Abstract: An authentication method and apparatus using a transformation model are disclosed. The authentication method includes generating, at a first apparatus, a first enrolled feature based on a first feature extractor, obtaining a second enrolled feature to which the first enrolled feature is transformed, determining an input feature by extracting a feature from input data with a second feature extractor different from the first feature extractor, and performing an authentication based on the second enrolled feature and the input feature.

Abstract: A video stream processing method and apparatus are provided. The method includes obtaining an image set of a target person from a multi-channel video stream, the multi-channel video stream being obtained for a same scene by a plurality of cameras, and an image in the image set includes a front face image of the target person; determining a virtual viewpoint in a target-person view mode based on the image in the image set; and projecting, based on a depth map of a target image and a pose of a real viewpoint corresponding to the target image, the target image onto an imaging plane corresponding to the virtual viewpoint to obtain a video stream in the target-person view mode, the target image intersecting with a vision field of the target person in the multi-channel video stream.

Abstract: Mobility traffic drop solutions for EVPN-based networking systems that reduce delays related to a device reassociating from one access point to a different access point. For example, a method may include learning information related to a path of a mobile device configured to travel in a physical space along the path; identifying a plurality of access points having coverage areas that provide service to locations along the path and a plurality of networking tunnel endpoints servicing the plurality of access points; assigning the plurality of networking tunnel endpoints to a mobility zone associated with the mobile device; and transmitting data from a source to at least two of the networking tunnel endpoints of the mobility zone.

Abstract: A method and a system for generating an augmented 3D digital model of an intraoral anatomical structure a subject. The method comprises: obtaining an unfolded surface of a 3D digital model of the intraoral anatomical structure, the unfolded surface comprising a 2D grid including a plurality of 2D cells; generating a texture reference map by: assigning, to each one of the plurality of 2D cells, a respective value of at least one textural parameter; using the texture reference map for applying the at least one textural parameter onto the 3D digital model to generate the augmented 3D digital model; and causing display of the augmented 3D digital model of the intraoral anatomical structure.

Abstract: Described are a mobile apparatus for observing a road surface and a method for controlling the same, and the mobile apparatus for observing a road surface may include: a collector acquiring road surface sensing information including image information and road surface state information corresponding to a road surface; a determiner determining whether there is a paint on the road surface based on the image information; and a corrector generating final road surface state information by selectively performing correction of the road surface state information based on a result of determining whether there is the paint on the road surface.

Abstract: Systems and methods for generating targeted media content capture an image from an image capture device. The system may analyze the image to recognize a visual identifier for each entity in the image, each of which may have one or more group identifiers. The system may aggregate the group identifiers to identify the number of each group in the audience area and select media content to display to the audience based on the aggregate numbers of each group identified in the audience area. The system may also derive time restrictions for groups identified in the audience area to help optimize how groups traverse through one or more areas.

Abstract: The disclosure relates improving correctional officer safety. A system can include a first camera facing a region of a correctional facility including monitored objects, the first camera configured to generate first pixel data including first pixels corresponding to the objects, a second camera in the correctional facility and facing away from the region, the second camera configured to generate second pixel data including second pixels corresponding to a person that approaches the region, and a server configured to receive the first and second pixel data through a network connection, transmit the received data to a recognition service through the network, and receive an alert from the alert service that indicates a monitoring rule associated with an object of the objects is violated, an identification associated with the person, a last known location of the person or the object, and an indication of the monitoring rule violated.

Abstract: A control circuit accesses a memory having stored therein total detected computed tomography image signal information in a projection domain for an object, a first model representing object scatter, a second model representing background scatter, and a third model representing detector crosstalk. Prior to a reconstruction step, the control circuit processes the total detected computed tomography image signal information in the projection domain for the object as a function of each of the first model, the second model, and the third model to thereby compensate for object scatter, background scatter, and detector crosstalk by providing scatter and crosstalk-corrected computed tomography image signal information in the projection domain for the object. The control circuit can then carry out a reconstruction step using the scatter and crosstalk-corrected computed tomography image signal information in the projection domain for the object.

Abstract: A vehicle position information acquisition device includes: a position information detector that detects position information of a vehicle; a map data storage that stores a feature type of a feature on a map and a position data group in association with each other; an imaging unit that images a region ahead of the vehicle; a feature detector that detects a surrounding feature; a reference position data group extractor that extracts a reference position data group; a reference position data group storage; a comparative position data group extractor that extracts a comparative position data group; a comparative position data group storage; an error processor that associates reference position data with comparative position data having a shortest distance and calculates an error in a distance between the reference position data and the comparative position data that are associated with each other; and a correction unit that corrects the position information.

Abstract: A rescue support apparatus includes: a registration unit configured to register biometric information and personal information of a prospective climber to be associated with each other; a reception unit configured to receive an image and positional information of a terminal of an arbitrary finder from the terminal in a case where the arbitrary finder finds a person to be rescued during mountain climbing, the image being obtained by photographing biometric information of the person to be rescued by the terminal of the finder; an authentication control unit configured to control authentication using the registered biometric information for the biometric information contained in the image; and a rescue request unit configured to transmit rescue request information to a rescue system in a case where the authentication is succeeded, the rescue request information containing the personal information associated with the biometric information and the positional information received from the terminal.

Abstract: An image generation device derives, for a subject including a specific structure, a subject model representing the subject by deriving each feature amount of the target image having the at least one representation format and combining the feature amounts based on the target image. A latent variable derivation unit derives a latent variable obtained by dimensionally compressing a feature of the subject model according to the target information based on the target information and the subject model. A virtual image derivation unit outputs a virtual image having the representation format represented by the target information based on the target information, the subject model, and the latent variable.

Abstract: Systems and devices may receive an ambient noise signal and use that ambient noise signal to generate a distorted ambient noise signal that may be provided to a speaker that is proximate to a microphone of the audio-activated device so that the speaker may project sound corresponding to the distorted ambient noise into the microphone of the audio-activated device so that, for example, that the audio-activated device cannot decipher speech and other sounds in the ambient noise of an environment. While the distorted ambient noise is being projected into the microphone of the audio-activated device, it may be scanned and/or analyzed to determine whether an audio trigger (e.g., an audio trigger or phrase) is included therein and, if so, an undistorted ambient noise signal may be communicated to the speaker of the audio-activated device so that the audio-activated device may respond to a command included in the ambient noise.

Abstract: A target object tracking system (1) includes a processor (5) for receiving image data (S1) captured by one or more sensor (7) disposed on the vehicle (2). The processor (5) is configured to analyse the image data to identify image components (IMC(n)) and to determine a movement vector (V(n)) of each image component (IMC(n)). The movement vectors each include a magnitude and a direction. At least one of the image components (IMC(n)) is classified as a target image component relating to the target object and at least one of the remaining image components (IMC(n)) as a non-target image component. The movement vector (V(n)) of the at least one target image component is modified in dependence on the movement vector of the or each non-target image component. The target object (3) is tracked in dependence on the modified movement vector of the at least one target image component. The disclosure also relates to a method and a non-transitory computer-readable medium.

Abstract: Object tracking for augmented reality involves determining a location of an object in a current frame (10) of a video stream based on object feature representations extracted from different locations in the current frame (10) and object feature representations belonging to a model of the object. The model comprises at least one object feature representation extracted from at least one previous frame (20) of the video stream and at least one object feature representation from a feature set comprising at least one server-generated object feature representation of objects belonging to a same object class as the object.

Abstract: A method of the invention comprises obtaining training dental CT scans, identifying individual teeth and jaw bone in each of these CT scans, and training a deep neural network with training input data obtained from these CT scans and training target data. A further method of the invention comprises obtaining a patient dental CT scan, identifying individual teeth and jaw bone in this CT scan and using the trained deep learning network to determine a desired final position from input data obtained from this CT scan. The (training) input data represents all teeth and the entire alveolar process and identifies the individual teeth and the jaw bone. The determined desired final positions are used to determine a sequence of desired intermediate positions per tooth and the intermediate and final positions and attachment types are used to create three-dimensional representations of teeth and/or aligners.

Abstract: A computing device establishes communication with a financial institution communication device, and receives an instruction for a user to perform an action to authenticate the user. The action includes providing user-provided data indicative of a location. The computing device determines first location information based on the user-provided data. The computing device also determines second location information using a location sensor. The computing device authenticates the used based on determining that the first location information correlates to the second location information.

Abstract: Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem. The one or more components include a semantic segmentation model configured for assigning labels to each of multiple pixels in an image responsive to what is represented in each of the multiple pixels. The image is an image of a specimen generated by an imaging subsystem. The computer subsystem is configured for determining information for the specimen from the assigned labels and without a reference image for the specimen.

Abstract: A label-free cell classification and screening system based on hybrid transfer learning, including a data preprocessing module for acquiring 2D light scattering video data and for digital cell filtering, is made public here; the data preprocessing module includes the label-free high-content video flow cytometry, which has the optical excitation module, the sheath flow control module, and the data acquisition and processing module; the image archiving module is used to sort and set labels for cells; in the feature extraction module, the first convolutional neural network is used to obtain image data feature vectors; in the cell classification and screening module, a support vector machine model is used to obtain the cell screening results.

Abstract: A method may include obtaining, using a head detection model and for an image of a video stream, head detection information, where the head detection information identifies heads detected in the image. Method may also include obtaining buffer bounding boxes. Obtaining the buffer bounding boxes may include obtaining head buffer bounding boxes for the heads detected in the image, and combining at least two of the head buffer bounding boxes into a proximity buffer bounding box. The method may furthermore include identifying a set of templates based on the buffer bounding boxes. Method may in addition include creating, individually, head frame definitions for the buffer bounding boxes using the set of templates, generating an image frame definition that combines the head frame definitions, and processing the video stream using the image frame definition.

Abstract: A method performed by a wireless device (18) comprises receiving (250), from a master node (12A) for multi-connectivity operation, a configuration message (20) which includes a master configuration (28) and one or more conditional PSCell configurations (22). The method also comprises transmitting (260) a first message (26) in response to the configuration message (20). The first message (26) indicates acknowledgement of receipt, applying of, and/or understanding of the master configuration (28). The method also comprises, after transmitting (260) the first message (26), when the condition for applying the PSCell configuration (22) of at least one of the one or more conditional PSCell configurations (22) is fulfilled, transmitting (270), to the master node (12A), a second message (30) that includes an indication (24) indicating application by the wireless device (18) of the PSCell configuration (22) of at least one of the one or more PSCell configurations (22).