119 results about "Shape reconstruction" patented technology

Simultaneous 2-D room shape reconstruction and self-localization is accomplished using no pre-established infrastructure. A mobile device with co-located microphone and loudspeaker is used to collect echoes reflected by the walls. The system uniquely recovers arbitrary 2-D convex room shape as well as the position of mobile device 10 by collecting and processing distances between three consecutive measurement points as well as acoustic echoes from the device. A practical algorithm for room shape reconstruction and self-localization in the presence of noise and higher order echoes is proposed. Experimental results are provided to demonstrate the effectiveness of the approach.

Reconstructing the shape of the surface of an object in greater than two dimensions is performed using a noise-tolerant reconstruction process and/or a multi-resolution reconstruction process. The noise-tolerant reconstruction process can be a Bayesian reconstruction process that adds noise information representing the noise distribution in optical image(s) of the object to surface gradient information estimated from the images to determine surface height information that defines the shape of the surface of the object in greater than two dimensions. In the multi-resolution reconstruction process, for each resolution of the image, the surface gradient information is estimated and the surface height information is calculated using the estimated surface gradient information. To obtain the final surface height map, the surface height information from each resolution is combined to reconstruct the shape of the surface of the object in greater than two dimensions. The multi-resolution reconstruction process can be used with the Bayesian reconstruction process or with another decomposition process, such as a wavelet decomposition process.

The invention discloses a three-dimensional human body model attitude and shape reconstruction method through a video sequence, and the method comprises the steps: 1), extracting two-dimensional jointpoints of a person in a video frame; 2), extracting facial feature points of the person in the video frame; 3), extracting a two-dimensional contour line of the person in the video frame; 4), estimating camera parameters, and generating a perspective matrix according to the camera parameters; 5), carrying out the optimization of the model posture and shape through an optimization method; 6), obtaining the edge points of the 3D human body model at the camera angle and the matching relationship between the edge point and the 2D contour line; 7), carrying out the re-optimization of the shape ofthe model through the optimization method so that the sum of the differences between the distances from the positions of the edge points of the three-dimensional model at the camera angle after projection to the positions of the two-dimensional contour points in the video frame is minimized. The method can avoid the posture turnover in the reconstruction process, and also can accurately reconstruct the posture of a head under the condition that the overall similarity of the model is guaranteed.

The invention discloses an intelligent visual defect detection system based on an AC magnetic field. The system comprises a probe, an auxiliary circuit and system detection software and uses a defect quantification and shape reconstruction algorithm. An excitation part of the probe adopts a double-U-shaped structural design and consists of a mangan zinc ferrite iron core and two sets of orthogonal current-carrying coils, a detection part adopts a two-dimensional array structure, and the array probe adopts a lifting-releasing type traveling mode. The hardware processing of detection signals comprises signal conditionings such as amplification, filtering, and the like and also introduces an original excitation signal as a reference signal to carry out phase sensitive detection and low-pass filtering on the detection signals. The signals are sent into a computer through an A/D acquisition card, then the detection software is used for carrying out digital filtering and correlation analysis on the signals to draw a magnetic induction intensity curve and a butterfly diagram in real time, and size quantification and three-dimensional shape inversion are realized through the defect quantification and the shape reconstruction algorithm. The intelligent visual defect detection system gives a full play of the advantages of the computer and greatly improves the intellectualized and visual levels of AC magnetic field detection.

A method for generating a three-dimensional model of a structure based on at least one two-dimensional image of the structure includes obtaining a general three-dimensional model of the structure; determining at least one image feature from the at least one two-dimensional image; determining an orientation of the general three-dimensional model of the structure relative to the at least one two-dimensional image of the structure so that at least one image feature of a two-dimensional projection of the three-dimensional model match or at least approximate the at least one two-dimensional image feature; and after determining the orientation of the general three-dimensional model, morphing a form or shape of the general three-dimensional model to fit the at least one two-dimensional image.

The invention provides a shape detection device and method based on a spiral FBG (fiber bragg grating) sensor array, and the device comprises the spiral FBG sensor array, an FBG demodulator, data collection and shape reconstruction equipment, and display equipment. The device does not need other peripheral auxiliary equipment, is not affected by electromagnetic interference, is good in medical compatibility, does not emit rays, and can achieve the long-distance remote monitoring. Through the spiral configuration of the FBG sensor array, the device can achieve the multi-point deformation detection of a single optical fiber, and forms a quasi-distributed detection system. Through the packaging of the optical fiber on a nickel-titanium alloy filament, the device protects a grating point from being worn, is strong in anti-interference capability, and enlarges the detection range. The device can obtain the shape of a flexible robot in real time, and is high in real-time response. Meanwhile, the device detects the curvature and torsion, is simple in detection method, can be used for the shape sensing detection in a gastroscope, colonoscope and a flexible/soft robot, and plays an important role in the flexible robots in the fields of dibaster assistance, medical rehabilitation and national defense security.

A high-density shape reconstruction is conducted in measuring animal bodies as well. An image processing system has a projection device, an imaging device, and an image processing apparatus connected to the projection device and the imaging device, wherein the projection device projects a projected pattern to an observation target, the imaging device captures the projected pattern, and the image processing apparatus performs shape reconstruction based on an input image including the projected pattern. The image processing apparatus includes a unit for fetching the input image captured by the imaging device and performing line detection for the projected pattern projected by the projection device, wherein the projected pattern is a grid pattern formed of wave lines; and a unit for performing shape reconstruction by associating intersection points of vertical and horizontal lines extracted by the line detection with the projected pattern.

The invention discloses an ecological restoration method for a municipal eutrophicated river. The method comprises the following steps: arranging a barring and controlling water level system at a barring and controlling water gate of the river; in the main stem of the river, piling cubic meters of earth obtained after desilting to form an along-river gentle slope and a river-center island, wherein a bank slope ratio is 1: 2.5 to 1: 5, and a shoal water zone and a deep and broad water zone are successively formed from a dam of the river to the center of the river; carrying out rock mound type and jack-like concrete block type bottom shape reconstruction on the slope surface of the along-river gentle slope; constructing embankment-zone aquatic plant zones at the river-center island and the along-river gentle slope having undergone bottom shape reconstruction and constructing a plant floating bed bio-zone in an along-river zone; and releasing filter-feeding and omnivore fish, shellfish and shrimps. With the restoration method provided by the invention, the water quality of the river is improved from class IV and V to class III or a higher class; biodiversity of a water area is increase by more than 2 times; the river has better capability in smooth regulation of water storage and flood discharge; and a water system has the further improved functions of underground water supplement, carbon immobilization, oxygen release, climate adjustment, water conservation, etc.

A 3-dimensional (3D) whole shape reconstruction apparatus using a depth image and a color image and a 3D whole shape reconstruction method are provided. The 3D whole shape reconstruction apparatus may include an information generation unit to generate shape information of 3D portions using a depth image and a color image, and a shape reconstruction unit to reconstruct a 3D whole shape of a user by matching the shape information of 3D portions.

The invention discloses a sub-surface defect shape reconstruction method for thermal imaging detection. The sub-surface defect shape reconstruction method consists of a thermal response signal acquisition process, a process of solving a phase difference between a defective region and a non-defective region, and a process of reconstructing a defect shape by adopting an envelope line. The method comprises the following steps: performing linear scanning on a test piece by adopting a linear thermal source; then performing Fourier analysis on data at a collected heating source position; solving corresponding phase differences between other position and non-defective positions; reversing the depths of defects according to the phase differences; then, making an envelope line according to scanning results of position lines, namely, solved depths; finally, estimating the shapes of the defects according to the envelope line. By adopting the sub-surface defect shape reconstruction method, the shapes of irregular defects can be estimated and reconstructed, quantitative assessment can be performed on the defects, and the problem on the aspect of quantitative analysis of the defects of the type during surface excitation is solved.

The invention discloses a method for reconstructing two-dimensional structure of paper cellulose fiber based on image processing, which relates to the technical field of fiber structure shape reconstruction, adopts an SEM image for the following treatments of binarization, morphology improvement, skeleton and edge line extraction, node extraction and replacement of straight line with curve, and finally obtains a paper cellulose fiber two-dimensional structure model, wherein the binarization adopts a more accurate binarization algorithm combining the double threshold with the local threshold; the morphology improvement adopts the repair algorithms such as expansion, erosion, opening and closing calculation; the replacement of straight line with curve adopts an algorithm for recognizing the curve node pairs able to be replaced by straight line through determining whether the nodes are connected or not. With the method of the invention, the problem that an existing in the currently available paper cellulose structure model differs greatly with an actual fiber microstructure or the problem that the model parameters are excessively complex can be resolved. The reconstructed structure model can be applied to the structure finite element simulated calculation of a plurality of cellulose application fields.

The invention discloses a method of acquiring a three-dimensional foot shape by using a foot shape video and sensor data acquired by a smart phone. The smart phone provided with an IMU sensor is coiled on a naked foot to shoot the foot shape video and corresponding IMU data at 360degrees, and by establishing a factor diagram, a video camera attitude, a three-dimensional point cloud coordinate, the IMU data, a video contour, and other various acquired data are used as factors, and then by defining constraint error equations among the factors and solving the equations, the parameters of the video camera are acquired, and are introduced in a reference model for foot shape reconstruction. The point cloud distribution, the normal vector, the surface curvature, and other information of the reference model are fully used to guide deformation of a reconstructed foot shape, and then under the condition of the reconstructed foot shape being not deviated from a reconstruction point cloud, the reconstructed foot shape is close to a real foot shape as much as possible, and interferences of noise points are reduced, and therefore a process of acquiring a corresponding foot shape three-dimensional grid model conveniently is realized. Acquisition costs of foot shape data are reduced, and accuracy and robustness of parameter calculation are improved.

Shape measurement of a specular object even in the presence of multiple intra-object reflections such as those at concave regions of the object. Silhouettes of the object are extracted, by positioning the object between a camera and a background. A visual hull of the object is reconstructed based on the extracted silhouettes, such as by image capture of shadows of the object projected onto a screen, and image capture of reflections by the surface of the object of coded patterns onto the screen. The visual hull is used to distinguish between direct (single) reflections of the coded patterns at the surface of the object and multiple reflections. Only the direct (single) reflections are used to triangulate camera rays and light rays onto the surface of the object, with multiple reflections being excluded. The 3D surface shape may be derived by voxel carving of the visual hull, in which voxels along the light path of direct reflections are eliminated. For surface reconstruction of heterogeneous objects, which exhibit both diffuse and specular reflectivity, variations in the polarization state of polarized light may be used to separate between a diffuse component of reflection and a specular component.

The invention relates to a structure optimization method for a low frequency electromagnetic sensor based on a genetic algorithm. The method is suitable for the structure design of a COMSOL analog low frequency electromagnetic sensor model and the shape reconstruction for defect detecting and belongs to the field of nondestructive detection. The method comprises the following steps: on the basis of simplifying the COMSOL analog low frequency electromagnetic sensor model, parameterizing an optimization model of the COMSOL analog low frequency electromagnetic sensor and defining the reading paths for different variables; setting a genetic optimized fitness function and main parameters including an algorithm running parameter and a control parameter; compiling a dynamic link function, calling for the COMSOL model by MATLAB and constructing a channel for mutually transferring data; calling a COMSOL genetic algorithm for optimizing the parameters of the low frequency electromagnetic sensor model, and while acquiring the fitness function meeting the convergence criterion, acquiring an optimized result, namely, the optimized structure parameter of the low frequency electromagnetic sensor. According to the method provided by the invention, the limitation of the COMSOL single assignment operation is broken through and the intelligent optimization of the COMSOL model parameters is realized.

The invention discloses an object shape reconstruction method based on a fiber Bragg grating. The object shape reconstruction method based on the fiber Bragg grating comprises the following steps: (1)when the shape of an object to be measured changes, the center wavelength of the fiber Bragg grating is measured through a spectrum analyzer, and a wavelength drift measured by the spectrum analyzeris converted into a strain value; (2) the strain value is converted into a discrete curvature value; (4) the discrete curvature value of each sensing point is made to be continuous according to the space curve theory and spline interpolation theory; (5) the continuous bending curvature is substituted into the Frenet-serret equation; and (6) after a tangent vector is obtained, the indefinite integration is performed to obtain the curve shape of the object to be measured. The measurement accuracy of the object shape reconstruction method and system based on the fiber Bragg grating is improved; the object shape reconstruction method and system based on the fiber Bragg grating is suitable for measurement under the circumstance that the distance between adjacent fiber Bragg grating sensors is relatively long; and the object shape reconstruction method based on the fiber Bragg grating can save the number of fiber Bragg grating sensors needed to increase the measurement accuracy.

The invention relates to a laser tracker-based mobile detection robot large component shape reconstruction method. The method comprises the following steps: (1) constructing different coordinate systems based on a laser tracker; under a laser tracker coordinate system, a laser tracker is adopted for measurement, so that an omnidirectional mobile platform coordinate system, a reference coordinate system and a vision measurement system coordinate system are constructed; (2) carrying out spatial point testability check on the model; (3) carrying out model-based spatial point automatic measurement; (4) acquiring measurement point cloud data; and (5) carrying out shape matching evaluation so as to complete shape reconstruction. According to the invention, repeated measurement is reduced, a large amount of manpower participates in the measurement process, the measurement and evaluation efficiency is improved, and the personnel safety is ensured. Meanwhile, a physical mobile detection robot system is controlled in a virtual environment, and the process of controlling reality with virtuality is achieved through disappearance of position deviation of existing functions of the laser tracker.

The invention belongs to the technical field of image processing and mode recognition, particularly relates to a scene-adaptive fine three-dimensional face reconstruction method and system and electronic equipment, and aims to solve the problems of strong model feeling and poor generalization of a reconstruction result of existing three-dimensional face reconstruction. The method comprises the following steps: augmenting face shapes of a training set based on a 3DMM and a graphical imaging model to obtain a plurality of pieces of three-dimensional face data and corresponding images thereof; fitting a three-dimensional variable model for the image corresponding to the three-dimensional face data as an initial shape, and performing virtual multi-view generation based on the image corresponding to the three-dimensional face data and the initial shape to obtain a multi-view image; inputting the multi-view image into a many-to-one funnel network, performing optimization through a loss function with consistent vision to obtain a refined three-dimensional face shape. According to the method, the three aspects of training data construction, model design and scene self-adaption are improved, and the robustness of the model in an unconstrained scene is improved while fine shape reconstruction is achieved.

The invention discloses an optical fiber shape reconstruction method based on a Beta frame. The method comprises the following steps: firstly, respectively carrying out bending-free state measurementand bending state measurement on a to-be-measured optical fiber by utilizing a distributed three-dimensional shape sensing system based on an optical frequency domain reflectometer (OFDR), and carrying out cross-correlation demodulation on two groups of signals obtained by measuring whether bending exists or not to obtain a frequency spectrum offset of the whole optical fiber; solving strain values of all positions of the optical fiber by using the spectrum offset, and solving the curvature and the bending angle of the optical fiber by using the relationship between the strain and the curvature and the bending angle; substituting the curvature and the bending angle of the optical fiber into a differential equation of a Beta standard frame to solve the Beta standard frame of each point on the optical fiber; and finally, carrying out tangent vector integration on the curve in the Beta frame to obtain the shape of the optical fiber. According to the method, good curve reconstruction performance can be obtained, and especially when turning point exists in optical fiber bending, reconstruction precision can be obviously improved.

The invention discloses a three-dimensional face modeling method based on a double-tributary network, and the method comprises the following steps: 1) constructing a face shape reconstruction tributary based on an auto-encoder structure, and obtaining an identity space diagram and an expression space diagram; 2) respectively expressing an identity attribute component and an expression attribute component by utilizing the identity space diagram and the expression space diagram; 3) constructing a facial texture reconstruction branch based on a semantic region to obtain a facial texture map withhigh truth; and 4) constructing a fusion module: correspondingly combining the reconstructed face shape model and the reconstructed face texture map according to a predefined three-dimensional vertextopological relation to obtain a final reconstructed three-dimensional face model. According to the invention, decoupling learning is carried out on the identity and expression attributes of the humanface, and processing of the face shape and the face texture is carried out by using the double-tributary network, so that accurate three-dimensional human face reconstruction with large-amplitude expressions is achieved.

In target shape reconstruction, in order to determine efficiently and quickly the profile of complex targets on a substrate, the various degrees of freedom or variable parameters of the various shapes of which a single profile is made up can be reduced by linking together the variable parameters using simple formulae or by approximating the shape of the overall profile such that it takes in to account the various shapes making up that profile. Fewer parameters gives rise to fewer iterations of calculations on those parameters, which increases the speed of profile reconstruction.

A method of multi-view deblurring for 3-dimensional (3D) shape reconstruction includes: receiving images captured by multiple synchronized cameras at multiple viewpoints; performing iteratively estimation of depth map, latent image, and 3D motion at each viewpoint for the received images; determining whether image deblurring at each viewpoint is completed; and performing 3D reconstruction based on final depth maps and latent images at each viewpoint. Accordingly, it is possible to achieve accurate deblurring and 3D reconstruction even from any motion blurred images.