A machine may be configured to execute a machine-learning process for identifying and understanding fine properties of various items of various types by using images and associated corresponding annotations, such as titles, captions, tags, keywords, or other textual information applied to these images. By use of a machine-learning process, the machine may perform property identification accurately and without human intervention. These item properties may be used as annotations for other images that have similar features. Accordingly, the machine may answer user-submitted questions, such as “What do rustic items look like?,” and items or images depicting items that are deemed to be rustic can be readily identified, classified, ranked, or any suitable combination thereof.

A material search system, includes a material search server, including a processor, a non-transitory memory, an input/output, a material library for storing material representations, a material search manager, a machine learner, an image translation model, and a semantic model; and a material search device. Each material representation includes a visual image, a color palette, a structural image, and a semantic structure. Also disclosed is a method of searching a material library and generating output material representations; including performing reverse image, reverse structure, and semantic searches; training image and structural translation models; and training a semantic model.

A number of embodiments can include a photographic chamber. In some embodiments, a photographic chamber can comprise one or more frames arranged in a convex shape and having an opening; one or more walls coupled to the one or more frames and having one or more recesses configured to receive photography equipment; and a door matching the one or more walls, wherein the door can be located in the opening when positioned in a closed configuration. Other embodiments are disclosed herein.

A method for making texture symbols of a land use classification map is disclosed in the disclosure, including: capture of texture materials; extraction of main colors; color clustering; extraction of a texture skeleton; tile effect removal; and establishment of a texture library. The disclosure has the following advantages: definitions and classes of texture symbols are provided, and a procedure of making texture symbols is made clear; used natural texture symbols and symbolic texture symbols have clear semantic meanings, facilitating information transfer of the map; the quality and layering of the map are improved; the texture symbols can be directly used for production, to provide a fundamental support for survey and mapping of land use, and also to provide a solution for large-scale result mapping of natural resource survey. The expression of thematic maps of current land use classification is improved.

A computer-implemented technique is described herein for performing an image-based search that allows a user to create a custom query image that expresses the user's search intent. The technique generates the query image based on one or more input images and/or one or more information items that describe at least one desired characteristic of the query image. The technique then submits the query image to a search engine, and, in response, receives a set of candidate images that match the query image. In one implementation, the technique constructs the query image using a decoder neural network that operates on a mixed latent variable vector. In one approach, the technique uses a generative adversarial network (GAN) to produce the decoder neural network.

There is provided with an information processing method for outputting album data corresponding to an album in which images are laid out. The method comprises obtaining information corresponding to each of a plurality of images, selecting a plurality of analysis target images from the plurality of images, executing a predetermined analysis on the plurality of selected analysis target images, and outputting album data. In case where images satisfying the predetermined criterion is less than the predetermined number, the predetermined analysis is executed on a predetermined image not selected by the predetermined selection condition. In the outputting, album data corresponding to an album in which the predetermined number or greater of images including the predetermined image are laid out is output.

A system and method for creating a 3D virtual model of an event, such as a wedding or sporting event, and for sharing the event with one or more virtual attendees. Virtual attendees connect to the experience platform to view the 3d virtual model of the event on virtual reality glasses, i.e. a head mounted display, from a virtual gallery, preferably from a user selected location and orientation or a common location and orientation for all virtual attendees. In one form the virtual attendees can see and interact with other virtual attendees in the virtual gallery.

A system uses a trained classifier to identify or predict the item attributes of an item depicted in an image, and compares these attributes to those specified in a corresponding item description. The system may, for example, be used to verify the accuracy of listings submitted by users to an electronic catalog. For example, if an item description submitted by a user does not specify all of the item attributes identified from the item image(s) submitted by the user, the system may generate a suggested edit to the item description.

A circular dome for photographing vehicles includes curved frames that support a skin. Contoured walls offset from the curved frames to define a recess adapted to receive cameras and lights for photographing vehicles around a perimeter of the dome. A door matching the contour of the curved frames completes the dome and is size to receive a vehicle, to collectively implement subtractive lighting along the perimeter of the dome. A system and method are provided for automatically photographing vehicles in an enclosable circular domed structure where an automated process captures a series of vehicle images, and uploads the captured images to a web template for display and recordation.

Embodiments of the present disclosure provide systems, methods, and computer storage media for mitigating delays typically experienced when training codebooks during the encoding process. Instead of training a codebook based on a single digital asset, multiple digital assets determined to have asset characteristics in common can be grouped together to form a group of digital assets, from which a single codebook can be trained. The group of digital assets together form a codebook training set, such that each digital asset therein can be analyzed, in parallel, to expeditiously train a single codebook. A codebook trained in this manner can be employed to encode other digital assets sharing the asset characteristics as those in the codebook training set.