Abstract: A method, system and computer-usable medium are disclosed for machine learning to identify service request records associated with an account that is likely to escalate. Certain aspects of the disclosure include generating a random forest model using a training set of service request records to determine a probability of escalation for service requests of the training set; applying the random forest model to a current set of service request records to determine an escalation probability for service requests in the current set; and assigning service request records in the current set to a plurality of escalation probability bins, wherein the service request records of the current set are generally equally divided between the plurality of escalation probability bins, and wherein the service request records of the current set are assigned to a probability bin based on the escalation probability of the service request record.

Abstract: The disclosure relates to the automatic determination of correction factor values for producing MR images using a magnetic resonance system. A plurality of MR images is produced, wherein each MR image is produced using parameters with parameter values and using correction factors with correction factor values. In order to produce the MR images, MR data of the same examination object is acquired under the same external boundary conditions. The MR images are evaluated automatically in respect of artifacts in the respective MR image, in order to determine the MR image with the least artifacts among the MR images. The correction factor values are determined as those correction factor values which have been used to produce the MR image with the least artifacts. The parameters determine a sequence, with which the MR data is acquired for producing the MR images. The correction factors reduce influences which influence the acquisition of the MR data.

Abstract: Anonymization processing for protecting privacy and personal information can be appropriately performed based on a detection state of a moving object within an imaging range. Processing corresponding to one of a first mode for anonymizing an area of a human body based on a fixed background image and a second mode for anonymizing the area of the human body based on a basic background image is performed on an area of a detected moving object based on a detection result of a moving object detection unit.

Abstract: This specification discloses a user identity verification method, apparatus, and system, relating to the field of information technology. The method comprises: receiving a facial image and one or more eye-print pair images corresponding to an identity verification object from a client, wherein a number of the one or more eye-print pair images corresponds to a number of eye-print collection steps, comparing the facial image to a preset facial image and comparing the one or more eye-print pair images to preset eye-print templates, and sending successful identity verification information to a client when comparison results for the facial image and the one or more eye-print pair images meet preset conditions.

Abstract: An inspection apparatus includes a memory for storing shape information including a plurality of line segments representing a shape of an object; and a processor coupled to the memory and the processor that detects a plurality of feature lines from an image of the object, generates a plurality of combinations obtained by correlating each of the plurality of line segments and each of the plurality of feature lines with each other, generates a plurality of projection lines by projecting each of the plurality of line segments onto the image, sets a threshold value with respect to an error between a position of the projection lines and a position of the feature lines of the line segments included in each of the plurality of combinations based on a statistical value of the error, and classifies the plurality of combinations using the threshold value.

Abstract: A facial recognition authentication process may utilize images of a user's face that are captured while the user is being illuminated using both flood infrared illumination and patterned illumination (e.g., speckle pattern illumination). As the user's face is illuminated by both flood infrared illumination and patterned illumination, the captured images may include both flood infrared illumination data and depth map image data. Flood infrared illumination data may be generated from the images to assess two-dimensional features of the user in the captured images. Depth map image data may be generated from the pattern data in the images to assess three-dimensional (depth) features of the user in the captured images. The flood infrared illumination data and the depth map image data may be used separately by facial recognition authentication process to attempt to authenticate the user in the captured images as an authorized user of the device.

Abstract: This application relates to the field of digital watermark technologies and discloses a digital watermark embedding method and extraction method, a digital watermark embedding apparatus and extraction apparatus, and a digital watermark system. The method includes obtaining a digital watermark of a composite file, splitting the digital watermark into N sub-watermarks according to a carrier quantity N of the composite file, each sub-watermark being corresponding to partial content of the digital watermark, embedding an ith sub-watermark in an ith carrier of the composite file, to obtain an ith target carrier, and integrating N target carriers into a target file. This application resolves a problem in the related technology that a digital watermark technology cannot ensure integrity of an order file, and protects carriers of a composite file, thereby ensuring security and integrity of the composite file.

Abstract: A method for intraoral scanning, including introducing an intraoral scanner (IOS) head into an oral cavity, acquiring an image of a field of view (FOV), processing the acquired FOV image and adjusting at least one image acquisition parameter based on said processing, and an intraoral scanner (IOS) including an IOS head including at least one imager imaging a field of view (FOV), at least on light emitter that illuminates said FOV and circuitry that controls said imager and/or said light emitter.

Abstract: A method for the reconstruction of a test part in an X-ray CT method in an X-ray CT system, which has an X-ray with a focus, an X-ray detector, and a manipulator which moves the test part within the X-ray CT system. To generate recordings of the test part in various positions, the manipulator travels a predefinable parameterizable path-curve and makes recordings at triggered positions. For each recording, the position of the manipulator is determined and the respective associated projective geometry is calculated. Thereafter, a further path curve is followed having different parameters from the preceding path curve. The path curve is determined iteratively by means of an optimization algorithm, at the value of which the quality function is minimal. For each test part, a CT reconstruction is carried out by means of a suitable algorithm with reference to the allocation of the individual recordings to the respective projective geometry.

Abstract: A visual tracker may track an object by identifying the object in a frame, and the visual tracker by identify the object in the frame within a search region. The search region may be provided by a motion modeling system that independently models the motion of the object and models the motion of the camera. For example, an object motion model of the motion modeling system may first model the motion of the object, assuming the camera is not in motion, in order to identify the expected position of the object. A camera motion model of the motion modeling system may then update the expected position of the object, obtained from the object motion model, based on the motion of the camera.

Abstract: An image recognition method includes: selecting an augmentation process from augmentation processes based on a probability table, in response to an acquisition of an input image; acquiring an augmented image by augmenting the input image based on the selected augmentation process; and recognizing an object from the augmented image based on a recognition model.

Abstract: The present invention relates to a device and method for processing an image for generating a design image based on a reference marker. A method for processing an image for generating a design image based on a reference marker includes receiving, from at least one external device, a computerized tomography (CT) scan image and a plurality of oral scan images related to a person to be treated who has a plurality of reference markers attached to an inside of an oral cavity, generating a registered image by registering the images on the basis of locations of the plurality of reference markers detected from the images, determining, on the basis of the registered image, a teeth profile related to the inside of the oral cavity of the person to be treated, and generating a design image related to the inside of the oral cavity on the basis of the teeth profile.

Abstract: Examples of the present disclosure relate to methods for performing object detection. In one such example, data representing an image is received. The image comprises at least one target region and a further region. The at least one target region is identifiable using data indicative of a gaze direction of a viewer of the image. A first portion of the data is processed using a first processing scheme to perform object detection in the at least one target region of the image. The first portion of the data represents the at least one target region of the image. A second portion of the data is processed using a second, different, processing scheme. The second portion of the data represents the further region of the image.

Abstract: An image feature map generating unit (3) generates, on the basis of feature amounts extracted from a plurality of images successively captured by a camera (109), an image feature map which is an estimated distribution of the object likelihood on each of the images. An object detecting unit (4) detects an object on the basis of the image feature map generated by the image feature map generating unit (3).

Abstract: A camera-based security system protects an asset by detecting an aerial surveillor and consequently storing notifications into a video archive, alerting to an operator console, and actuating privation apparatus. One or more cameras provides video streams to a processor which derives object motion. Attributes of object motion trigger notification to record and alert on conditions associated with an aerial surveillor. Tracking of pixels, pixel blocks, and motion vectors enable rules based determination of an airborne surveillance vehicle according to characteristic hovering or lingering by masking LSB of accumulated positive and negative movements. Actuators cause privation enhancement apparatus to obfuscate the protected asset (structure, area, or volume) or to interpose between the protected asset and the surveillor without damage or disabling. The method traces a travel path of an object; and determines a ray from a private property to a surveillor drone.

Abstract: A method and system for processing medical image data are disclosed. In an embodiment, the method includes providing measurement data of a to be reproduced body region of a patient; reconstructing, using a reconstruction algorithm, a first image volume representing the body region from the measurement data; identifying a subregion representing a partial volume of the first image volume, confining the subregion within the first image volume, and assigning a specific tissue structure, differing from a remaining volume of the first image volume, to the subregion; determining, based upon the specific tissue structure of the subregion, at least one reconstruction parameter varying in comparison to the first image volume; reconstructing, from the measurement data linked with the subregion and based upon the at least one reconstruction parameter, a second image volume; and contouring, within at least the second image volume, structure boundaries between different anatomical structures of the patient.

Abstract: A method for capturing a high-quality cardiac plethysmography signal automatically and seamlessly using the video cameras embedded in personal electronic devices, includes a program running in the background that periodically takes a picture of the person using the device, runs face detection and/or recognition algorithm, and upon detection of a face, records a video, and then processes the video using algorithms to assess video quality by extracting video quality parameters. When video quality parameters are above predefined thresholds, the recorded video is processed further to generate a plethysmography signal indicative of cardiac activity. The plethysmography signal may then be processed to deduce cardiac activity. The method maintains a pleasurable user experience with the personal electronic devices.

Abstract: A method of orthodontic treatment planning for a patient includes receiving three-dimensional intraoral surface scan data of a dentition of the patient, receiving three-dimensional volumetric scan data of the dentition of the patient, and overlaying the intraoral surface scan data and the volumetric scan data to generate an integrated patient model comprising a root of at least one tooth having a longitudinal axis. The method further includes determining, for use in planning an orthodontic treatment, a center of rotation of the at least one tooth, wherein the center of rotation is defined as a point located a predetermined distance from a base of the root to an apex of the root along the longitudinal axis of the at least one tooth in the integrated patient model.

Abstract: Techniques for using image dataset transformations to verify the quality of a computer vision system are disclosed. In some example embodiments, a computer-implemented method comprises: accessing a database to obtain a reference image; generating a plurality of new images based on the reference image using a plurality of transformations, each one of the plurality of transformations being configured to change a corresponding visual property of the reference image; feeding the plurality of new images into an image classifier to generate a corresponding classification result for each one of the plurality of new images; determining that the image classifier does not satisfy one or more accuracy criteria based on the generated classification results for the plurality of new images; and based on the determining that the image classifier does not satisfy the one or more accuracy criteria, selectively performing a function.

Abstract: A vehicle system in a vehicle, comprising a first sensor configured to survey an environment proximate to the vehicle, including an object outside of the vehicle, a second sensor located within a vehicle cabin and configured to obtain data indicative of facial information of an occupant of the vehicle, and a processor in communication with the first and second sensors and programmed to output information regarding the object on a display of the vehicle system in response to the data indicative of the facial information indicating that the occupant is viewing the object outside of the vehicle.