Abstract: The embodiments herein provide a system and method for personalized cartoon image generation. The method (100) comprises launching a keyboard interface (101), capturing a digital picture (102), face segmentation using neural network (103), normalization of segmented face (104), face cartoonification (105), which generates bobble head, facial landmark extraction (106), facial expression feature transfer (109) and customization of the generated plurality of cartoon images (110). Hence, the embodiments herein helps in creation of personalized plurality of cartoon images to make the user part of the conversations and the graphics or content shared look similar to the user input face and more aesthetically pleasing instead of using any reference stickers to convey the messages.

Abstract: The present technique relates to an apparatus and a method for video-audio processing, and a program each of which enables a desired object sound to be more simply and accurately separated. A video-audio processing apparatus includes a display control portion configured to cause a video object based on a video signal to be displayed; an object selecting portion configured to select the predetermined video object from the one video object or among a plurality of the video objects; and an extraction portion configured to extract an audio signal of the video object selected by the object selecting portion as an audio object signal. The present technique can be applied to a video-audio processing apparatus.

Abstract: An image processing apparatus includes at least one processor or circuit configured to execute a plurality of tasks including an acquisition task configured to acquire two first images made by capturing the same object at two different viewpoints, and an image processing task configured to input the two first images into a machine learning model and to estimate a second image at one or more viewpoints different from the two viewpoints.

Abstract: An artificial intelligence (AI) platform to support selective replacement of one or more image layers of a container image build. A metadata file is subject to natural language processing and one or more corresponding vector representations are created and subject to evaluation by a set of artificial neural networks (ANNs). A first ANN assesses each vector representation with respect to compliance and operability, and the second ANN selectively assesses the vector representation(s) with respect to similarity with one or more compliant vector representations. In response to the assignment of the second score, at least one vector representation of the received metadata file is selectively replaced with at least one compliant vector representation. The metadata file is selectively provisioned with the selectively replaced vector representation(s).

Abstract: System and method for extracting human pose information from an image, comprising a feature extractor connected to a database, a convolutional neural network (CNN) with a plurality of CNN layers. Said system/method further comprising at least one of the following modules: a 2D body skeleton detector for determining 2D body skeleton information from the human-related image features; a body silhouette detector for determining body silhouette information from the human-related image features; a hand silhouette detector for determining hand silhouette detector from the human-related image features; a hand skeleton detector for determining hand skeleton from the human-related image features; a 3D body skeleton detector for determining 3D body skeleton from the human-related image features; and a facial keypoints detector for determining facial keypoints from the human-related image features.

Abstract: The present disclosure provides systems and methods that perform face reconstruction based on an image of a face. In particular, one example system of the present disclosure combines a machine-learned image recognition model with a face modeler that uses a morphable model of a human's facial appearance. The image recognition model can be a deep learning model that generates an embedding in response to receipt of an image (e.g., an uncontrolled image of a face). The example system can further include a small, lightweight, translation model structurally positioned between the image recognition model and the face modeler. The translation model can be a machine-learned model that is trained to receive the embedding generated by the image recognition model and, in response, output a plurality of facial modeling parameter values usable by the face modeler to generate a model of the face.

Abstract: A facial feature matching system comprises a facial feature matching engine. A first user selection of reference facial images is received, and facial features of reference faces are characterized using the facial feature recognition engine comprising a neural network with input, hidden, and output layers. The facial features are weighted. The weighted facial features are used to identify users that have facial features similar to the weighted facial features, wherein the respective reference faces include faces different than the faces of the users. Similarity indicators are generated for the identified users. The generated respective similarity indicators are used to generate a ordering of the identified users which is rendered via the user device. A first user selection of a second user in the ordered identified users is received and the first user and the second user are enabled to communicate over an electronic communication channel.

Abstract: Various embodiments contemplate systems, architectures and methods for extracting and selecting headshots of human or non-human entities from catalogs of images of such subjects. The methods described may find and extract faces from within groups of subjects, verify that the extracted faces correspond to the desired subject, determine cropping or masking regions, or both, of rectangular, circular, elliptical or some other geometry to provide an easily recognized image of the desired subject, expand the output image by synthesizing pixels as may be needed for a desired cropping or masking region, select preferred images among a collection of images of the desired subject, and perform other useful functions. The resulting output images may be in either direct form, reference form or both forms.

Abstract: There are provided systems, methods, and apparatus, for optimizing a policy controller to control a robotic agent that interacts with an environment to perform a robotic task. One of the methods includes optimizing the policy controller using a neural network that generates numeric embeddings of images of the environment and a demonstration sequence of demonstration images of another agent performing a version of the robotic task.

Abstract: One embodiment provides a method, including: receiving, at an information handling device, a request from a user to access content; detecting, using at least one sensor associated with the information handling device, a face of the user; generating, using at least one audio output device and subsequent to the detecting, an audible sound; determining, using a processor, whether an expected movement of the face is identified with respect to the audible sound; and granting, responsive to determining that the expected movement is identified, the user access to the content. Other aspects are described and claimed.

Abstract: Various implementations disclosed herein include devices, systems, and methods that present a view of a device user's face portion, that would otherwise be blocked by an electronic device positioned in front of the face, on an outward-facing display of the user's device. The view of the user's face portion may be configured to enable observers to see the user's eyes and facial expressions as if they were seeing through a clear device at the user's actual eyes and facial expressions. Various techniques are used to provide views of the user's face that are realistic, that show the user's current facial appearance, and/or that present the face portion with 3D spatial accuracy, e.g., each eye appearing to be in its actual 3D position. Some implementations combine live data with previously-obtained data, e.g., combining live data with enrollment data.

Abstract: A data cleaning method is provided. The method incudes: acquiring a training face dataset, the training face dataset including a plurality of training images each labeled with a person ID; acquiring a candidate face verification model and training the candidate face verification model by the plurality of training images; acquiring a plurality of feature embeddings from the candidate face verification model after training, and determining a similarity between the average feature embedding of one person ID and each image labeled as the same person ID; extracting at least one training image whose similarity is smaller than a similarity threshold from the plurality of training images; and excluding the at least one extracted training image in response to receiving a confirmation signal.

Abstract: This application discloses a face anti-spoofing recognition method and apparatus, a device, and a storage medium, and relates to the field of artificial intelligence (AI) technologies. The method is performed by a computer device, including: acquiring face video data including a to-be-detected face; detecting eye contours of the to-be-detected face from image frames of the face video data, and generating an eye contour sequence; performing eye movement probability prediction based on the eye contour sequence, and generating an eye movement state sequence; acquiring a first dataset and a second dataset in the eye movement state sequence; determining a probability of existence of an abnormal blink behavior of the to-be-detected face according to the first dataset and the second dataset; and determining that the to-be-detected face is a real face in a case that the probability is less than a predetermined threshold.

Abstract: Systems, methods, and computer readable media for identifying a person in a video are disclosed. Systems, methods, devices, and non-transitory computer readable media may include at least one processor that may be configured to generate a spatiotemporal emotion data compendium (STEM-DC) from the video and to process the STEM-DC using a deep fully adaptive graph convolutional network (FAGC) to determine a first person representation vector that represents the person in the video.

Abstract: An information processing apparatus (100) includes a collation unit (102) that collates first feature information extracted from a person included in a first image (20) with first registered feature information stored in a storage unit (110), and a registration unit (104) that stores, in a case where the first feature information is unable to be extracted from the person or a collation result in the collation unit (102) indicates a mismatch, second feature information extracted from the person in the storage unit (110) as second registered feature information, in which the collation unit (102) collates second feature information extracted from a person included in a second image (22) with the second registered feature information stored in the storage unit (110), and thus specifies the person corresponding to the second registered feature information in the second image (22).

Abstract: Disclosed is a display device for more easily providing information on a character in a current scene to a user upon receiving a character search request. The display device includes a display configured to display an image, a wireless communication interface configured to receive character information of characters relating to the image, and a controller configured to control the display to display thumbnails of the characters based on the character information, wherein the controller controls the display to display an indicator on a thumbnail of a matching character most similar to a face image of a character in a current scene among the thumbnails of the characters.

Abstract: Methods, systems, and computer-readable storage media for determining that a subject is a live person include capturing a set of images of a subject instructed to perform a facial expression. A region of interest for the facial expression is determined in a first image of the set, the first image representing a first facial state that includes the facial expression. A set of facial features is identified in the region of interest, the facial features being indicative of interaction between facial muscles and skin of the subject due to the subject performing the facial expression. A determination is made, based on the facial features, that the first image substantially matches a template image of the facial expression of the subject. Responsive to determining that the first image substantially matches the template image, identifying the subject as a live person.

Abstract: A video surveillance system includes: a detection unit that detects a predetermined event on the basis of an image captured by a first imaging apparatus; and a control unit that controls a second imaging apparatus such that the second imaging apparatus captures an image of a predetermined position after the detection of the predetermined event.

Abstract: In one embodiment, a set of feature vectors can be derived from any biometric data, and then using a deep neural network (“DNN”) on those one-way homomorphic encryptions (i.e., each biometrics' feature vector) can determine matches or execute searches on encrypted data. Each biometrics' feature vector can then be stored and/or used in conjunction with respective classifications, for use in subsequent comparisons without fear of compromising the original biometric data. In various embodiments, the original biometric data is discarded responsive to generating the encrypted values. In another embodiment, the homomorphic encryption enables computations and comparisons on cypher text without decryption. This improves security over conventional approaches. Searching biometrics in the clear on any system, represents a significant security vulnerability. In various examples described herein, only the one-way encrypted biometric data is available on a given device.

Abstract: The present invention is a system for and method of enabling an initiating party to capture, store, and retrieve an image of at least one acknowledging party performing an acknowledgement requested by the initiating party where the acknowledging party(s) may be remotely located from the initiating party.

Abstract: A computer-implemented method including receiving, by a monitoring system that is configured to monitor a property and from a touchless doorbell device that includes a camera and a motion sensor, an image, analyzing, by the monitoring system, the image, based on analyzing the image, determining that the image likely includes a representation of a person, and based on determining that the image likely includes a representation of a person, performing a monitoring system action.

Abstract: Embodiments of this application disclose a method and an apparatus for generating a three-dimensional face model. The method includes obtaining a plurality of target face images and a plurality of depth images corresponding to the plurality of target face images, the plurality of target face images comprising a same face; obtaining, according to an image type of each target face image, a regional face image that is in each target face image and that corresponds to the image type of each target face image, the image type comprising a front face type, a left face type, a right face type, or a head-up type; obtaining a regional depth image in a corresponding depth image according to the regional face image; and performing image fusion based on the plurality of obtained regional face images and the plurality of obtained regional depth images, to generate a three-dimensional face model.

Abstract: A gate apparatus includes a gate unit which is disposed on a second plane crossing a first plane in which an authentication object moves in one direction and which partitions a moving space of the authentication object from another space, an inclined face which is formed on the gate unit to cross the first plane and the second plane and which is inclined upwardly from the first plane, a display configured to display an image on the inclined face, and an image acquisition unit configured to capture an image of the authentication object in proximity to the display.

Abstract: A method may include generating a vector from unstructured data included in an untransformed transaction, and determining, for the vector, a cluster ID of cluster IDs by matching the vector with a matching cluster vector of cluster vectors. The method may further include generating a query using the cluster ID and the untransformed transaction, and transforming, using the cluster IDs, untransformed transactions to transformed transactions. The transformed transactions may each include a cluster ID. The method may further include generating, using the query, a query result from features of the transformed transactions, generating a fraud score using the query result, and presenting the fraud score and the cluster ID.

Abstract: Images of a hand are obtained by a camera. A pose of the hand relative to the camera may vary due to rotation, translation, articulation of joints in the hand, and so forth. Avatars comprising texture maps from images of actual hands and three-dimensional models that describe the shape of those hands are manipulated into different poses and articulations to produce synthetic images. Given that the mapping of points on an avatar to the synthetic image is known, highly accurate annotation data is produced that relates particular points on the avatar to the synthetic image. An artificial neural network (ANN) is trained using the synthetic images and corresponding annotation data. The trained ANN processes a first image of a hand to produce a second image of the hand that appears to be in a standardized or canonical pose. The second image may then be processed to identify the user.

Abstract: An authentication system (10) is provided with: an acquiring means (110) for acquiring a face image of a target (500) passing a gate (200); a face authentication means (120) for performing a face authentication, in which it is determined that whether or not the target is a registered target, by collating information obtained from the face image of the target with information about faces of a plurality of registered targets; and a determining means (130) for determining whether or not the target can pass through the gate on the basis of a number of times of successful authentication when the face authentication is performed a plurality of times. According to such the authentication system, it is possible to properly determine that whether or not a target can pass a gate.

Abstract: A device may include a sensor window. The sensor window may include a substrate. The sensor window may include a set of layers disposed onto the substrate. The set of layers may include a first subset of layers of a first refractive index and a second set of layers of a second refractive index different from the first refractive index. The set of layers may be associated with a threshold transmissivity in a sensing spectral range, and may be configured to a particular color in a visible spectral range and associated with a threshold opacity in the visible spectral range. The device may include a spectral sensor device aligned to the sensor window and including at least one sensor element to receive light in the sensing spectral range and provide a plurality of sensing functionalities based on at least one measurement of the light in the sensing spectral range.

Abstract: An information processing apparatus (100) includes a collation unit (102) that collates first feature information extracted from a person included in a first image (20) with first registered feature information stored in a storage unit (110), and a registration unit (104) that stores, in a case where the first feature information is unable to be extracted from the person or a collation result in the collation unit (102) indicates a mismatch, second feature information extracted from the person in the storage unit (110) as second registered feature information, in which the collation unit (102) collates second feature information extracted from a person included in a second image (22) with the second registered feature information stored in the storage unit (110), and thus specifies the person corresponding to the second registered feature information in the second image (22).

Abstract: Systems and techniques are described for processing one or more images. For example, an imaging system may receive an image of an environment and detect a face of a person in the image. The imaging system may identify profile data associated with the person and retrieve, based on the profile data, a synthesized face. The imaging system may generate a modified image of the environment at least in part by modifying the image to use the synthesized face for the person in place of the face of the person. The imaging system may further output the modified image of the environment. In some examples, the imaging system uses trained machine learning model(s) to generate the modified image.

Abstract: An information processing apparatus (10) includes a time and space information acquisition unit (110) that acquires high-risk time and space information indicating a spatial region with an increased possibility of an accident occurring or of a crime being committed and a corresponding time slot, a possible surveillance target acquisition unit (120) that identifies a video to be analyzed from among a plurality of videos generated by capturing an image of each of a plurality of places, on the basis of the high-risk time and space information, and analyzes the identified video to acquire information of a possible surveillance target, and a target time and space identification unit (130) that identifies at least one of a spatial region where surveillance is to be conducted which is at least a portion of the spatial region or a time slot when surveillance is to be conducted, from among the spatial region and the time slot indicated by the high-risk time and space information, on the basis of the information of the

Abstract: An approach for increasing security of biometric templates is described. An improved system is adapted to split a full set of features or representations of a trained model into a first partial template and a second partial template, the second partial template being stored on a secure enclave accessible only through zero-knowledge proof based interfaces. During verification using the template, a new full set of features is received for comparison, and a model is loaded based on the available portions of the model. Comparison utilizing the second partial template requires the computation of zero-knowledge proofs as direct access to the underlying second partial template is prohibited by the secure enclave.

Abstract: An image processing apparatus includes a first detection unit configured to detect, from an image in which an object including a plurality of parts is captured, first feature points corresponding to the parts of the object, an acquisition unit configured to acquire a reliability indicating a likelihood that a position indicated by a feature point is a part corresponding to the feature point for each of the first feature points detected by the first detection unit, a second detection unit configured to detect a second feature point based on some of the first feature points for a part corresponding to a first feature point with the low reliability, and a determination unit configured to determine an area including the object based on some of the first feature points and the second feature point.

Abstract: This application provides an exposure parameter adjustment method, device, and storage medium. The method includes: obtaining a face box of a first-frame image and a second-frame image, where the face box of the first-frame image is used to indicate a region of a face in the first-frame image, and the second-frame image is a next-frame image of the first-frame image; correcting the face box of the first-frame image to obtain a second-face box; cropping the second-frame image based on the second-face box to obtain a face image of the second-frame image; and adjusting an exposure parameter based on the face image of the second-frame image. In this solution, a face box of a previous-frame image is first corrected, then a face image is cropped by using the second-face box, so that a face image obtained through cropping and an actual face region in an image that is cropped are consistent.

Abstract: A method for increasing the confidence of a match between a test image and an image stored in a library database in which features are extracted from the test image and compared to features stored in the image database. If a match is determined, one or more transformations are performed on the test image to generate pose-altered images from which features are extracted and matched with pose-altered images in the database. The scores for the subsequent matchings can be aggregated to determine an overall probability of a match between the test image in an image in the library database.

Abstract: Document portion identification in a recorded video is disclosed, including: obtaining a recorded video; identifying a document portion that appears during the recorded video, wherein the document portion belongs to a document; and determining a video segment during which the document portion appears in the recorded video.

Abstract: A change detection means 840 detects an area of change in a product shelf on which a product has been arranged, on the basis of a captured image of the product. A classification means 850 classifies the change in the product shelf in the detected area of change. A shopping list generation means 860 generates a shopping list for a customer on the basis of the classification of the change in the product shelf and of shelving information on the product shelf.

Abstract: An image processing apparatus includes: an obtaining unit configured to obtain album information forming an album; a display control unit configured to display an editing screen for editing the album on a display based on the album information; and a recommendation unit configured to make a removal recommendation in the editing screen based on the album information, the removal recommendation being a recommendation to remove an image from an image group used in the album.

Abstract: An image processing apparatus is configured to acquire a query image including a subject that is a search target, and an image to be searched, extract a first feature vector that represents features of the search target included in the query image, extract a feature vector map that represents feature vectors of a subject at each position of the image to be searched, perform an arithmetic operation based on the first feature vector and the feature vector map to obtain a heat map that represents the likelihood that the search target is present.

Abstract: A device for simulating a behavior of a mammal in an environment by a virtual mammal includes a mobile head and at least one mobile eye including a first input for successive data representative of eye poses, a second input for mobility action instructions, a memory for storing information on the environment and on stabilization constraints, at least one processor assessing a current part of the environment and recording information on said current part, triggering successive movements of the head and of the eye(s) in function of said mobility action, controlling a dynamic adjustment of the successive movements of the eye(s) with respect to the successive movements of the head in function of the successive data and by using the stabilization constraints. The device further comprises a third input for training data representative of a training movement sequence of the head and the eye(s) associated with a training environment.

Abstract: Methods and systems disclosed herein describe a server that generates an artificial intelligence model comprising a neural network corresponding to at least two sets of data points corresponding to a first independent variable and each data point within a second set of data points corresponding to a second variable dependent upon a corresponding first variable; executes a clustering algorithm to generate a plurality of clusters corresponding to at least one data point within the set of data points; generates a training dataset comprising a third set of data points corresponding to a pairwise distance between each two data points within at least one cluster; and trains the artificial intelligence model based on the training dataset, wherein when the trained artificial intelligence model is executed, the artificial intelligence model identifies a distance between the new data point and at least one data point within at least one cluster.

Abstract: Provided herein is a method of pulmonary delivering to a subject at least one pharmacologically active agent being in a plant material, which is effected by pulmonary delivering the agent to the subject using a metered dose inhaler device that is configured to vaporize at least one pre-determined vaporized amount of the agent upon controllably heating the plant material, wherein the pre-determined vaporized amount is selected so as to achieve at least one pre-determined pharmacokinetic effect and/or at least one pre-determined pharmacodynamic effect induced by the agent in the subject.

Abstract: Examples of the present disclosure relate to systems and methods for providing more accurate skin assessments. These assessments can be used to produce custom recommendations that are tailored for the user's skin. Additionally, these example methods address privacy concerns of users, as its small focal distance, limited depth of field, and narrow field of view mean it can only image skin, and not the full face or body.

Abstract: A pattern recognition device (10) includes an acquisition unit (13) configured to acquire a plurality of recognition candidates obtained by pattern recognition for an input image and having a recognition score, a calculation unit (17) configured to calculate an evaluation value obtained by quantifying a possibility of a recognition candidate (K) being correct answer data corresponding to the input data on the basis of a feature quantity regarding a recognition candidate (A1) and the recognition candidate (K), for each pair of the recognition candidate (A1) having the number one recognition score and another recognition candidate (K) among the plurality of recognition candidates, and a determination unit (18) configured to determine a final recognition result from among the plurality of recognition candidates on the basis of an evaluation value for each recognition candidate (K).

Abstract: Disclosed are a face search method and device, an apparatus, and a computer-readable storage medium. According to the data volume of feature information in image feature databases currently to be searched, a user may flexibly select a technique of matching search feature information against feature information in a corresponding feature database, and/or select a technique of first performing initial matching for the search feature information against indices corresponding to feature information in a corresponding feature database, and then performing exact matching for the search feature information against feature information corresponding to a successfully matched index obtained from the initial matching.

Abstract: A device and method for performing a user identification of a user include acquiring a first image of the user. A second image of the user that is associated with a previous user identification of the user is selected. The first image and the second image are compared, and a user identification is performed based on the comparison of the first image the second image.

Abstract: An image of users of an application may be received from a computing device on a home network. The image may comprise representations of a group of users. Recognition techniques may be applied to the image. Unclaimed profiles may be created for users who are not recognized. The unclaimed profiles may be utilized by applications prior to being claimed by a user or group. Access to the unclaimed profiles may be controlled based on the identity of the network gateway used in the transmission of the image used as the basis for forming the profile.

Abstract: An information processing apparatus (2) includes: an extracting unit (212) that extracts a key point (KP) of a target object as a target key point (KP1) from an input image (IMG1); and a calculating unit (213) that calculates, as a score (SC) of the input image from which the target key point is extracted, an index value related to a reliability of the target key point based on the target key point.

Abstract: A method and computing system for rendering subsurface scattering are provided. An optical property and a thickness are received for each of a plurality of material layers. A latent space is trained for each of the plurality of material layers. A global transfer matrix is generated for at least one multi-layer material, each of the at least one multi-layer material including an ordered set of material layers selected from the plurality of material layers, by determining a transfer matrix for each adjacent pair of material layers in the ordered set of material layers using the latent space for each material layer in the adjacent pair of material layers, the transfer matrix describing angular and azimuthal reflectance and angular and azimuthal transmittance, and determining the global transfer matrix as a product of the transfer matrices of each adjacent pair of material layers.

Abstract: An electronic system, a method, and a computer program product support wireless communication with reduced distraction for a driver experiencing challenging driving conditions. The method includes connecting to a communication session with second electronic device(s) via a communication subsystem of the electronic device and via a communication network. The method includes receiving an indication of a challenging driving condition from a first image stream from image capturing device(s) positionable to have a field of view encompassing a face of a driver of a vehicle and/or a detected condition from sensor(s) that detects external conditions to the vehicle that can require the driver to be more attentive while the vehicle is in motion. In response to receiving the indication of the challenging driving condition, the method includes communicating a notification over the communication session to the second electronic device(s), the notification indicating that the driver is in the challenging driving condition.

Abstract: A method and system for detecting a leakage target by integrating temporal information. The method comprises: acquiring multiple frames of images of a target position, and arranging the multiple frames of images based on temporal information corresponding to the multiple frames of images to obtain a target image sequence; merging, in a channel dimension, the multiple frames of images in the target image sequence to obtain a multi-dimensional tensor; performing convolution processing on the multi-dimensional tensor to obtain a first output result, wherein the first output result is used for representing a frame difference between every two adjacent ones of the multiple frames of images; calculating an accumulated frame difference corresponding to the multiple frames of images based on the first output result; and inputting the accumulated frame difference to a trained target detection model as input data to obtain a second output result integrated with the temporal information.