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: Automated techniques provide for recalibrating cameras configured for monitoring an area of real space. 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. Transformation information between the selected images and the set of calibration images is obtained based on one or more features extracted from the selected images using a trained neural network classifier corresponding to points located at relatively immobile structures. The features extracted from the selected images match features in the set of calibration images. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: The technology disclosed relates to a method for tracking inventory items including dividing an area of real space into a plurality of cells and identifying inventory items and their locations in the area of real space using sequences of images produced by at least two sensors. The identifying of inventory items further includes comparing a score for the particular inventory item having a location matching a particular cell and based on one or more counts of inventory events, and a second threshold, and accepting or rejecting the particular inventory item as the predicted inventory item in dependence on whether the score is above the second threshold. In response to the identification of the inventory items, the method also includes determining, for a particular inventory item matched with a particular cell, whether a count of the particular inventory item is below a third threshold for re-stocking the particular inventory item.

Abstract: A method for identifying and tracking an inventory item is provided. The method includes using two or more sensors to produce two or more outputs associated with an inventory item, including at least one of a possible identifier for the inventory item and a possible event type indicating whether the inventory item has been taken from a shelf or placed onto a shelf. The method further includes generating confidence levels for the inventory item, wherein each respective confidence level is based on a subset of one or more outputs, and identifying, based on the confidence levels, a prediction for the inventory item including at least one of a predicted identifier for the inventory item and a predicted event type for the inventory item. The method further includes modifying a planogram of a shopping store based on the prediction for the inventory item.

Abstract: Automated techniques provide for recalibrating cameras in a real space in which puts and takes of items are tracked. 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 match one or more features from the selected images with features extracted from the set of calibration images using a trained neural network classifier. The features correspond to points located at displays or structures that remain substantially immobile. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: A method for tracking inventory items is provided. The method includes using sensors to produce respective sequences of images of corresponding fields of view, the field of view of each sensor overlapping with the field of view of at least one other sensor. The method includes dividing the area of real space into cells having volume and coordinates in a real space, and identifying inventory items and their locations in three dimensions using the sequences of images produced by at least two sensors having overlapping fields of view. The method includes, in response to the identification of the inventory items: (i) matching locations in three dimensions of identified inventory items with cells in the plurality of cells, and (ii) determining, for a particular inventory item matched with a particular cell, whether a count of the particular inventory item is below a threshold for re-stocking the particular inventory item.

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 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 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 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 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: Automated techniques provide for recalibrating cameras in a real space in which puts and takes of items are tracked. 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 match one or more features from the selected images with features extracted from the set of calibration images using a trained neural network classifier. The features correspond to points located at displays or structures that remain substantially immobile. Camera calibrations can be updated when transform information between features matched meets or exceeds a threshold.

Abstract: A method for tracking inventory items is provided. The method includes using sensors to produce respective sequences of images of corresponding fields of view, the field of view of each sensor overlapping with the field of view of at least one other sensor. The method includes dividing the area of real space into cells having volume and coordinates in a real space, and identifying inventory items and their locations in three dimensions using the sequences of images produced by at least two sensors having overlapping fields of view. The method includes, in response to the identification of the inventory items: (i) matching locations in three dimensions of identified inventory items with cells in the plurality of cells, and (ii) determining, for a particular inventory item matched with a particular cell, whether a count of the particular inventory item is below a threshold for re-stocking the particular inventory item.

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: 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 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 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.