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 depth camera assembly (DCA) has a light source assembly, a mask, a camera assembly, and a controller. The light source assembly includes at least one light source. The mask is configured to generate an interference pattern that is projected into a target area. The mask has two openings configured to pass through light emitted by the at least one light source, and the light passed through the two openings forms an interference pattern across the target area. The interference pattern has a phase based on a position of the light source. The camera assembly is configured to capture images of a portion of the target area that includes the interference pattern. The controller is configured to determine depth information for the portion of the target area based on the captured images.

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 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.

One disclosed example provides a method for displaying a hologram via a head-mounted display (HMD) device. The method comprises, via a camera system on the HMD device, acquiring image data capturing a surrounding environment by detecting illumination light output by a projector located on a case for the HMD device. A distance is determined from the HMD device to an object in the surrounding environment based upon the image data. The method further comprises displaying via the HMD device a hologram, the hologram comprising a left-eye image and a right-eye image each having a perspective based upon the distance determined.

A system for visualizing a three-dimensional target area of an object with a measuring device which determines a distance of a surgical instrument in a target area with respect to a predetermined structure in the target area, a display unit for representing the views, and a control unit. The control unit controls the display unit such that the display unit is in a first display mode when a determined distance is greater than a predetermined first limit value, and switches from the first display mode into a second display mode when the determined distance changes from being greater than a predetermined second limit value, which is smaller than or equal to the predetermined first limit value, to smaller than the predetermined second limit value.

A system for visualizing a three-dimensional target area of an object with a measuring device which determines a distance of a surgical instrument in a target area with respect to a predetermined structure in the target area, a display unit for representing the views, and a control unit. The control unit controls the display unit such that the display unit is in a first display mode when a determined distance is greater than a predetermined first limit value, and switches from the first display mode into a second display mode when the determined distance changes from being greater than a predetermined second limit value, which is smaller than or equal to the predetermined first limit value, to smaller than the predetermined second limit value.