The present teaching relates to method, system, and programming for responding to an image related query. Information related to each of a plurality of images is received, wherein the information represents concepts co-existing in the image. Visual semantics for each of the plurality of images are created based on the information related thereto. Representations of scenes of the plurality of images are obtained via machine learning, based on the visual semantics of the plurality of images, wherein the representations capture concepts associated with the scenes.

One or more embodiments of the disclosure include a character management system that determines and utilizes contextual meaning with regard to standardized image characters. In particular, the character management system determines contextual meaning with regard to standardized characters based on the manner in which the standardized characters are utilized in a repository of electronic documents. Moreover, the character management system can utilize the contextual meaning to search, recommend, analyze, and translate with regard to the use of standardized image characters.

Disclosed is a secure telephone call management system for authenticating users of a telephone system in an institutional facility. Authentication of the users is accomplished by using a personal identification number, preferably in conjunction with speaker independent voice recognition and speaker dependent voice identification. When a user first enters the system, the user speaks his or her name which is used as a sample voice print. During each subsequent use of the system, the user is required to speak his or her name. Voice identification software is used to verify that the provided speech matches the sample voice print. The secure system includes accounting software to limit access based on funds in a user's account or other related limitations. Management software implements widespread or local changes to the system and can modify or set any number of user account parameters.

Techniques for generating a digital wardrobe are presented herein. A transceiver can be configured to receive a request having a garment identifier and a user identifier. Additionally, an access module can be configured to access a first garment model, access a body model of the user corresponding to the user identifier, and access a second garment model corresponding to the user identifier. Furthermore, a processor can be configured by a garment simulation module to position the body model inside the first garment model and the second garment model, and calculate simulated forces based on the positioning. Moreover, a rendering module can be configured to generate an image of the garment models draped on the body model based on the calculated simulated forces. Subsequently, a display module can be configured to cause presentation of the generated image on a display of a device.

A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

A system for identifying and timing an athlete during a timed sporting event. The athlete is timed using image recognition technology in which one or more images of the athlete taken during the sporting event by a camera (106a, 106b, or 106c) is time-stamped to generate a finish time for the athlete. The athlete is identified by comparing one of the images taken during the sporting event with a profile image of the athlete.

A media communication system and computer-implemented method for transmitting responsive display auxiliary content to an end-user communication device to be rendered on a display device. The communication system is arranged to analyze media content constituents, including image content; create a throne portion based on the image content; create a headline, including headline rendering instructions, based on the image content; create a background, including background rendering instructions, based on the image content; create image rendering instructions based on the headline and background; and generate responsive display auxiliary content, including the headline rendering instructions, background rendering instructions and image rendering instructions. The system can include a transmitter arranged to send the responsive display auxiliary content to an end-user communication device, which can be arranged to render the responsive display auxiliary content on a display device with the headline rendered vertically on the throne portion and partially outside a viewport of a responsive display auxiliary container and the image content stacked atop of and offset with respect to the background.

In a database, product image data is accumulated. A search portion acquires product image data having the image characteristics information that is the same as or similar to the image characteristics information that indicates the characteristics of the image of input image data from the database for the input image data. A search server outputs information on another product that is different from the product corresponding to the product image data together with the product image data acquired by the search portion.

A facility for constructing a display module in connection with a web page is described. The facility obtains content associated with the web page and uses the obtained content to generate a query used to select an image. The facility then generates the display module that incorporates the selected image.

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.