The present invention relates to a face recognition method and a face recognition device, the method including: a step for detecting one or more faces in an image frame; a step for updating a face object in a face list by using the one or more pieces of detected face information; and a step for recognizing an identity corresponding to the face object by using a plurality of feature vectors of the face object in the updated face list.

An disclosure includes: moving image acquisition unit configured to acquire moving image data obtained through moving image capturing of at least a mouth part of an utterer; a lip detection unit configured to detect a lip part from the moving image data and detect motion of the lip part; a moving image processing unit configured to generate a moving image enhanced to increase the motion of the lip part detected by the lip detection unit; and a display control unit configured to control a display panel to display the moving image generated by the moving image processing unit.

In general, one innovative aspect of the subject matter described in this specification may be embodied in methods that may include validating user data pages extracted from a digital identification in circumstances where a user device that includes the digital identification is either unavailable or presently lacks network connectivity. For instance, an authorized device may be used to extract user data pages from the digital identification by either exchanging communications with the user device using a proximity-based data exchange protocol, or by using a physical identification card to identify the digital identification on a user record. The user data pages may then be validated by comparing checksums associated with user data pages against the checksums within the user record, and decrypting the user data pages using a decryption key that is variably designated by a security status assigned to the digital identification.

A method and system for voice commands recognition. The system comprises a video camera and a microphone producing an audio/video recording of a user issuing vocal commands and at least one processor connected to the video camera and the microphone. The at least one processor has an associated memory having stored therein processor executable code causing the processor to perform the steps of: obtain the audio/video recording from the video camera and the microphone; extract video features from the audio/video recording and store the result in a first matrix; extract audio features from the audio/video recording and store the result in a second matrix; apply a speech-to-text engine to the audio portion of the audio/video recording and store the resulting syllables in a text file; and identify via a neural network the vocal commands of the user based on the first matrix, the second matrix and the text file.

An image capturing apparatus performs automatic image capturing of a subject by using an image capturing unit, controls a plurality of images acquired by the automatic image capturing to be recorded in a recording unit, selects deletion candidate images from among the plurality of images recorded in the recording unit, based on a predetermined deletion condition, automatically deletes the deletion candidate images, and performs control so that information about images other than the deletion candidate images, among the plurality of images recorded in the recording unit and including the deletion candidate images before being automatically deleted, is transmitted to an external apparatus via a communication unit before the deletion candidate images are deleted so that the information is displayed on the external apparatus.

Submitting a data space to a provider can risk exposing sensitive information in the data space. To protect the sensitive information, the data space can be analyzed to identify features that are relevant to sensitive information and features that are relevant to a goal task. Features that are relevant to the sensitive information but are not relevant to the goal task can be pruned from the data space, and the pruned data space can be transmitted to the provider.

Disclosed in some examples are devices, methods, systems, and machine-readable mediums for enhanced meeting room solutions to provide increased inclusiveness for both remote and in-room participants for network-based communication sessions, such as hybrid network-based communication sessions. Content of a first type is placed in a location exclusive of a discontinuity in a display device and content of a second type is placed in a location inclusive of the discontinuity of the display device.

The disclosure provides a method for generating a three-dimensional virtual image. The method includes: obtaining a face image to be processed and a three-dimensional reference model; obtaining a three-dimensional face model, face attribute information and face image information by inputting the face image to be processed into a trained neural network; obtaining a three-dimensional image model by performing a deformation process on the three-dimensional reference model based on the three-dimensional face model; and obtaining a target virtual image by adjusting the three-dimensional image model based on the face attribute information and the face image information.

A method and system for content display. The method includes: capturing, by an imaging device, a plurality of images of an environment; generating, by a computing device, first user profiles based on appearance of users recognized in the images; detecting devices in the environment and associating the detected devices to the users to obtain associated devices that are held by the users; retrieving, by the computing device, second user profiles of the users based on identifications of the associated devices; selecting at least one content based on the first user profiles and the second user profiles; and displaying the at least one selected content.

A method of presenting product information in a vending machine may include detecting audio information from a consumer and converting the audio information to a text string. The method may include identifying a keyword in the text string, and determining products from a product database associated with the keyword. The method may include returning a list of the products that correspond to the keyword.