391 results about "Image estimation" patented technology

A system for collecting data for training a computer vision model for shape estimation includes: an imaging system configured to capture one or more images; and a processing system including a processor and memory storing instructions that, when executed by the processor, cause the processor to: receive one or more input images from the imaging system; estimate a pose of an object depicted in the one or more images; render a shape estimate from a 3-D model of the object posed in accordance with the pose of the object; and generate a data point of a training dataset, the data point including one or more images based on the one or more input images and a label corresponding to the one or more images, the label including the shape estimate.

The present disclosure discloses a method for suppressing the azimuth ambiguity of multi-channel SAR systems based on channel cancellation, which falls within the field of radar signal processing. The method includes: imaging echoed of the multi-channel SAR system based on a linear mapping reconstruction algorithm to obtain a reconstructed high-resolution wide-swath image; estimating positions of the azimuth ambiguity regions of the reconstructed high-resolution wide-swath image; extracting ambiguity images in the azimuth ambiguity regions based on channel cancellation and the refocusing algorithm; and suppressing a repetitive ambiguity image in imaging the echo of the multi-channel SAR system. The method weakens the influence of the original image on azimuth ambiguity extraction, improves the performance of ambiguity suppression, and solves the problem of additional repetitive ambiguity in multi-channel SAR systems by reconstructing the ambiguity signal, and improves the image quality of the multi-channel SAR system, which has great value for subsequent applications such as SAR image interpretation.

The invention relates to an asteroid global terrain three-dimensional reconstruction method for illumination variation, and the method comprises the following steps: inputting an asteroid optical image, estimating the pose of a camera, generating a sparse point cloud, and initializing a Gaussian radiation field; using the image segmentation large model to output a segmentation mask of the asteroid optical image, and pruning the Gaussian radiation field; identifying a shadow region on the surface of the asteroid by combining a # imgabs0 # mixed mask output by a Gaussian radiation field; the camera position, the spherical harmonic coefficient and the Hash code are combined with the angle of the incident light to be input into a neural network, and color values of Gaussian primitives of illumination and shadow areas are regressed; depth normal consistency loss and rotation variance and scale constraint loss are added, optimization of a Gaussian radiation field is jointly supervised in combination with luminosity loss, a Gaussian opacity field is calculated, and a three-dimensional model of the asteroid global terrain is extracted. According to the method, the shadow region on the asteroid can be identified, and the three-dimensional reconstruction precision of the asteroid with surface illumination variation is improved.

An information processing system according to an aspect of the present disclosure includes: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: estimate an age of a customer from a customer image; receive input of identification information about a product; display a first age verification screen requesting the customer to express his / her age in response to the input of the identification information about an age-restricted product in a case where the estimated age of the customer meets a predetermined condition; and display a second age verification screen requesting the customer for proof of age in response to the input of the identification information about an age-restricted product in a case where the estimated age of the customer does not meet the predetermined condition.

The invention discloses a vertical rail scanning remote sensing satellite natural multi-coverage image resolution improving method and system, and relates to the field of remote sensing image processing. The method solves the problems that due to the fact that the distance between an existing vertical rail scanning imaging sensor and a ground target is increased, image pixels cover a wider ground range, the actually-measured spatial resolution is reduced, and fine detection and recognition of ships, aircrafts and the ground target cannot be supported. SIFT feature point extraction is carried out, and feature points extracted from different images are matched by using a Euclidean nearest distance matching strategy; taking one registered image as a reference, and constructing an initial high-resolution image through up-sampling; establishing an imaging degradation model from a high-resolution image to a low-resolution observation image; calculating a residual image of the simulation image and the real observation image; and back-projecting the residual error back to the high-resolution image space, and updating high-resolution image estimation.

A substrate inspection apparatus for inspecting a substrate, includes: an acquisition part configured to acquire an estimated image of an inspection target substrate after a process by a substrate processing apparatus, based on an image estimation model created by a machine learning by using a captured image before the process by the substrate processing apparatus and a captured image after the process by the substrate processing apparatus for each of a plurality of substrates, and a captured image of the inspection target substrate before the process by the substrate processing apparatus; and a determination part configured to determine the presence or absence of a defect in the inspection target substrate, based on a captured image of the inspection target substrate and the estimated image of the inspection target substrate after the process by the substrate processing apparatus.

To provide an image processing apparatus that can more correctly determine a row of teeth having permanent teeth and milk teeth mixed therein.SOLUTION: An image processing apparatus comprises: an acquisition unit that acquires an image of the inside of the oral cavity; an estimation unit that estimates a row of teeth from an image acquired by the acquisition unit by using a learning model that has learned the relationship between the image of the inside of the oral cavity and the row of teeth; and a correction unit that makes a correction on a result of the estimated row of teeth on the basis of a rule related to the order of losing the milk teeth and getting the permanent teeth.SELECTED DRAWING: Figure 4

The invention discloses an image compressed sensing reconstruction method and system based on a recursive diffusion model, and belongs to the technical field of image processing and compressed sensing, and the method comprises the steps: obtaining a to-be-reconstructed original image; performing block compressed sensing sampling on an original image to be reconstructed to obtain a complete observation value; initializing the complete observation value by adopting a pseudo-inverse reprojection operation to obtain an initial reconstructed image; performing complete reconstruction on the initial reconstruction image by using a recursive diffusion model; wherein in the whole image domain, the initial reconstruction image is used as the image estimation of the current iteration, through a lightweight recursion UNet submodule and an operator condition circulation prior submodule in the recursion diffusion model, multi-step iteration reconstruction is carried out, and a final reconstruction image is output. According to the method, a recursive refinement mechanism and stride memory prior are introduced, high-quality image reconstruction is realized under a small number of iteration steps, and the calculation and storage overhead is remarkably reduced.

The invention discloses a snapshot multispectral camera demosaicing method and device based on a binary tree coating array, and the method comprises the steps: extracting a plurality of single-spectrum mosaic images according to a multispectral original image and a spectrum, and carrying out the estimation of a pseudo panchromatic estimation image according to the multispectral original image; calculating a difference value between each spectral band sparse pseudo panchromatic estimation image and the original spectral band sparse image, and calculating difference values at all pixel positions; adding the difference image after filtering interpolation with the pseudo panchromatic estimation image to obtain a demosaicing reconstruction result based on the pseudo panchromatic estimation image; and enhancing the spatial high-frequency information of the binary tree low-node spectral band image based on the binary tree high-node spectral band image by using the color and spatial correlation between adjacent spectral bands. According to the method, the problem of artifacts caused by weak spectrum correlation of the wide spectrum distribution optical filter can be solved, the artifacts of the reconstructed image are reduced, and the spatial resolution capability of the demosaiced image is improved.

The invention discloses a shield deslagging volume dynamic detection method and a detection system thereof, and relates to the technical field of shield deslagging volume metering, the method comprises the following steps: arranging sound wave and vibration sensors, collecting sound vibration signals in a deslagging process, and calculating to obtain a first volume estimation value; collecting propelling attitude and conveyor rotating speed information, calculating an attitude correction coefficient and correcting the first estimated value to obtain a second estimated value; based on the dynamic image sequence at the deslagging window, extracting section and trajectory features to form a third volume estimation value; detecting the water content of the muck through a microwave sensor, calculating a water content correction coefficient, and compensating and correcting an image estimation result to obtain a fourth volume estimation value; and finally, carrying out weighted fusion on the second and fourth estimated values to obtain the final deslagging volume. According to the method, multi-source information of sound vibration, vision and water content is fused, the precision and robustness of slag discharge volume estimation are effectively improved, the method adapts to complex working condition changes, and the safety and efficiency of shield construction are guaranteed.

A shape estimation apparatus estimates, based on captured images obtained by capturing an object from different directions using a plurality of image capturing apparatuses, a first element group representing a three-dimensional shape of the object, determines whether to delete elements from the first element group, and generates a second element group by deleting the elements from the first element group. With respect to a first element among elements forming a surface of the shape represented by the first element group, if a distance between the first element and a second element corresponding to a position at which a straight line connecting the first element and the image capturing apparatus that has captured the first element intersects the surface does not exceed a predetermined threshold, the first element is excluded from a deletion target.

A system for remote monitoring of a workout, including: a processor; a non-transient memory; an imaging sensor; and a display device, the non-transient memory having computer-readable instructions stored thereon which, when executed by the processor, perform steps including: capturing imagery of at least a face of a subject, estimating and monitoring a peripheral blood volume pulse (BVP) or heart rate from the imagery using remote photoplethysmography (rPPG), performing facial age estimation using computer vision to analyze the imagery of the face to estimate an age of the subject, estimating a maximum heart rate using at least the age of the subject, calculating a heart rate zones as a predetermined percentage of the maximum heart rate, and displaying an indication of a current heart rate zone based on a current BVP or heart rate.

The invention relates to a method for holographic generation of an array of focusing points arranged according to multiple positions of the field of an optical system, which comprises: (S10) detecting images formed by the optical system at a plurality of calibration points arranged according to multiple positions of the field of the optical system; (S20) estimating aberrations introduced by the optical system onto the optical field from the detected images; (S30) applying a phase mask to the optical beam in order to generate a plurality of focusing points arranged according to multiple positions in the field of the optical system; wherein the phase mask is calculated from the estimated aberrations in order to simultaneously compensate for the aberrations at each focusing point. The invention also relates to a holographic generation system which carries out this method.

To provide an information processor, an information processing method and an information processing program for grasping the degree of understanding of a student during a lesson in real time, and for facilitating the selection of teaching material contents suitable for the lesson and the review of the lesson.SOLUTION: The information processing apparatus 10 is an information processing apparatus that supports a class by a teacher user using a teacher user terminal, and includes a captured data acquisition unit 12 that acquires a camera image from each of student user terminals of student users who take the class, an understanding level determination unit 13 that estimates an understanding level of the student user for the class on the basis of the camera image, and a display control unit 14 that aggregates the estimated understanding levels of the student users and displays transition of the understanding levels in the class on the teacher user terminal.SELECTED DRAWING: Figure 1

An in-vehicle display system includes: an angle estimation unit that estimates, based on an image captured by a camera, an angle provided by a straight line connecting an own vehicle and a preceding vehicle with respect to a front-rear direction of the own vehicle; an inter-vehicle distance estimation unit that estimates an inter-vehicle distance between the own vehicle and the preceding vehicle based on a detection result obtained by a radar sensor of the own vehicle; a height calculation unit that calculates a height of the preceding vehicle based on the angle and the inter-vehicle distance; a gradient estimation unit that estimates a gradient of a road ahead of the own vehicle based on a temporal change of the height of the preceding vehicle; and a display control unit that displays an icon on a windshield so that the icon is superimposed on a landscape ahead of the own vehicle.

A method of training one or more neural networks, the one or more neural networks being for use in lossy image or video encoding, transmission and decoding, the method comprising the steps of: receiving first and second input images; estimating optical flow information indicative of a difference between representations of the first and second input images; receiving first and second output images; estimating optical flow information indicative of a difference between representations of the first output image and the second output image; updating the parameters of the one or more neural networks based on the evaluated function; and repeating the above steps using a first set of input images to produce one or more trained neural network.

The invention relates to the technical field of nuclear medicine diagnosis, and particularly provides an ROI image reconstruction method and system based on SPECT data, and the method comprises the steps: reconstructing a coarse scanning image according to large-view coarse scanning projection data; generating ROI image estimation according to the coarse scanning image; performing loop iteration updating on the ROI image estimation until a preset convergence condition is met; the loop iteration updating process comprises the following steps: generating estimated projection data according to ROI image estimation of current iteration; obtaining projection deviation according to the estimated projection data and the small-view fine scanning projection data; obtaining an image state index according to ROI image estimation of the current iteration and the previous iteration; determining a coarse scanning data contribution weight according to the image state index; updating the ROI image estimation of the current iteration according to the projection deviation, the small-view fine scanning projection data, the coarse scanning data contribution weight and the large-view coarse scanning projection data; according to the method, the iterative reconstruction process can adapt to the dynamic change of the image state.

A computer-implemented method for determining an estimation of a two-dimensional scattered radiation distribution in a two-dimensional X-ray image that is based on an imaging procedure performed by an X-ray detector is provided. The method includes receiving the X-ray image, applying an estimation algorithm to the X-ray image or to a two-dimensional intermediate image determined from the X-ray image. The estimation algorithm determines a respective two-dimensional partial scattered radiation image for a plurality of physical scatter processes such that image values of pixels of the respective partial scattered radiation image in each case describe an estimated value for a respective scattered radiation dose that was applied to a respective detector region of the X-ray detector assigned to the respective pixel during acquisition of the X-ray image by the respective physical scatter process. The estimation of the scattered radiation distribution is determined based on the plurality of partial scattered radiation images.

The invention provides a dark image enhancement method and device, electronic equipment and a storage medium, and relates to the technical field of image processing. The dark image enhancement method comprises the following steps: estimating an incident light pattern according to a dark image; performing difference processing on the dark image and the incident light image to obtain a difference image; enhancing the difference image by using gamma correction to obtain a corrected image; and determining a first gradient matrix according to the gradient of the dark image and the corrected image, and calculating a first structure tensor by using the first gradient matrix and a preset matrix. And calculating a second gradient matrix of the dark image, multiplying the second gradient matrix with the supernormal matrix to obtain a third gradient matrix, and reconstructing the image by using the lookup table to obtain an enhanced fusion image. The structure tensor is introduced to supplement energy, the estimated difference image is fused to realize dark image enhancement, and the calculation complexity is reduced while the edge details and color information of the original dark image are retained.

The invention relates to a satellite-borne GNSS-S radar moving ship multi-station information intelligent refocusing SAR imaging method, and the method comprises the steps: carrying out the BP SAR imaging processing of M double-station scattering echo signals of a GNSS-S radar, and obtaining M double-station SAR images; selecting N double-station SAR images with the output signal-clutter-noise ratio greater than 5dB, and respectively performing ship detection and positioning to obtain N position coordinates of the same ship target; establishing a multi-objective optimization function based on the N pieces of position coordinate information of the ship target, and performing intelligent optimization on the multi-objective optimization function by using a genetic optimization algorithm to obtain two-dimensional speed information of the moving ship target; and performing phase compensation on the moving ship target in the M double-station SAR images by using the two-dimensional speed information of the ship target to obtain a refocused double-station SAR image, and estimating the high-precision coordinate position of the ship target. According to the method, the more accurate velocity vector can be obtained, so that the imaging effect of the refocusing SAR is better, and uncontrolled positioning with higher precision is realized.

A method for training a neural network to extract domain invariant features suitable for image registration comprises collecting a first set of multi-modal images comprising a first image of at least one first modality and a corresponding second image of at least one second modality (3). A first feature is extracted from at least one first image while a second feature is extracted from at least one second image (5, 7) using a feature extraction subnet of a neural network. Domain-invariant loss and homography loss are estimated for the images (9, 11), and the neural network is trained to minimize a multi-objective loss function comprising domain-invariant embedding loss and homography loss (13).

A method of estimating a posture of a robot is disclosed. The posture estimation method of the robot according to the present disclosure includes: generating a first marker and at least one second marker and attaching them to the robot; collecting an image including the first marker and at least one of the plurality of second markers; estimating position information and rotation information of the first marker and each of the second markers; deriving the position information and the rotation information of the first marker depending on a relative positional relationship between the first marker and each of the second markers when the first marker is not identified; and estimating a posture of the robot based on the position information and the rotation information of the first marker.

The invention relates to a precipitation image estimation method based on a multi-scale convolution attention decoder, a precipitation estimation model based on the multi-scale convolution attention decoder MCAD is constructed, the MCAD decodes features extracted by an encoder and outputs an estimated precipitation image, the MCAD adopts a multi-scale convolution attention module MCAM architecture, and the precipitation image is estimated by the MCAM architecture. The MCAD combines multi-scale information extraction and an attention mechanism, constructs a multi-scale feature pyramid through parallel depth divisible convolution, synchronously captures spatial distribution features of large-scale layered cloud precipitation and small-scale convective precipitation, and fully excavates precipitation information features in satellite remote sensing data; a channel attention module CAB is designed to dynamically calculate contribution weights of FY-4B infrared channels, and feature expression of water vapor sensitive channels (9-11 channels) is enhanced; and in combination with spatial distribution of a spatial attention module SAB focusing rainfall core area, the accuracy of rainfall intensity estimation is enhanced through feature map re-calibration.

The present invention provides a method and system for rapidly deblurring a fuzzy QR code, relating to the field of QR code deblurring. The method comprises: S1, preprocessing; S2, setting a maximum deblurring level (max_scale) and initializing a fuzzy kernel function; S3, constructing a first objective function and a second objective function; S4, estimating a clear image; S5, estimating a fuzzy kernel function; S6, if max_scale is reached, proceeding to S11; otherwise, proceeding to S7; S7, if three image-finding patterns are detected, proceeding to S8; otherwise, proceeding to S9; S8, determining whether decoding is currently possible; if so, proceeding to S11; otherwise, proceeding to S9; S9, determining whether the current deblurring level is max_scale–1; if so, proceeding to S10; otherwise, proceeding to S4; S10, obtaining an image clarity evaluation value Q and a threshold value T; if Q>T, proceeding to S4; if Q<T, proceeding to S11; and S11, outputting a deblurred QR code image. While ensuring the recognition rate of the deblurred QR code image, the method improves the efficiency of QR code image deblurring and effectively and accurately deblurs fuzzy QR codes.

There is provided an information processing apparatus, an information processing method, and a program that allow for reduction in power consumption in authentication using multiple cameras. The information processing device performs camera search processing of searching for a camera suitable for authentication of a target among non-activated cameras yet to be activated, on the basis of a position and an angle of the target estimated from an image captured by an active camera which is an activated camera among multiple cameras, and activating the camera found by the search. The present technology can be applied to facial recognition systems.

This invention discloses a quantum entangled light spatial correlation imaging method based on iterative deconvolution, belonging to the field of quantum information. The method includes the following steps: illuminating the target sample with a position-momentum entangled light source, and acquiring multiple frames of entangled light carrying sample information using a single-photon camera; performing statistical operations on the acquired multi-frame images to remove irrelevant background noise and obtain a joint probability distribution image of the sample; extracting the correlation width using the spatial distribution image of the joint probability distribution through differential coordinate projection to construct the point spread function of the optical system; using the point spread function for forward convolution projection and backward error projection, updating the image estimate through iterative calculation until the convergence condition is met to obtain the target sample image. This invention utilizes a camera to image with a position-momentum entangled light source under low illumination conditions, which can obtain high-contrast target imaging and has potential advantages in imaging light-sensitive samples.

Provided is an information processing device comprising: an acquiring unit that acquires an image of the ground around a moving body and information indicating the behavior of the moving body when the moving body moves; an estimating unit that estimates the type of the ground on the basis of the image; and a predicting unit that predicts the behavior of the moving body when the moving body moves on the ground of the type estimated by the estimating unit on the basis of a regression model for the type of the ground, and updates the regression model for the type of the ground on the basis of the predicted behavior of the moving body and the behavior of the moving body acquired by the acquiring unit. This allows the behavior of the moving body to be estimated more appropriately.

This invention discloses a low-light image quality enhancement system and method based on enhanced night scene modeling. The system includes: a sample data construction module, which generates enhanced low-light scene images based on an initial image dataset using a dual-channel hybrid generative network architecture and constructs an optimized training sample library; and a hybrid enhancement model, constructed based on an attention module and a probabilistic graphical model module. During the training phase, the hybrid enhancement model uses the optimized training sample library as input and employs a region-adaptive weighted loss function for parameter optimization. During the application phase, the optimized model receives the low-light image to be processed, estimates the illumination and noise distribution of the low-light image, and generates the enhanced image. This invention significantly improves the coverage of night scene training data and achieves adaptive enhancement of image features under low-light conditions, significantly improving the noise suppression effect in dark areas and the ability to restore image details.

An image processing apparatus acquires a first low-energy image and a first high-energy image captured in a state in which a grid for removing scattered rays is inserted between a radiation source and a radiation detector, and the radiation source is disposed at a first position at which an incidence direction of radiation is a normal direction with respect to the grid, acquires a second low-energy image and a second high-energy image captured in a state in which the grid retreats from between the radiation source and the radiation detector, and the radiation source is disposed at a second position, estimates a thickness of the subject from the first low-energy image and the first high-energy image, and generates a difference image indicating a difference between the second high-energy image and the second low-energy image from the second low-energy image and the second high-energy image based on the thickness.