An embodiment provides a method, including: receiving, from a device, a user identification; storing, in a storage device, first data produced by first free-form user input specifying one or more regions of an image and second data comprising second free-form user input describing the one or more regions of the image; each first data having corresponding second data stored in association therewith; selecting, using a processor, a data set comprising at least a portion of the first data and the second data based at least in part on the user identification; and providing the selected data set for display. Other embodiments are described and claimed.

A computer implemented method for detecting an object in a crowded scene utilizing an image capturing device. The method includes receiving an image of a predetermined area. From the image, the existence of selected portions as representing an entity of a selected class is determined. Each selected portion is assigned an initial confidence value that the selected portion is an entity representative of a selected class. Each selected portion is evaluated with each other to determine a context confidence value. The context confidence value and initial confidence value are utilized to determine which of the one or more selected portions are entities of a selected class.

Provided is a system capable of further reducing risk such as a contact between a moving body such as a vehicle and a traffic participant present around the moving body. According to an environment recognition system (1) of the present invention, a database (10) stores each of a plurality of reference symbol strings describing the state of an environmental element constituting each of a plurality of scenes assumed to be around the moving body. A first arithmetic processing element (11) detects a scene around the moving body and generates a symbol string describing the state of the environmental element constituting the detected scene. A second arithmetic processing element (12) evaluates similarity between the symbol string and each of the plurality of reference symbol strings stored in the database (10).

Methods for prioritizing a set of images identified as responsive to an image search query from a user based on features of the images identified as relevant to a geographic region of the user are provided. In one aspect, the method includes submitting a plurality of images to a computer-operated convolutional neural network that is configured to analyze image pixel data for each of the plurality of images to identify features, in each of the plurality of images, influencing a download probability of the corresponding image in a plurality of geographic regions. The method also includes receiving, from the neural network and for each of the plurality of images, a download probability of each image for each of the plurality of geographic regions. Systems and machine-readable media are also provided.

Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

There is provided an information processing apparatus for automatically generating information representing a context surrounding a user, the information processing apparatus including: a recognition processing unit configured to perform, on the basis of user environment information including at feast any of location information representing a location where a user is present, image information relating to an environment surrounding a user, and audio information relating to the environment, an analysis process of at least any of the location information, the image information, and the audio information included in the user environment information, at a predetermined time interval, and to recognize a context surrounding the user, using the acquired result of analysis relating to the user environment; and a context candidate information generating unit configured to generate context candidate information representing a candidate of the context surrounding the user, the context candidate information including, at least, information representing the context surrounding the user and information representing the user's emotion in the context using the result of context recognition performed by the recognition processing unit.

The present disclosure relates to a method and apparatus for searching an image, and to a computer-readable recording medium for executing the method. The apparatus for searching an image of the present disclosure obtains features of an input image; and obtains words that correspond to the features respectively and an adjacent word that is adjacent to the words corresponding to the features. When a word is assigned to a first word cell of a plurality of word cells that are included in a visual feature space, an adjacent word is assigned to at least one second word cell that is adjacent to the first word cell, where the plurality of word cells is assigned to different words, and at least one word being within a predetermined distance from a word is designated as the adjacent word. The apparatus is further configured to search for an image that is identical or similar to the input image based on information associated with a first group of images corresponding to the word and information associated with a second group of images corresponding to the adjacent word, the information on the first and second groups of images being stored in a database.

Aspects of the present disclosure provide a gesture recognition method and an apparatus for capturing gesture. The apparatus categorizes the raw data of a gesture into gesture elements, and utilizes the contextual dependency between the gesture elements to perform gesture recognition with a high degree of accuracy and small data size. A gesture may be formed by a sequence of one or more gesture elements.

Method to customize an application associated with a television experience based on the recognition of users located in front of a display and in the field of view of a camera, comprising the following steps: —an initialization step during which each user is enrolled in a database of a computer system and is defined by a profile referenced by a profile ID and comprising the user name, biometric data and additional personal data, —a finding step during which a wide image, acquired by said camera is scanned to isolate at least one user's faces, to define a marking area surrounding it, to memorize the position of said marking areas, —a matching step to extract the biometric data from said marking area, to match them with the biometric data of the profiles stored in the database, and to assign the detected profile ID with the marking area. While subsequent identification is requested by the application, the following steps are executed —acquiring a wide image with the camera, —extracting the areas of said image according to the marking areas, —extracting for a particular marking area the biometric data of a face, —starting the comparison of the extracted biometric data with the biometric data of the profile ID related to this marking area, and in absence of match, continuing with the other biometric data of the database until one profile is found, —transmitting the found profile ID to the application.

Systems and methods for censoring text-based data are provided. In some embodiments a censoring system may include at least one processor and at least one non-transitory memory storing application programming interface instructions. The censoring system may be configured to perform operations comprising storing a target pattern type and a computer-based model for identifying a target data pattern corresponding to a target pattern type within text based data. The censoring system may also be configured to receive text-based data by a server, and to retrieve the stored target pattern type to be censored in the text-based data. The censoring system may be configured to identify within the received text-based data, a target data pattern corresponding to the retrieved target pattern type. The censoring system may be configured to censor target characters within the identified target data pattern, and transmit the censored text-based data to a receiving party.