Abstract: A batteryless device is provided. The batteryless device includes a logic processor, a power storage cell, a sensor, a persistent memory, a wireless logic and an antenna configured to harvest power in response to exposure to radio frequency (RF) energy. The harvested power is transferred to the power storage cell such that when the power storage cell has a threshold amount of power the logic processor is activated to start or resume execution of code associated with a task of sampling the sensor, processing sensor data from the sensor into an encrypted message, and transmitting the encrypted message. The batteryless device transmits one or more of said encrypted messages using said wireless logic to a local device proximate to a location of the batteryless device. The one or more encrypted messages providing information related a state of a package to which the batteryless device is attached.

Abstract: A method for providing real-time recommendations to user in a shopping environment involves sampling a shopping environment using video cameras to generate video features related to a shopper in connection to an item, the sampling input to a machine learning model to create labels related to a state of a scenario, the scenario including the shopper handling the item. Supplemental information is provided to the shopper in connection with the item. The makeup of the supplemental information may be sourced from online service or device associated with the shopper. The supplemental information may be delivered to the shopper, or to a shopper-aware display in the store, or elsewhere. A processing entity associated with the store detects a scenario to identify the shopper as having finished shopping, and causing a charge of the item to a cashierless shopping cart associated with the shopper.

Abstract: A method for providing real-time recommendations to user in a shopping environment involves sampling a shopping environment using video cameras to generate video features related to a shopper in connection to an item, the sampling input to a machine learning model to create labels related to a state of a scenario, the scenario including the shopper handling the item. Supplemental information is provided to the shopper in connection with the item. The makeup of the supplemental information may be sourced from online service or device associated with the shopper. The supplemental information may be delivered to the shopper, or to a shopper-aware display in the store, or elsewhere. A processing entity associated with the store detects a scenario to identify the shopper as having finished shopping, and causing a charge of the item to a cashierless shopping cart associated with the shopper.

Abstract: Method of identifying actions of a shopper to account for taken items by the shopper in a cashierless checkout includes sampling a shopping environment using one or more video cameras to generate video features related a shopper in connection to an item and sampling using one or more supplemental sensors to generate supplemental sensor feature data, receiving output of the sampled video and supplemental sensor features as feature inputs to a deep learning model used for making inferences related to the state of a scenario involving shopper action of taking the item into their possession or held and other actions including moving outside a zone initially associated with the item.

Abstract: A system and controller are provided. In one example, the system includes a controller for playing a video game. The controller includes input buttons for controlling interaction during play of the video game. The controller includes an inertial sensor for detecting translational or rotational movement of the controller and a vibrational device. A voice input device is associated with the controller. A wireless communication circuit of the controller is provided for communicating data between the controller and a local computing device. The local computing device is connectable to a network. The data includes control responsive to presses of said input buttons or control received from said voice input device.

Abstract: Methods and system for processing shopping activity for a retail store are provided. One example method includes associating a plurality of sensor devices to monitor a shelf of the retail store. The shelf having one or more physical items and each of the physical items is capable of being associated with a state change in response to user interaction. The method includes detecting user interaction by a user in the retail store with a physical item of the one or more physical items. The user interaction causes the state change in a sensor device associated with the shelf, and responsive to the state change transmitting a message related to the state change over a network to an end node. The end node is configured to receive the message causing processing of an action based on the message. The one or more physical items are offered for sale in the store and data regarding the user interaction of the physical item is associated to a user account of the user.

Abstract: A cashierless tracking system uses a biometric sensor disposed at the entry of a store or the entry of a shelf or an entry to a section of a store is configured to capture biometric feature aspects of a user. Cashierless shopping is enabled without requiring a user to supply mobile phone or device to identify themselves. Instead, processing and classification of biometric features occur via a neural network to identify at least one label representing classified features of the user, the label being used to identify a profile for the user. A plurality of sensors in the store produces data to identify a take of an item by a single user or by a group of users tied to a single account. Included tracking embodiments involve overlapping cameras, skeletal tracking, microphone input, feature extraction and/or feature engineering. The take of the item is chargeable to an electronic shopping cart of the user.

Abstract: A computer-implemented methods for generating a mini-game are provided. One method includes recording gameplay of a game on a computer game system and receiving a signal to generate said mini-game, and responsive to said signal suspending play of the game. The method includes identifying a start point and an end point for the mini-game from the recorded game, and using said start point and said end point for generating executable instructions to enable play of the mini-game. The method includes saving said generated executable instructions to a distribution system. The distribution system includes at least one server to enable access to the mini-game to access said generated executable instructions. And, selection of the generated executable instructions enables interactive gameplay of the mini-game.

Abstract: A scene of a portion of a simulated environment within a field of view of a virtual camera from a virtual camera point of view (camera POV) is displayed on a display. The scene displayed is changed during a user's interaction with the simulated environment. A revised virtual camera path is generated that places more of an advertising target within the field of view of the virtual camera. The advertising target is characterized by a field of attraction of the camera POV.

Abstract: Methods and systems related to tracking activity in a store in association with a cashier-less environment are provided. One example method includes identifying actions in a store. The method includes sampling a shopping environment using one or more sensors that include at least one camera capable of providing depth sensing to produce image data of a scene that shows a shopper in the store and tracking data related to one or more limbs of the shopper in connection to an item. The method includes receiving output of the sampling as feature inputs to one or more machine learning models and deriving one or more label inferences of a behavior state of the shopper in connection with a state of the item. At least one processing entity associated with the store detects the state of the item to change from one as item handled by said shopper to one as item queued for purchase.

Abstract: Method and systems are provided for processing actions in a store. One example method includes capturing sensor output from two or more sensors in a shopping environment. One sensor includes a first camera to capture scene data where the scene includes movement of a shopper in the store performing interaction with an item in the store. Another sensor includes a second camera capturing at least part of the scene from a different perspective. The method includes processing, by a processing entity associated with the store, at least one of the camera's output to generate feature data. The feature data is processed by one or more machine learning models to produce engineered feature data. The engineered feature data includes data relating to tracking skeletal movement of shopper.

Abstract: Ancillary information associated with one or more images embedded in a digital broadcast data stream may be accessed by a digital broadcast receiving device. The device may include a receiver unit, a processor, and a memory. The processor may execute program instructions to access the ancillary information. Control data may be associated with one or more visual components of one or more video images. The control data and images may be combined into a digital broadcast data stream. The device may receive the images and control data. The images may be presented on a display device. The receiving device may use the control data to present or store a perceptible indication that ancillary information is associated with the visual components in conjunction with presenting the images. The device may use the control data to present or store the ancillary information in response to an input signal.

Abstract: A method of tracking a user in a store and tracking takes and puts in regard to items in said store. One method includes tracking a shopper in a physical store using two or more cameras that are overlapping to infer and account for shopping activity performed by the shopper. The method includes providing output of at least one of the two or more cameras to a processing entity to extract skeletal limb features of the shopper. Then, processing the skeletal limb features of the shopper to detect a take of an item from the store into possession of the shopper. The method further includes detecting, based on the tracking, that the shopper has exited the store and processing a charge to an account of shopper for the item based on the detected take.

Abstract: A device is provided that includes a logic processor, a power storage cell, a sensor, a wireless logic and a power source. The power source is configured to harvest power in response to exposure to radio frequency (RF) energy using an antenna element of the device. The harvested power is transferred to the power storage cell such that when the power storage cell has a usable amount of power the logic processor (a) samples data using the sensor, (b) processes the sample data into a message that is encrypted, and (c) transmits the message using the wireless logic to an end node that is configured to receive the message from the device. When usable amount of power is not present in the power storage cell during any one of (a)-(c), data is saved in persistent memory until additional harvested power is present in the power storage cell.

Abstract: Devices, systems, and method are provided for tracking items in a store for processing a cashier-less purchase transaction. In one example, a method includes tracking a shopper in a store using one or more sensors to process an account of shopping activity performed by the shopper. The method further includes monitoring the shopper in the store using said one or more sensors. Output of the one or more sensors is processed by a processing entity associated with the store to produce input feature data for aspects of a current scenario involving actions of the shopper and one or more items in the store. The processing entity associated with the store processes the input feature data to characterize aspects of the current scenario. The processing entity characterizes aspects of the current scenario in part by accessing a trained machine learning model that is maintained for a profile of the shopper. The input feature data is for actions of the shopper in relation to the scenario.

Abstract: Devices, systems, and method are provided for tracking items in a store for processing a cashier-less purchase transaction. In one example, the method includes detecting a portable device in the physical store. The portable device has an application that associates the portable device with an on-line account of a shopper. The method includes receiving identification data for an item taken from a location of the physical store by the shopper using one or more sensors of the physical store to target the item for purchase. The identification data is configured to identify a type of said item for adding it to an electronic shopping cart of the shopper having the on-line account for processing said cashier-less purchase transactions. The method includes instructing to process an electronic charge via a payment service for the item. And, one or more additional portable devices are usable at the physical store to facilitate one or more shoppers to make purchases of items.

Abstract: Devices, systems, and method are provided for processing requests for items to be pre-gathered from a store, the processing of the requests is executed using one or more processing entities. One method includes receiving tracking data from portable device associated with a user having an online account with the store. One or more items are identified from a shopping list of the user as associated with the online account of the store. Processing the tracking data is made to determine a current route of the portable device to the store. Sending instructions is processed to create a task for pre-gathering one or more items from the store. The sending of instructions is triggered in response to confirming that the current route of the portable device remains headed to the store. The method also includes receiving an indicator that the one or more items from the store have been gathered.

Abstract: During output of a primary media stream from a cable, satellite, television, radio or internet source, a condition, signal or indication of a commercial break is detected causing a context switch to occur and enabling other services, programming or devices to intervene during the commercial break and causing an alternative output to be produced by a process or device. When the commercial break is over, the system may optionally rejoin with the primary media stream.

Abstract: A computer-implemented methods for generating a mini-game are provided. One method includes recording gameplay of a game on a computer game system and receiving a signal to generate said mini-game, and responsive to said signal suspending play of the game. The method includes identifying a start point and an end point for the mini-game from the recorded game, and using said start point and said end point for generating executable instructions to enable play of the mini-game. The method includes saving said generated executable instructions to a distribution system. The distribution system includes at least one server to enable access to the mini-game to access said generated executable instructions. And, selection of the generated executable instructions enables interactive gameplay of the mini-game.

Abstract: A scene of a portion of a simulated environment within a field of view of a virtual camera from a virtual camera point of view (camera POV) is displayed on a display. The scene displayed is changed during a user's interaction with the simulated environment. A revised virtual camera path is generated that places more of an advertising target within the field of view of the virtual camera. The advertising target is characterized by a field of attraction of the camera POV.