

Abstract: A mechanized store uses a first camera to detect an identity of an item and a second camera to detect an identity of the item. The identity of the item detected using the first image is compared to the identity of the item detected using the second image. The user and/or to a store employee can be alerted to a discrepancy.

Abstract: A mechanized store identifies a user in an area. A sensor is used to identify an item removed from a display by the user. Cameras are configured to detect items removed from the display. An identity of the user is matched to items removed from the display by the user to obtain a result. The result is saved to a record of the user.