A method for identifying stored products in household storage devices. A set of images of a stored product of the storage device is captured, and the stored product is identified by evaluating image data of the set of images by a standard identification algorithm. The standard identification algorithm has been trained by way of a standard set of images captured with a standard configuration. Before the standard identification algorithm is used, a data characteristic of the image data is adapted to a standard data characteristic of the standard set of images by way of an adaptation algorithm that is at least partially trained based on a configuration of the household storage device. The method is particularly applicable for domestic food handling appliances such as refrigerators and cooking appliances and also extractor hoods.

A food class of a food item is recognized. A target doneness score is defined for the food item based on the food class and a desired doneness level. A recurrent model is utilized to determine a current doneness score of the food item according to sensor data captured of the food item. The current doneness score and the target doneness score are utilized to control a heating system to cook the food item.

A media sharing and communication system, including a recording mechanism that records a desired portion of media upon activation by a first individual user, a first user transmitter/receiver that transmits the portion of media and a message generated by the first individual user regarding the portion of media to a second individual user and is capable of transmitting a message to a second individual user, a confirmation mechanism that confirms that the second individual user is authorized to view the portion of media, a notification mechanism that notifies the first individual user if the second individual user is not authorized to receive the portion of media, a second user transmitter/receiver that receives the portion of media and voice message upon authorization of the second individual user, a search mechanism, and a video recording mechanism, an online betting module, and an online food ordering module.

A media sharing and communication system, including a recording mechanism that records a desired portion of media upon activation by a first individual user, a first user transmitter/receiver that transmits the portion of media and a message generated by the first individual user regarding the portion of media to a second individual user and is capable of transmitting a message to a second individual user, a confirmation mechanism that confirms that the second individual user is authorized to view the portion of media, a notification mechanism that notifies the first individual user if the second individual user is not authorized to receive the portion of media, a second user transmitter/receiver that receives the portion of media and voice message upon authorization of the second individual user, a search mechanism, and a video recording mechanism, an online betting module, and an online food ordering module.

Embodiments of the present disclosure include apparatuses, computer-implemented methods, and computer program products for automatic product verification and shelf product gap analysis. Some embodiments utilize a multi-imager imaging engine to capture at least two image data objects associated with at least a near field and a far field via corresponding near and far-field imagers. The far field image data object in some embodiments is processed to identify, and/or detect and decode, product information on a product label at a shelving location for future processing. The near-field image data object may be processed to identify a product set located within the environment surrounding the product label. The information identified from each image data object may be processed to identify whether one or more product mismatches, pricing mismatches, and/or product gaps are present at the shelving location, with improved likelihood of success for each task.

Described herein are systems and methods for determining dryness of produce using image data. A method can include receiving, by a computing system and from an imaging device, image data of a batch of produce, performing, by the computing system, object detection to identify each produce in a frame of the image data, extracting, by the computing system, temperature values in pixels of the identified produce in the frame, and determining, by the computing system, distribution characteristics of the extracted temperature values. The method can also include predicting, by the computing system, a dryness metric for the batch of produce based on applying a trained model to the determined distribution characteristics. The model can be trained using temperature distributions of other produce, the temperature distributions being annotated based on previous mappings of skewness of the temperature distributions to dryness.

Described herein are systems and methods for determining dryness of produce using image data. A method can include receiving, by a computing system and from an imaging device, image data of a batch of produce, performing, by the computing system, object detection to identify each produce in a frame of the image data, extracting, by the computing system, temperature values in pixels of the identified produce in the frame, and determining, by the computing system, distribution characteristics of the extracted temperature values. The method can also include predicting, by the computing system, a dryness metric for the batch of produce based on applying a trained model to the determined distribution characteristics. The model can be trained using temperature distributions of other produce, the temperature distributions being annotated based on previous mappings of skewness of the temperature distributions to dryness.

In some embodiments, a system for remotely purchasing perishable products includes a plurality of image capture devices configured to capture images of perishable products, a product image database, a product attribute database, and a control circuit configured to execute computer program modules. An image processing module receives and processes images from the image capture devices to form a composite image. A product identification module identifies and segments the products in the composite image. A product selection module causes an application executed on a remote electronic device operated by a customer to display the composite image and receives from the application a selection of a product to purchase, at least one product attribute, and a quantity of individual product units to purchase. The product selection module identifies the individual product units having the selected product attribute(s) and outputs signaling to cause retrieval of the individual product units.

In some embodiments, a system for remotely purchasing perishable products includes a plurality of image capture devices configured to capture images of perishable products, a product image database, a product attribute database, and a control circuit configured to execute computer program modules. An image processing module receives and processes images from the image capture devices to form a composite image. A product identification module identifies and segments the products in the composite image. A product selection module causes an application executed on a remote electronic device operated by a customer to display the composite image and receives from the application a selection of a product to purchase, at least one product attribute, and a quantity of individual product units to purchase. The product selection module identifies the individual product units having the selected product attribute(s) and outputs signaling to cause retrieval of the individual product units.

A method of reality augmentation, including: (a) determining the identity of a container, for example chocolate spread, with a top opening; (b) acquiring an image of the container from a top thereof; (c) estimating a geometry of the filling of said container based on said identity and said image; and (d) overlaying an augmentation, for example, a coupon or a toy, on an image, based on said estimation.