In order to enable high image acquisition rate with simultaneous low energy consumption of a camera 1, a camera (1), in particular a 3D time-of-flight camera, is provided, comprising an illumination unit (2) which emits light pulses during an illumination phase (Bp), an image sensor (3) which generates images from the light pulses reflected by an object, a switching controller (4) which controls current to the illumination unit (2), the switching controller (4) being operable in a continuous and a discontinuous mode (CCM; DCM), and a control unit (5) which is designed to activate and deactivate the continuous mode (CCM) of the switching controller (4) as a function of the illumination phase (Bp) of the illumination unit (2).

In order to enable high image acquisition rate with simultaneous low energy consumption of a camera 1, a camera (1), in particular a 3D time-of-flight camera, is provided, comprising an illumination unit (2) which emits light pulses during an illumination phase (Bp), an image sensor (3) which generates images from the light pulses reflected by an object, a switching controller (4) which controls current to the illumination unit (2), the switching controller (4) being operable in a continuous and a discontinuous mode (CCM; DCM), and a control unit (5) which is designed to activate and deactivate the continuous mode (CCM) of the switching controller (4) as a function of the illumination phase (Bp) of the illumination unit (2).

A system for refining an item identification model detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system captures images of the item. The system extracts a set of features from at least one of the images. The system identifies the item based on the set of features. The system receives an indication that the item is not identified correctly. The system receives an identifier of the item. The system identifies the item based on the identifier of the item. The system feeds the identifier of the item and the images to the item identification model. The system retrains the item identification model to learn to associate the item to the images. The system updates the set of features based on the determined association between the item and the images.

A system for refining an item identification model detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system captures images of the item. The system extracts a set of features from at least one of the images. The system identifies the item based on the set of features. The system receives an indication that the item is not identified correctly. The system receives an identifier of the item. The system identifies the item based on the identifier of the item. The system feeds the identifier of the item and the images to the item identification model. The system retrains the item identification model to learn to associate the item to the images. The system updates the set of features based on the determined association between the item and the images.

A system for updating a training dataset of an item identification model determines that an item is not included in a training dataset. In response to determining that the item is not included in the training dataset, the system obtains an identifier of the item. The system detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system captures images of the item. The system extracts a set of features associated with the item from the images. The system associates the item to the identifier and the set of features. The system adds a new entry to the training dataset, where the new entry represents the item labeled with the identifier and the set of features.

A system for updating a training dataset of an item identification model determines that an item is not included in a training dataset. In response to determining that the item is not included in the training dataset, the system obtains an identifier of the item. The system detects a triggering event at a platform, where the triggering event corresponds to a user placing the item on a platform. The system captures images of the item. The system extracts a set of features associated with the item from the images. The system associates the item to the identifier and the set of features. The system adds a new entry to the training dataset, where the new entry represents the item labeled with the identifier and the set of features.

A device configured to capture a first image of an item on a platform using a camera and to determine a first number of pixels in the first image that corresponds with the item. The device is further configured to capture a first depth image of an item on the platform using a three-dimensional (3D) sensor and to determine a second number of pixels within the first depth image that corresponds with the item. The device is further configured to determine that the difference between the first number of pixels in the first image and the second number of pixels in the first depth image is less than the difference threshold value, to extract the plurality of pixels corresponding with the item in the first image from the first image to generate a second image, and to output the second image.

A cooking appliance includes a body defining a cooking cavity. A door is rotatably coupled to the body. An imager assembly is coupled to an interior surface of the door. The imager assembly includes an image sensor configured to obtain image data within a field of view, a first primary mirror positioned at a first angle proximate to the image sensor and within the field of view, and a second primary mirror positioned at a second angle proximate to the image sensor and within the field of view. A secondary mirror assembly includes multiple secondary mirrors coupled to the body within the cooking cavity. The secondary mirrors reflect image views within the cooking cavity to the first primary mirror and the second primary mirror which reflects the image views to the image sensor to be captured as the image data.

A lens apparatus includes a lens disposed closest to an object, a holder holding the lens, a cover having a first opening to expose the lens when viewed from an optical axis direction of the lens and being positioned with the holder in the optical axis direction, and an exterior member having a second opening to engage with an outer diameter of the cover. A first gap in a diameter direction orthogonal to the optical axis direction formed between the holder and the cover is larger than a second gap in the diameter direction formed between the exterior member and the cover.

An image processing apparatus determines whether an image represented by image data includes two circular areas and executes predetermined processing on the image if it is determined that the image includes two circular areas. The image processing apparatus can recognize if the image data is taken with a dual-eye lens even when an image capture apparatus that has recorded the image data has not recognized that a dual-eye lens unit has been attached and processing the image appropriately.