Abstract: Techniques for identifying lidar points associated with static objects, and using such lidar points to annotate objects within two-dimensional images are discussed herein. In some examples, an object manager may receive accumulations of lidar data captured from lidar devices of a vehicle while traversing within a driving environment. In some examples, the object manager may receive a plurality of annotated images. Such annotations may identify static objects within the driving environment. In some instances, the object manager may project a lidar point into an annotated image and determine that the lidar point is associated with an annotated pixel. Based on the pixel being associated with the annotated object, the object manager may determine that the lidar point is associated with object. In some examples, the object manager may determine a subset of lidar points that are associated with the object.

Abstract: In an aligning method by grouped data according to the present disclosure, while initial grouped data is generated and a process of generating and aligning three-dimensional image data is performed, if a state in which pieces of three-dimensional volume data are not connected to each other continues for a predetermined time or longer, new grouped data is generated, so that at least one discontinuous grouped data may be generated. If three-dimensional volume data stored in new grouped data and three-dimensional volume data of previously generated grouped data are identified to have overlapping parts therebetween, an additional alignment step is performed to connect the overlapping parts to each other. As a result, a data gap is supplemented, and a patient's entire oral model data can be easily obtained.

Abstract: An image segmentation apparatus for magnetic resonance imaging according to an embodiment includes processing circuitry. The processing circuitry is configured to obtain a localizer image of an organ, the localizer image being three-dimensional or being in a plurality of layers and two-dimensional. The processing circuitry is configured to temporarily localize, on a basis of the localizer image, a segment in which the organ is present in terms of the layer direction of a plurality of slices included in the localizer image. The processing circuitry is configured to obtain a segmentation result of the organ, by performing an image segmentation process on the localizer image positioned inside the segment in which the organ is present.

Abstract: An image forming apparatus includes an image forming portion to form an image on a sheet, a tray on which sheets to be fed are stacked, and a swing member supported by the tray and configured to swing in a case where the swing member is pushed by a discharged sheet. A stacking portion includes a first surface on an upper portion of a first portion, and a moving member in contact with the discharged sheet. The moving member can be positioned at a position downstream of the first surface in the discharge direction, wherein the swing member overlaps with the first surface as viewed in the sheet width direction in a case where the swing member is not in contact with a discharged sheet, and the swing member is arranged such that a lower end of the swing member is not in contact with the stacking portion.

Abstract: Embodiments are disclosed for multichannel content recommendation. The method may include receiving an input collection comprising a plurality of images. The method may include extracting a set of feature channels from each of the images. The method may include generating, by a trained machine learning model, an intent channel of the input collection from the set of feature channels. The method may include retrieving, from a content library, a plurality of search result images that include a channel that matches the intent channel. The method may include generating a recommended set of images based on the intent channel and the set of feature channels.

Abstract: A facial parsing method and apparatus, a facial parsing network training method and apparatus, an electronic device and a non-transitory computer-readable storage medium, which relate to the field of artificial intelligence. The facial parsing method includes inputting a facial image into a pre-trained facial parsing neural network; extracting a semantic feature of the facial image by using a semantic perception sub-network; extracting a boundary feature of the facial image by using a boundary perception sub-network; and processing the cascaded semantic feature and boundary feature by using a fusion sub-network, to obtain a facial region to which each pixel in the facial image belongs. The method can improve the resolution capability of a neural network for boundary pixels between different facial regions of a facial image, thereby improving the precision of facial parsing.

Abstract: When a character string corresponding to a predetermined item is not extracted in a first document image as a processing target by entity extraction processing, the character string corresponding to the predetermined item in the first document image is acquired based on positional information about an area where the character string corresponding to the predetermined item is previously extracted in a second document image having the same format as that of the first document image.

Abstract: Useful information on image transmission is provided to a user who transmits an image in a network print technology.

Abstract: By processing an image in which a plurality of articles (such as products) placed on a shelf are captured, an image processing unit (120) determines the article name (such as the product name) of each of the plurality of articles captured in the image. Determining an article name also includes determining identification information tied to the article name. When a specific condition is satisfied for an article the article name of which is indeterminable by the image processing unit (120) (hereinafter described as an undetermined article), an article inference unit (130) infers the article name of the undetermined article to be the article name of an article positioned adjacent to the undetermined article.

Abstract: A processor-implemented method with image preprocessing includes: transforming a fingerprint image into a frequency domain; suppressing a low-frequency region corresponding to a first noise component of the fingerprint image in the frequency domain; and restoring the frequency domain, in which the low-frequency region is suppressed, as an image.

Abstract: A method of adjusting mental state includes acquiring video data of a first individual, identifying a first set of features based on image, audio, and text data extracted from the video data, predicting a baseline mental state for the first individual based on the first set of features, identifying a target mental state, and simulating a predicted path from the baseline mental state to the target mental state. The predicted path is simulated using a multidimensional mental state model, a plurality of actions, and a computer-implemented machine learning model. The predicted path comprises one or more actions of the plurality of actions and corresponding changes to at least one of first and second dimensions of the multidimensional mental state model. The one or more actions of the predicted path are output to a second individual and are performable to adjust the baseline mental state of the first individual.

Abstract: By processing an image in which a plurality of articles (such as products) placed on a shelf are captured, an image processing unit (120) determines the article name (such as the product name) of each of the plurality of articles captured in the image. Determining an article name also includes determining identification information tied to the article name. When a specific condition is satisfied for an article the article name of which is indeterminable by the image processing unit (120) (hereinafter described as an undetermined article), an article inference unit (130) infers the article name of the undetermined article to be the article name of an article positioned adjacent to the undetermined article.

Abstract: Embodiments herein provide a method for detecting a candid moment in an image frame. The method includes: receiving, by an electronic device, image frames; determining, by the electronic device, a candid score of each image frame in the image frames using a Machine Learning (ML) model, wherein the candid score is a quantitative value of candidness present in the image frames; determining, by the electronic device, whether the candid score of the image frame in the image frames meets a threshold candid score; identifying, by the electronic device, that the candid moment is present in the image frame in response to determining that the candid score of the image frame meets the threshold candid score; and displaying, by the electronic device, the image frame comprising the candid moment.

Abstract: An optical member includes a lens array including lens bodies, and transmissive members. The transmissive members are made of a material having a uniform refractive index, and are disposed at positions nearer an object to be read or at positions farther from the object to be read than the corresponding lens bodies are disposed. The transmissive members have a columnar shape extending along the optical axes of the lens bodies, and allow light incident through one end faces to exit through the other end faces. The optical axes of the lens bodies are deviated from the central axes of the transmissive members corresponding to the respective lens bodies at least in the sub-scanning direction, and an end face of the transmissive member to which an end face of each lens body is opposed is thereby an end face of the corresponding transmissive member.

Abstract: Systems and methods include acquisition of a first image of a first activity record, determination of first text based on the first image, generation of a first embedding based on the first text, generation of a second embedding based on the first embedding using a first model, where a number of dimensions of the second embedding is less than a number of dimensions of the first embedding, determination of a first cluster based on the second embedding using a second trained model, the second trained model trained using unsupervised learning, and determination of a first activity type associated with the first activity record based on the first cluster, the second embedding and historical activity data associating the first cluster with a plurality of activity types and each of the plurality of activity types with a respective embedding metric.

Abstract: A method includes: selecting, from among a series of images, a candidate image that was captured at an image-capturing time instant corresponding to a point-cloud-generating time instant at which a point cloud was generated; generating a two-dimensional data set from the point cloud; superimposing the two-dimensional data set on the candidate image to result in a superimposed image; obtaining a derived distance inconsistency between the candidate image and the two-dimensional data set in the superimposed image; feeding the derived distance inconsistency into a conversion model to obtain a derived time difference; calculating a target time instant based on the derived time difference and the image-capturing time instant of the candidate image; and selecting, from among the series of images that have been received from the image capturing device, a target image that was captured at a time instant the closest to the target time instant.

Abstract: A presentation attack detection system includes RGB and thermal imaging cameras for acquiring images of an individual and a processor operable to determine a metric for whether the individual is a real human based on the thermal imaging and RGB image data. Related methods are also described.

Abstract: Provided in embodiments of the disclosure are an information generation method and apparatus. The information generation method comprises: obtaining an input video, and extracting video frames and audio data in the input video; processing the video frames to determine a target video frame, and processing the audio data to obtain text information; determining, based on a corresponding time of the target video frame in the input video and corresponding time of the text information in the input video, target text information corresponding to the target video frame; and processing the target video frame and the target text information to generate graphic and text information.

Abstract: A program causes a computer to perform processing of: acquiring an endoscopic image obtained by capturing a subject using an endoscope; extracting region-of-interest information from the acquired endoscopic image; acquiring a three-dimensional medical image obtained by capturing an inside of a body of the subject using at least one of X-ray CT, X-ray cone beam CT, MRI-CT, and an ultrasonic diagnostic device; deriving position information in a coordinate system of the three-dimensional medical image specified by the region-of-interest information and the three-dimensional medical image; and storing the region-of-interest information and the three-dimensional medical image in association with each other based on the derived position information and a capturing time point of each of the endoscopic image and the three-dimensional medical image.

Abstract: Disclosed are a method and apparatus for converting 3D manuals into 2D interactive videos for a cloud service.