A work machine including a sensing device, a user interface, and a control unit is disclosed. The control unit may be configured to generate a productivity layer based on productivity data, and generate an image layer based on image data. The image data may include information relating to an image corresponding to a state of an operation associated with a worksite and a geospatial reference associated with the image. The control unit may be configured to generate a composite image of the worksite based on a map layer, the image layer, and the productivity layer, and cause the composite image to be displayed via the user interface. The composite image may position the image layer relative to the map layer based on the geospatial reference and geographical coordinates corresponding to the geospatial reference, and position the productivity layer relative to the image layer.

An image evaluation apparatus which is capable of evaluating an image that can be given positive evaluations in a networking service. Images included in post data posted on a networking service and evaluating values for the post data are obtained at predetermined time intervals. When the post data has been obtained, first parameters are generated by applying an image analysis process to the images. The first parameters and the evaluation values are stored in association with each other. Upon input of image to be evaluated, a second parameter is generated by applying the image analysis process to the image to be evaluated. A first parameter corresponding to the second parameter is extracted from the plurality of stored first parameters. Parameter evaluation values representing variations in the evaluation values associated with the extracted first parameter in notifying order are calculated. Notification of the calculated parameter evaluation values is provided.

Approaches presented herein enable arranging images in a sequence for displaying based on a locus of a moving object in the images. Specifically, a moving object in a plurality of images is selected and metadata of the plurality of images analyzed to determine a locus of the moving object. The plurality of images is arranged along the locus of the moving object in a display environment. Image parameters may be adjusted according to an image placement along the locus, such as angular tilt and size. A place along the locus may be selected and additional images searched for based on a geo-locational metadata tag. The plurality of images may be a series of video frames or a group of photographs.

Approaches presented herein enable arranging images in a sequence for displaying based on a locus of a moving object in the images. Specifically, a moving object in a plurality of images is selected and metadata of the plurality of images analyzed to determine a locus of the moving object. The plurality of images is arranged along the locus of the moving object in a display environment. Image parameters may be adjusted according to an image placement along the locus, such as angular tilt and size. A place along the locus may be selected and additional images searched for based on a geo-locational metadata tag. The plurality of images may be a series of video frames or a group of photographs.

In one implementation, a non-transitory computer-readable storage medium stores program instructions computer-executable on a computer to perform operations. The operations include obtaining first content representing a physical environment in which an electronic device is located using an image sensor of the electronic device. A physical feature corresponding to a physical object in the physical environment is detected using the first content. A feature descriptor corresponding to a physical parameter of the physical feature is determined using the first content. Second content representing a computer generated reality (CGR) environment is generated based on the feature descriptor and presented on a display of the electronic device.

In one implementation, a non-transitory computer-readable storage medium stores program instructions computer-executable on a computer to perform operations. The operations include obtaining first content representing a physical environment in which an electronic device is located using an image sensor of the electronic device. A physical feature corresponding to a physical object in the physical environment is detected using the first content. A feature descriptor corresponding to a physical parameter of the physical feature is determined using the first content. Second content representing a computer generated reality (CGR) environment is generated based on the feature descriptor and presented on a display of the electronic device.

An image capture device may include an image sensor configured to capture an image and processing apparatus. The processing apparatus may be configured to obtain data and associate a function for each of the obtained data. The processing apparatus may be configured to store each function instance as analytic data. The processing apparatus may determine an analytic trigger occurrence and determine if the analytic trigger occurrence is greater than a function instance threshold. The processing apparatus may be configured to display a notification based on the analytic data.

An electronic apparatus connected to an image capture apparatus receives an image capture instruction for requesting the image capture apparatus to perform image capture processing, in response to a user operation. If the image capture instruction is received, the electronic apparatus performs control to display a first image recorded by the image capture apparatus performing the image capture processing according to a capture request based on the image capture instruction from the electronic apparatus on a screen without a second image recorded by the image capture apparatus automatically performing the image capture processing according to satisfying a predetermined condition for automatic capturing. If the image capture instruction is not received, the electronic apparatus performs control to display both the first image and the second image on the screen.

There is provided a method of creating an augmented reality image, comprising: capturing by an imaging sensor of a mobile device, a two dimensional (2D) image of a three dimensional scene (3D) comprising objects and pixel neighborhoods, selecting with a graphical user interface (GUI) presented on a display of the mobile device, pixel(s) of the 2D image corresponding to a certain object, computing a 3D geo-location of the certain object corresponding to the selected pixel(s) of the 2D image, wherein the 3D geo-location includes an altitude relative to sea level, and wherein the 3D geo-location is geographically distinct and spaced apart from a location of the imaging sensor outputted by a location sensor, and creating a tag for the selected pixel(s) of the certain object of the 2D image according to the computed 3D geo-location within a virtual grid, wherein the tag maps to media-object(s) correspond with real world coordinates.

An Artificial Intelligence system that may reside inside a mobile software application that uses the latest face recognition algorithms to organize photos on the phone in the picture gallery based on faces. It then analyzes photos in the phone contacts and matches the photos in the phone contacts with the photos in the picture gallery. When a match is detected, the photos are tagged with the phone number/contact from the phone contacts. This way photos on the phone are tagged with the phone number of the person in the photo. If there are multiple people in the picture, each person's face is tagged with their respective phone number. If there is no photo associated with a contact, then the user has the ability to tag the photo manually. Clicking on the tag option, pulls up the phone contact list and the user can only assign tags to photos from their contacts. The goal is to make sure every photo of every person in the photo gallery is tagged with a phone number, to enable artificial intelligence instead of humans to identify users in photos and to automatically share photos with the users identified, and the ability to enable smart search for users to find photos in their gallery based on the phone number of each person in their contracts list that the artificial intelligence system has tagged based on matching their photos in the gallery with their photos in their contact list.