Abstract: Photographing parameter(s) include a parameter(s) relating to exposure time and diaphragm, and is used upon capturing an image of a target. A database stores a table indicating a relationship between a value(s) of the photographing parameter(s) and a recognition accuracy threshold that is used upon determining a result of recognition. The recognition accuracy threshold associated with received photographing parameter(s) is extracted from the database, and the image is received. Recognition of the target is performed from the received image in accordance with recognition accuracy threshold.

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: There is provided a technique for dividing a plurality of images into a plurality of image groups using a method which differs according to a predetermined condition. An image processing apparatus divides the plurality of images into the plurality of image groups according to time information corresponding to the plurality of images which are candidates to be laid out on a template. Then, at least one image included in each of the plurality of image groups is laid out on the template corresponding to each of the plurality of image groups. In the dividing, the plurality of images is divided into the plurality of image groups by a method which differs according to the predetermined condition.

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 disparity estimation method performed by a processor includes extracting a first image patch comprising a reference pixel from a first image, extracting a second image patch comprising a target pixel corresponding to the reference pixel from a second image, and estimating a residual of an initial disparity between the reference pixel and the target pixel from the first image patch and the second image patch using a residual model, the residual being an estimated difference between the initial disparity and an actual disparity between the reference pixel and the target pixel.

Abstract: A computer-implemented method of signal processing comprises providing images. The method comprises for each respective one of at least a subset of the images: applying a weakly-supervised learnt function, the weakly-supervised learnt function outputting respective couples each including a respective localization and one or more respective confidence scores, each confidence score representing a probability of instantiation of a respective object category at the respective localization. The method further comprises determining, based on the output of the weakly-supervised learnt function, one or more respective annotations, each annotation including a respective localization and a respective label representing instantiation a respective object category at the respective localization. The method further comprises forming a dataset including pieces of data, each piece of data including a respective image of the subset and at least a part of the one or more annotations determined for the respective image.

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 host vehicle position estimation device includes an object determination unit configured to determine whether or not a planar object is included in a captured image, on which a host vehicle travels, a center point information acquisition unit configured to, when the planar object is included in the captured image, acquire center point information of the planar object including at least one of longitudinal center coordinate and lateral center coordinate of the planar object in the captured image, a longitudinal distance calculation unit configured to calculate a longitudinal distance as a distance between the host vehicle and the planar object in a front-rear direction of the host vehicle, and a host vehicle position estimation unit configured to estimate a host vehicle position using the positional information of the planar object on the map and the longitudinal distance.

Abstract: A display device is provided. The display device includes a display panel having a biometric detecting area configured to detect a biometric pattern of a biometric object in a blanking period of the display device. The biometric detecting area has plural blocks and each of the blocks comprises plural first pixels and plural photodetectors adjacent to the first pixels, respectively. The light sequentially penetrates the first pixels within each of the blocks in the blanking period of the display device.

Abstract: Provided is a process, including obtaining, with a robot, raw pixel intensity values of a first image and raw pixel intensity values of a second image, wherein the first image and the second image are taken from different positions; determining, with one or more processors, an overlapping area of a field of view of the first image and of a field of view of the second image by comparing the raw pixel intensity values of the first image to the raw pixel intensity values of the second image; spatially, with one or more processors, aligning values based on sensor readings of the robot based on the overlapping area; and inferring, with one or more processors, features of a working environment of the robot based on the spatially aligned sensor readings.

Abstract: A control device determines whether deviation between a predetermined position detected by a processor and a reference predetermined position stored in advance in a control device is within a preset allowable range.

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 for recognizing the face of a user that uses a device in a facility includes receiving a photo of the user and extracting a face image of the user from the photo. The method includes receiving a full candidate face set of all registered users, a first list of registered users that are within the facility, and a second list of registered users that are using other devices in the facility. The method includes generating a reduced candidate face set from the full candidate face set by excluding at least one of (1) candidate faces corresponding to users that are not included in the first list or (2) candidate faces corresponding to users that are included in the second list, from the full candidate face set. The method also includes determining whether the face image corresponds to a candidate face of the reduced candidate face set.

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: A system and method for processing a machine-readable code associated with an object moving relative to an imaging device may include imaging the machine readable code. A determination may be made as to whether image data of the machine-readable code is clipped along a leading edge of a first image frame. If the machine-readable code is determined to be clipped, (i) image data of the machine-readable code in the first image frame may be skipped, and (ii) image data contained in a subsequent image frame may be processed. Otherwise, if the code is not determined to be clipped, processing image data in the subsequent image frame may be skipped.

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 neural network-based classification method, including: obtaining a neural network and a first classifier; inputting input data to the neural network to generate a feature map; cropping the feature map to generate a first cropped part and a second cropped part of the feature map; inputting the first cropped part to the first classifier to generate a first probability vector; inputting the second cropped part to a second classifier to generate a second probability vector, wherein weights of the first classifier are shared with the second classifier; and performing a probability fusion on the first probability vector and the second probability vector to generate an estimated probability vector for determining a class of the input data.

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.