Textile matching using color and pattern recognition and methods of use are provided herein. An example method includes analyzing an image (305) of a first article of clothing to obtain color information and pattern information (205-230), comparing the color information and pattern information of the first article of clothing to color information and pattern information for a plurality of other articles of clothing (using Bayesian probability analysis to determine matched pairs, and providing a user with wardrobe suggestions using the matched pairs (705-740).

Textile matching using color and pattern recognition and methods of use are provided herein. An example method includes analyzing an image (305) of a first article of clothing to obtain color information and pattern information (205-230), comparing the color information and pattern information of the first article of clothing to color information and pattern information for a plurality of other articles of clothing (using Bayesian probability analysis to determine matched pairs, and providing a user with wardrobe suggestions using the matched pairs (705-740).

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using location data to identify and provide services in association with items appearing in captured images. One of the methods includes receiving, from a device, an image and location data representing the device's physical location, determining, based on the location data, that a particular set of one or more locations are within a threshold distance of the device's physical location, accessing, for each of the one or more locations in the particular set, item information that indicates one or more items that are associated with the location, determining, based on the accessed item information, that the image likely shows a particular item that is associated with one or more locations in the particular set, and providing, to the device, instructions for presentation of information about (i) the particular item and (ii) one or more locations in the particular set that are associated with the particular item.

An operation method for generating content including a user identification (ID), and an apparatus therefor are provided. The operation method of the device includes obtaining mapping information by making one or more pieces of biometric information for each of a plurality of users correspond to a user ID of each of the plurality of users, obtaining first content including a first user by photographing the first user, obtaining first biometric information of the first user, determining a first user ID corresponding to the first biometric information of the first user, based on the mapping information, and associating the first content with the first user ID, and storing the association of the first content with the first user ID.

Provided are a device and a method for acquiring music information about music played in an electronic device, acquiring a storyline of the music based on the music information, and acquiring and displaying one or more images based on the storyline.

A method, apparatus, system for image processing is provided that creates an object note for a picture. The method, apparatus or system includes: automatically obtaining picture description information from a picture source, wherein the picture description information at least partly have been formed automatically; obtaining annotation information from at least two object sources, wherein the two object sources are different from the picture sources, automatically fusing the said annotation information from the two object sources to form fused annotation information, and attaching said fused annotation information to the picture to create the object note for the picture.

The present invention provides a model generation method, word weighting method, device, apparatus, and computer storage medium. In one aspect, the embodiments of the present invention obtain other images that are identical to a specified image, and use the specified image and said other images as sample images; and then obtain a text clustering based on the texts of the sample images; and then obtain text features based on the text clustering and obtaining visual features based on the sample images; and carry out machine learning based on the text features and the visual features to generate a first regression model and a first sorting model for word weighting on words in the text of an image. The embodiments of the present invention therefore can improve the accuracy of the word weighting result in an image text, thus improving the accuracy of an image search result.

The present invention provides a model generation method, word weighting method, device, apparatus, and computer storage medium. In one aspect, the embodiments of the present invention obtain other images that are identical to a specified image, and use the specified image and said other images as sample images; and then obtain a text clustering based on the texts of the sample images; and then obtain text features based on the text clustering and obtaining visual features based on the sample images; and carry out machine learning based on the text features and the visual features to generate a first regression model and a first sorting model for word weighting on words in the text of an image. The embodiments of the present invention therefore can improve the accuracy of the word weighting result in an image text, thus improving the accuracy of an image search result.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for contextually disambiguating queries are disclosed. In an aspect, a method includes receiving an image being presented on a display of a computing device and a transcription of an utterance spoken by a user of the computing device, identifying a particular sub-image that is included in the image, and based on performing image recognition on the particular sub-image, determining one or more first labels that indicate a context of the particular sub-image. The method also includes, based on performing text recognition on a portion of the image other than the particular sub-image, determining one or more second labels that indicate the context of the particular sub-image, based on the transcription, the first labels, and the second labels, generating a search query, and providing, for output, the search query.

In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.