Abstract: An obstacle detection method can improve the accuracy of determining a relative positional relationship between two or more obstacles that are obstructed or obscured during automated driving. A road scene image of a road where a target vehicle is located is acquired. Obstacle recognition is performed to obtain region information and depth-of-field information corresponding to each obstacle in the road scene image. Target obstacles in an occlusion relationship and a relative depth-of-field relationship between the target obstacles are determined. A ranging result of each obstacle is acquired using a ranging apparatus corresponding to the target vehicle. An obstacle detection result of the road is determined based on the relative depth of field relationship between the target obstacles and the ranging result of each obstacle, thereby improving the accuracy of determining a positional relationship of obstructed or obscured obstacles during automated driving.

Abstract: Methods, systems, and computer-readable storage media for determining that a subject is a live person using a color-coded sequence including a sequence of colors. A subject is illuminated in accordance with the sequence of colors. A sequence of images of the subject is captured, where the sequence of images is temporally synchronized with illumination by the color-coded sequence. A filtered response image is generated by a matched filtering process on the sequence of images using the selected color-coded sequence. A determination is made, based on structural features around an eye region of the filtered response image, that the subject is a live person. Responsive to determining that the subject is a live person, initiating an authentication process to authenticate the subject.

Abstract: Taking a digital implant or abutment level digital impression by means of intra-oral, computed tomography or other imaging method provides the restorative doctor and laboratory accurate and effective data for determining the implant position, angulation and locking feature orientation without a physical impression. Such data is correlated with a digital library to produce an output which enables design and fabrication of an accurate restorative device such as a prosthetic tooth or crown. In this way the time-consuming, costly and error prone mechanical replication of the relevant dental anatomy is obviated.

Abstract: A detection device, such as an unmanned vehicle, is adapted to traverse a search area and generate sensor data associated with objects that may be present in the search area. The generated sensor data is used by a system including object detection inference models configured to receive the sensor data and output object data, a local object tracker configured to track detected objects in a local map, and a global object tracker configured to track detected objects on a global map. The local object tracker is configured to fuse object detections from the object detection inference models to identify locally tracked objects, and a Kalman filter processes frames of fused object data to resolve duplicates and/or invalid object detections. The global object tracker includes a pose manager, configured to track global objects in the global map and update the pose based on a map optimization process. User-in-the-loop processing includes a user interface for displaying and manual editing of detected object data.

Abstract: An individual object identification system includes: an image acquisition processor configured to perform an image acquisition process to acquire an image of a subject acquired using imaging equipment; a feature point extraction processor that extracts a feature point from the image; a local feature amount calculation processor that calculates a local feature amount of the feature point; a local feature amount group classification processor that performs classification into a predetermined number of local feature amount groups; a global feature amount calculation processor that calculates a global feature amount based on each of the local feature amount groups; a searching target image registration processor that registers a plurality of images that are searching targets; a global feature amount registration processor that registers the global feature amount related to each of the registered images in a global feature amount registration unit; a narrowing processor that narrows down the plurality of registere

Abstract: Disclosed is an effective domain name defense solution in which a domain name string may be provided to or obtained by a computer embodying a visual domain analyzer. The domain name string may be rendered or otherwise converted to an image. An optical character recognition function may be applied to the image to read out a text string which can then be compared with a protected domain name to determine whether the text string generated by the optical character recognition function from the image converted from the domain name string is similar to or matches the protected domain name. This visual domain analysis can be dynamically applied in an online process or proactively applied in an offline process to hundreds of millions of domain names.

Abstract: A neurovascular age prediction system based on white matter and a method thereof are disclosed. An analysis device generates an individual space periventricular area mask and an individual space deep white matter mask by nonlinear space counterpoint technology and MNI152 brain template, and reversely transforms individual coordinates into a transition matrix, performs white matter hyperintensity (WMH) signal image processing on the T1 weighted image and the T2 fluid attenuated inversion recovery (FLAIR) image to generate a T1 weighted WMH signal image and a T2 FLAIR WMH signal image, then converts the Ti WMH signal image and the T2 FLAIR WMH signal image into logarithms of a periventricular white matter volume and a deep WMH volume based on the individual space periventricular area mask and the individual space deep white matter mask, and substitutes the logarithms into a neurovascular age prediction model to obtain a neurovascular age prediction result.

Abstract: An image processing method and apparatus are provided. The method includes: obtaining an image; performing feature extraction on the image to obtain at least one first feature map, wherein the at least one first feature map includes N first feature values, and N is a positive integer; obtaining a target compression bit rate which corresponds to M target gain values, each target gain value corresponds to one first feature value, and M is a positive integer less than or equal to N; respectively processing corresponding first feature values based on the M target gain values to obtain M second feature values; and performing quantization and entropy encoding on at least one processed first feature map to obtain encoded data, wherein the at least one processed first feature map includes the M second feature values. According to the application, compression bit rate control is implemented in a same compression model.

Abstract: A stereoscopic image generating method is provided. The method includes: processing a first image to obtain depth data of each pixel in the first image, and generating a first depth-information map, wherein the first depth-information map includes depth information corresponding to each pixel; performing uniform processing on a plurality of edge pixels which are within a predetermined width from a plurality of edges of the first depth-information map, so that the processed edge pixels have the same depth information to establish a second depth-information map; setting a pixel offset corresponding to each pixel in the first image based on the depth information corresponding to each pixel of the second depth-information map; performing pixel offset processing on the first image to generate a second image; and outputting the first image and the second image to the display unit to display a stereoscopic image.

Abstract: An image processing method includes obtaining a to-be-processed image, performing an image processing operation on the to-be-processed image by inputting the to-be-processed image into a corresponding image processing model to obtain a processed image, and obtaining an output image according to the processed image of the corresponding image processing model. The image processing operation includes at least one of color deviation removal processing or ghost effect removal processing. The image processing model corresponding to the color deviation removal processing is a first image processing model, and the image processing model corresponding to the ghost effect removal processing is a second image processing model.

Abstract: A measurement apparatus, comprising: a projection apparatus configured to project a predetermined pattern on a subject; and an image capturing system configured to capture a group of images from at least two different viewpoints, wherein the distance between the viewpoints is shorter than the distances between the projection apparatus and the viewpoints, the measurement apparatus further comprising: relative position calculation means for obtaining a relative position of the projection apparatus relative to at least one of the viewpoints from pattern image positions on the group of images and a positional relationship between the viewpoints, wherein distance information regarding the subject is acquired from the relative position and a pattern image position on an image at the viewpoint.

Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry detects, for each of target points corresponding to feature points, a reference point having a spatial correlation with the target point in a medical image. The processing circuitry generates candidate points corresponding to the target point for each of the target points by using a detection model. The processing circuitry selects, for each of the target points, a candidate point based on a position feature indicating a spatial position relationship between the target point and the reference point. The processing circuitry selects, for each of a plurality of candidate point combinations, a candidate point combination based on a structural feature indicating a spatial structural relationship between the target points. The processing circuitry outputs feature points in the medical image based on the selected candidate point and candidate point combination.

Abstract: A computer implemented method and system for fitting eyeglasses captures images of the consumer while naturally trying-on frames in the normal course of selecting new frames. The system and method capture natural images of frame placement and using gaze prediction and eye tracking techniques ascertain eye measurements for accurate placement of the prescription within new eyewear.

Abstract: A document processing system processes a document image to identify document image regions including floating images, structured data units, and unstructured floating text. A first masked image is generated by deleting any floating images from the document image and a second masked image is generated by deleting any structured data units from the first masked image. The structured data units and the unstructured floating text are thus identified serially one after another. Textual data is extracted from the structured data units and the unstructured floating text by processing the corresponding document image regions via optical character recognition (OCR). Entities are extracted from the textual data using natural language processing (NLP) techniques.

Abstract: An image processing method includes acquiring a captured image obtained by imaging, generating a first image by correcting a blur component of the captured image, and generating a second image based on the captured image, the first image, and weight information. The weight information is generated based on (i) information on brightness of the captured image or information on a scene of the captured image and (ii) information on a saturated area in the captured image.

Abstract: A depth sensing system and a depth sensing method are provided. The sensing system includes depth sensing module and a processor for performing the sensing method. The depth sensing method incudes: obtaining a sensed target data set via a depth sensing module; calculating a period number corresponding to a measuring pixel; and calculating an actual range value or an actual depth of the measuring pixel in accordance with a period number and a range value of the measuring pixel. The step of calculating the period number of the target data set includes: calculating a spatial ratio in accordance with the position values of the pixel of optical center and measuring pixel, and a focal length of the depth sensing module; calculating a basic range in accordance with the spatial ratio and an unit depth; and calculating the period number corresponding to the measuring pixel.

Abstract: A system for determining candidate answers during an interview. The system may include a memory storing executable instructions, and at least one processor configured to execute the instructions to perform operations. The operations may include capturing, by an image sensor, a plurality of images comprising a plurality of candidate answers; detecting, based on the captured images, a first bounding box comprising the plurality of the candidate answers; detecting, based on the captured images, a second bounding box comprising a plurality of alphanumeric characters, a first one of the alphanumeric characters being located on a line of software code; calculating a distance from a side of a first bounding box to a side of a second bounding box; and determining, based on the calculated distance, a source code alignment.

Abstract: Disclosed herein are methods, systems, and apparatus for automated license plate recognition and methods for training a machine learning model to undertake automated license plate recognition. For example, a method can comprise dividing an image or video frame comprising a license plate into a plurality of image patches, determining a positional vector for each of the image patches, adding the positional vector to each of the image patches and inputting the image patches and their associated positional vectors to a text-adapted vision transformer. The text-adapted vision transformer can be configured to output a prediction concerning the license plate number of the license plate.

Abstract: A CPU acquires a distance image or a visible light image obtained by imaging a marker for measuring an SID as an object to be imaged using a TOF camera or a visible light camera. In addition, the CPU derives a marker distance between the TOF camera or the visible light camera and the marker from an image of a marker region corresponding to the marker in the acquired distance image or visible light image. Further, the CPU derives the SID on the basis of the derived marker distance and information indicating a positional relationship between an acquisition unit and the marker.

Abstract: The present application discloses a computing system for implementing an artificial neural network model. The artificial neural network model has a structure of multiple layers. The computing system comprises a first processing unit, a second processing unit, and a third processing unit. The first processing unit performs computations of the first layer based on a first part of input data of the first layer to generate a first part of output data. The second processing unit performs computations of the first layer based on a second part of the input data of the first layer so as to generate a second part of the output data. The third processing unit performs computations of the second layer based on the first part and the second part of the output data. The first processing unit, the second processing unit, and the third processing unit have the same structure.