Abstract: Aspects of the disclosure provide an image processing method, an image processing terminal, an image processing apparatus, and a non-transitory computer-readable storage medium. The method can include performing face detection on a target image to detect a face region in the target image. The method includes determining an expression class of the detected face region based on a trained expression recognition model and determining whether the determined expression class of the detected face region is a target expression class. If the determined expression class is the target expression class, head detection is performed to identify a head region in the target image and the identified head region is edited. If the determined expression class is not the target expression class, the head detection is not performed on the target image.

Abstract: A face authentication apparatus includes a face image acquisition unit, a collation unit, a time measurement unit, and a threshold change unit. The face image acquisition unit acquires a face image of an authentication target. The collation unit performs face authentication on the face image of the authentication target on the basis of a threshold. The time measurement unit measures the elapsed time from the time of starting operation of the face authentication apparatus. The threshold change unit restricts changing of the threshold to a value larger than a value determined depending on the measured elapsed time.

Abstract: A matching support apparatus includes a first display information generation unit that generates first display information for displaying, on the screen of a display device, a first display region for displaying an image including the face of a person targeted for matching captured using an image capturing apparatus, a second display information generation unit that generates second display information for displaying, on the screen of the display device 30, a second display region for displaying a reference face development image generated based on three-dimensional data of a head serving as a reference, and a user interface display information generation unit that generates first user interface display information for displaying, on the screen of the display device 30, a second user interface to be used in an operation for enabling a user to designate, in the second display region, a feature region of the person targeted for matching visible on the skin surface of the person targeted for matching.

Abstract: A system and a method for training a semantic segmentation model includes obtaining a plurality of sets of images each having an index z for visibility, iteratively training the model. Iteratively training the model includes (a) for each z above 1, obtaining preliminary semantic segmentation labels for each image of the set of images of index z?1 by applying the model to each image of the set of images of index z?1, (b) processing each preliminary semantic segmentation labels using semantic segmentation labels obtained using the model on a selected image of index 1, and obtaining processed semantic segmentation labels, (c) training the model using the set of images of index z?1 and the associated processed semantic segmentation labels, and (d) performing steps (a) to (c) for z+1.

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 methods for searching and ranking personalized videos are provided. An example method includes receiving a user request via a communication chat between a user of a computing device and a further user of a further computing device, searching, based on the user request, a pool of personalized videos to determine a first subset of personalized videos, determining first rankings of personalized videos in the first subset of personalized videos, the first rankings being based on global statistical data associated with the personalized videos, selecting, based on the first rankings, a second subset of personalized videos from the first subset of personalized videos, determining, based on at least one characteristic associated with the user, second rankings of personalized videos from the second subset of personalized videos, and presenting the personalized videos selected from the second subset within the communication chat and in order according to the second rankings.

Abstract: A method and device of similarity determination, network training, and search, an electronic device, and a storage medium are provided. The data similarity determination method includes: acquiring first data of a first object; mapping the first sub-data as a first semantic representation in a semantic comparison space, where the semantic comparison space enables a similarity between a semantic representation obtained by mapping data of the first modality to the semantic comparison space and a semantic representation obtained by mapping data of the second modality to the semantic comparison space to be computed; acquiring second data of a second object; mapping the second sub-data as a second semantic representation in the semantic comparison space; and calculating a similarity between the first data and the second data based on at least the first semantic representation and the second semantic representation.

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: A method of monitoring turbine blade creep in a gas turbine engine is provided. The method includes: receiving stereo images of a turbine blade of a row of turbine blades, the images having been obtained using a stereo borescope located in the engine adjacent the row of turbine blades; identifying same features of the blade in each of the stereo images; mapping each of the identified features by triangulation onto a 3D space to produce a 3D depth map of at least part of the blade; providing a 3D reference model of the blade; and comparing the 3D reference model with the 3D depth map to measure one or more deviations in shape of the blade to determine an amount of creep-induced distortion of the blade.

Abstract: A segmentation method and segmentation apparatus are provided, where the segmentation method includes receiving image frames comprising a current frame and an adjacent frame to the current frame, determining a feature map to aggregate the image frames based on temporal information between the current frame and the adjacent frame, extracting a feature of a region of interest (ROI) corresponding to instances included in the current frame from the feature map, predicting a class of an object corresponding to the ROI based on the feature of the ROI, and segmenting the instances by correcting an amodal mask predicted corresponding to the class of the object based on the feature of the ROI.

Abstract: An electronic device incorporates, and method and computer program product provide improved auto white balance (AWB) performance. The electronic device receives first image content from a first image capturing device of an electronic device. The electronic device receives second image content from a second image capturing device. The second image capturing device has a second field of view (FOV) that differs from a first FOV of the first image capturing device. The controller identifying, during an image capturing process for a target image within the first FOV, whether a condition exists that causes a distortion in a white balance of the first image content. In response to identifying that the condition exists, the controller captures the second image content within the second FOV, determining an AWB value for the second image content, and automatically adjusting the first image content using the AWB value for the second image content.

Abstract: Systems and methods for providing personalized videos are provided. An example method includes receiving preprocessed videos including a target face and facial expression parameters of the target face, modifying the preprocessed videos to generate one or more personalized videos by replacing the target face with a source face, where the source face is modified to adopt the facial expression parameters of the target face, providing a user interface enabling a user to share at least one personalized video of the one or more personalized videos with a further user of a further computing device, determining that an application to be used to share the personalized video does not allow auto-play of the personalized video in a video format, in response the determination, exporting the personalized video of the one or more personalized videos into an image file, and sharing the image file via the application.

Abstract: A method and system for detecting facial expressions in digital images and applications therefore are disclosed. Analysis of a digital image determines whether or not a smile and/or blink is present on a person's face. Face recognition, and/or a pose or illumination condition determination, permits application of a specific, relatively small classifier cascade.

Abstract: One example device includes an electronic processor configured identify, based on an incident type and a role of an object associated with a public safety incident, an uncompleted task that is to be performed by a public safety officer and that is associated with the object associated with the public safety incident. The electronic processor may be configured to identify first data included in a captured data file associated with the public safety incident that was generated at least partially by monitoring the object. The electronic processor may be configured to determine a time period within the captured data file during which the first data is identified to be present, and display an indication of the uncompleted task and at least one of the time period within the captured data file, the first data, and a user-selectable link to allow a user to consume the first data.

Abstract: Disclosed are systems and methods for template-based generation of personalized videos. An example method includes receiving a sequence of frame images, face area parameters corresponding to positions of a face area in a frame image of the sequence of frame images, and facial landmark parameters corresponding to the frame image of the sequence of frame images, receiving an image of a source face, modifying, based on the facial landmark parameters corresponding to the frame image, the image of the source face to obtain a further face image featuring the source face adopting a facial expression corresponding to the facial landmark parameters, and inserting the further face image into the frame image at a position determined by the face area parameters corresponding to the frame image, thereby generating an output frame of an output 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: A video input interface receives input video data in a normal state. A control input interface receives character data for On Screen Display (OSD) in a setup state. An encoder encodes the character data and stores encoded compressed data in a memory in the setup state. A decoder receives an instruction signal designating the character data to be displayed, reads, and decodes one piece of compressed data corresponding to the instruction signal from the memory, and reproduces the original character data in the normal state. A multiplexer superimposes character data on frame data and outputs the data.

Abstract: A mobile device, such as a smart phone, is provided with a camera. Digital content displayed on display screen of the mobile device may be manipulated in response to natural movements of the mobile device by a user. Motion of the mobile device is detected relative to a nearby textured surface by analyzing images of the textured surface. The displayed digital content is manipulated in response to the detected motion of the mobile device.

Abstract: Systems and methods for warning a user that media assets associated with another user depict the user with an undesired expression are provided. A plurality of media assets associated with a first user and depicting a second user may be identified. A set of expressions of the second user that the second user has indicated as undesirable may be retrieved. The depictions of the second user in the plurality of media assets and the expressions that the second user has indicated are undesirable may be compared. If it is determined that one or more of the media assets depict the second user with an undesirable expression, a notification may be generated to the second user indicating that one or more media assets of the first user depict the second user with an expression that the second user has indicated as undesirable.

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).