41 results about "Facial reconstruction" patented technology

An implantable device for use in tissue and ligament repair comprising at least one knitted section and at least one single continuous fiber traversing the at least one knitted section, the at least one single continuous fiber forming a plurality of traverses extending through the at least one knitted section. The implantable device may comprise at least one single continuous silk fiber. The implantable device is suitable for use in a variety or reconstructive or support applications such as breast reconstruction, mastopexy, breast augmentation revision, breast augmentation support, standard breast augmentation, chest wall repair, organ support, body contouring, abdominoplasty, facial reconstruction, hernia repair, and pelvic floor repair.

Pre-surgical planning for cranial and facial reconstruction includes preparing a computer generated jaw or skull model for determining a locational position for a dental implant, a surgical bone implant to repair missing bone in the cranium, install ear prostheses, and / or install nose prostheses. The computer generated jaw or skull model is made from medical imagery and computer aided design. A surgical guide is prepared with oversize holes in registration with analogs for the dental or surgical bone implants to be inserted at the locational positions determined by a dentist or surgeon in the jaw or cranial skull model. The surgical guide is fitted atop each analog, and the surgical guide is bonded to the jaw or skull model at a predetermined angle of the analog in the jaw or skull. The surgical guide is removed from the model attached to the law or skull of a patient for accurate drilling during the dental or surgical procedure for insertion of the implants into the jaw or skull of the patient.

The invention discloses a computer-aided 3D facial reconstruction method which comprises the following steps: 1) a skull is scanned to acquire a 3D digital skull model; 2) the 3D digital skull model with caverns is carried out acquisition of skull caverns and insertion of discrete points in the cavern area, and then the caverns are filled by adopting triangulation of spatial polygon, finally, the least squares fit and the interpolation method of the radial basis function are adopted to smoothly optimize a curved surface for partial and overall optimization to acquire a complete digital skull model; 3) the facial feature points are acquired by a method of manually marking feature points and a calculation method of adding normal soft tissue thickness along the normal direction of the curved surface, and the discrete feature points are carried out interpolation of the radial basis function and triangulation to acquire a facial reconstruction rudiment of the skull; 4) the reconstructed facial rudiment is generated into the 3D human face model with a sense of reality by a binding texture mapping algorithm. The computer-aided 3D facial reconstruction method has the advantages of good rapidity, high accuracy and reliability.

An implantable device for use in tissue and ligament repair comprising at least one knitted section and at least one single continuous fiber traversing the at least one knitted section, the at least one single continuous fiber forming a plurality of traverses extending through the at least one knitted section. The implantable device may comprise at least one single continuous silk fiber. The implantable device is suitable for use in a variety or reconstructive or support applications such as breast reconstruction, mastopexy, breast augmentation revision, breast augmentation support, standard breast augmentation, chest wall repair, organ support, body contouring, abdominoplasty, facial reconstruction, hernia repair, and pelvic floor repair.

The present invention provides a functionally graded bioactive glass / ceramic composite structure or bioactive glass / ceramic / bioactive glass sandwich structure for use in such applications as damage resistant, ceramic dental implants, immediate tooth replacement, endodontic posts, orthopedic prostheses, orthopedic stems, bone substitutes, bone screws, plates, and anchors, nonunion fractures repair, alveolar ridge augmentation, missing small bone parts (e.g. fingers, toes, etc), maxilla facial reconstruction, spinal fusion, and scaffolds for bone regeneration, comprising a residual bioactive glass or glass-ceramic layer at all accessible surfaces, followed by an underlying graded glass-ceramic layer, and then an dense interior ceramic. The residual bioactive glass or glass-ceramic layer can be further transformed to a carbonate apatite (CHA) layer by immersing in calcifying solution or simulated body fluid (SBF) with electrolyte composition similar to that of serum. The interior ceramic preferably contains yttria-tetragonal zirconia polycrystal (Y-TZP) or ceria stabilized tetragonal zirconia polycrystal (Ce-TZP) or magnesia stabilized zirconia (Mg-PSZ) or calcia stabilized zirconia (Ca-PSZ) or alumina or zirconia-alumina composites. Further, the invention provides methods for making the same functionally graded bioactive glass / ceramic composite structure or graded bioactive glass / ceramic / bioactive glass sandwich structure.

The invention belongs to the fields of forensic anthropology and computer graphics and relates to a criminology-oriented computer-assisted facial reconstruction method for skulls of unknown body sources. The criminology-oriented computer-assisted facial reconstruction method mainly includes steps of 1 three-dimensional modeling of a skull of an unknown body source, 2 gender discrimination of the skull of the unknown body source, 3 dense point based facial soft tissue rule analysis, 4 dense point registration based skull facial reconstruction method, 5 principal component analysis based facial estimation of the skull of the unknown body source, 6 generating of investigated photos based on three-dimensional facial model. The criminology-oriented computer-assisted facial reconstruction method can fast achieve facial reconstruction for skulls of unknown body sources, and can predict the facial features of victims before their death for criminal case investigation.

The invention is applicable to the technical field of computer vision, and particularly relates to a three-dimensional human body reconstruction method and device, computer equipment and a storage medium.The three-dimensional human body reconstruction method comprises the steps of obtaining a human body image of a target object; extracting a face image and a body image in the human body image; utilizing the facial image to obtain facial parameters according to a facial parameter prediction model; based on the body image, obtaining body parameters by utilizing a body parameter prediction model;inputting the human body image into a gender classifier model to obtain a gender parameter; and obtaining a human body three-dimensional model of the target object through an SMPL-X model according to the face parameters, the body parameters and the gender parameters. Compared with an existing human body prediction model, the problem that face reconstruction is ignored based on a three-dimensional human body model can be solved.

The invention provides a facial reconstruction method based on a non-supervision automatic encoder. The main content of the facial reconstruction method based on a non-supervision automatic encoder includes a semantic code vector, a decoder based on a parameter model and a loss layer. The process of the facial reconstruction method based on a non-supervision automatic encoder includes the steps: scene description is given in a semantic code vector mode; the parameter decoder generates a composite image corresponding the face, and a reverse image is formed through standard reverse propagation, and then end-to-end training without supervision is realized, and the parameter decoder includes an image forming model, a lighting model, image formation and reverse propagation; and a loss function is defined by three items, and the loss layer includes dense luminosity calibration, sparse landmark alignment, statistical regularization and reverse propagation. The facial reconstruction method based on a non-supervision automatic encoder can encode the details of the face, such as posture, shape, expression, skin color and scene lighting, is more exquisite, does not need supervision and allows end-to-end learning. Compared with a network of synthesizing face data training, the network can be preferably popularized to real data.

A 3D facial reconstruction system includes a main color range camera, a plurality of auxiliary color cameras, a processor and a memory. The main color range camera is arranged at a front angle of a reference user to capture a main color image and a main depth map of the reference user. The plurality of auxiliary color cameras are arranged at a plurality of side angles of the reference user to capture a plurality of auxiliary color images of the reference user. The processor executes instructions stored in the memory to generate a 3D front angle image according to the main color image and the main depth map, generate 3D side angle images according to the 3D front angle image and the plurality of auxiliary color images, and train an artificial neural network model according to a training image, the 3D front angle image and 3D side angle images.

The invention is a three-dimensional face reconstruction method, which automatically reconstructs a three-dimensional face model from a single frontal face image, and proposes two schemes, the first one: offline generation of a human face deformation model; automatic detection of people in the input image by using Adaboost Face location; automatically locate keypoints on the face in the input image using an active appearance model; reconstruct the geometry of the 3D face based on the shape components of the face deformation model and the face keypoints on the image; use shape-independent texture as the target Image, use the texture component of the face deformation model to fit the face texture to obtain the complete face texture; get the reconstruction result after texture mapping. The difference between the second type and the first type is that after reconstructing the geometric shape of the 3D face, the face texture fitting is not performed, but the input image is directly used as the texture image to obtain the reconstruction result. Solution 1 of the present invention is suitable for application in the fields of film and television production, three-dimensional face recognition, etc., and solution 2 has a fast reconstruction speed.

The invention belongs to the technical field of face recognition, and particularly relates to a multi-style face feature point detection method based on a convolutional neural network. According to the invention, fine tuning training is carried out on a residual network (ResNet-152) by inputting multiple styles of face images, so that style discrimination features are obtained; style clustering isperformed on the original image by using K-means by using style discrimination features; a style-aggregated face image set is generated through a generative adversarial network; finally, the originalface image and the style aggregation face image are jointly used as input, and face feature point prediction is generated through a cascade strategy. According to the method, errors caused by multiple styles to face detection are reduced, the accuracy of face detection is improved, and the method can be applied to face recognition, head posture estimation, face reconstruction, 3D face reconstruction and the like.

A computer-implemented method for generating a three-dimensional model of an object. The method includes generating a coarse geometry mesh of the object; calculating an optimization for the coarse geometry mesh based on photometric consistency and surface consistency associated with the coarse geometry mesh; and refining the coarse geometry mesh with the optimization to generate the three-dimensional model for the object.

The invention discloses a calibration method for a virtual three-dimensional face reconstruction system, and the method comprises the steps: S1, solving a transformation relation between a world coordinate system and a CT three-dimensional coordinate system through employing a model coordinate system of a cylindrical die as the world coordinate system; S2, solving internal parameters of the monocular camera by using a checkerboard calibration board to obtain a transformation relationship between a camera coordinate system and a camera image coordinate system; s3, shooting a phantom at an initial point through a monocular camera, and solving a transformation relation between a world coordinate system and a camera image coordinate system; S4, according to the known coordinate transformationrelationship, finally obtaining the transformation relationship from the CT three-dimensional coordinate system to the camera image coordinate system; and S5, since the monocular camera is fixed on the CBCT, when the cantilever rotates, solving the coordinate transformation relation at any position. The method is used for realizing system calibration of the monocular camera and the CBCT, hardwareand data bases are laid for three-dimensional face reconstruction, and the problem that a binocular vision scanner is required to reconstruct a three-dimensional face in the prior art is solved.

The present invention provides a functionally graded bioactive glass / ceramic composite structure or bioactive glass / ceramic / bioactive glass sandwich structure for use in such applications as damage resistant, ceramic dental implants, immediate tooth replacement, endodontic posts, orthopedic prostheses, orthopedic stems, bone substitutes, bone screws, plates, and anchors, nonunion defects repair, alveolar ridge augmentation, missing small bone parts (e.g. fingers, toes, etc), maxilla facial reconstruction, spinal fusion, and scaffolds for bone regeneration, comprising a residual bioactive glass or glass-ceramic layer at all accessible surfaces, followed by an underlying graded glass-ceramic layer, and then an dense interior ceramic. Further, the invention provides methods for making the same structure.

The invention discloses a computer-aided 3D facial reconstruction method which comprises the following steps: 1) a skull is scanned to acquire a 3D digital skull model; 2) the 3D digital skull model with caverns is carried out acquisition of skull caverns and insertion of discrete points in the cavern area, and then the caverns are filled by adopting triangulation of spatial polygon, finally, theleast squares fit and the interpolation method of the radial basis function are adopted to smoothly optimize a curved surface for partial and overall optimization to acquire a complete digital skull model; 3) the facial feature points are acquired by a method of manually marking feature points and a calculation method of adding normal soft tissue thickness along the normal direction of the curvedsurface, and the discrete feature points are carried out interpolation of the radial basis function and triangulation to acquire a facial reconstruction rudiment of the skull; 4) the reconstructed facial rudiment is generated into the 3D human face model with a sense of reality by a binding texture mapping algorithm. The computer-aided 3D facial reconstruction method has the advantages of good rapidity, high accuracy and reliability.

A method of creating a 3-dimensional facial reconstruction of a user of a transit system includes detecting a user within a range of an image capture device positioned at a transit access point. A plurality of images of a first portion of the user's face are captured using the image capture device while the user passes through the range of the image capture device. A plurality of positions of the user may be detected as the user passes through the range of the image capture device. The plurality of images are combined with the plurality of positions and a relative angle and position of the user's face are calculated based on the combination of the plurality of images and the plurality of positions. A 3-dimensional model of the first portion of the user's face is generated based on the calculated relative angle and position and the 3-dimensional model is stored.

The invention discloses a high-fidelity face three-dimensional reconstruction method based on a multilevel deformation model. According to the method, a video image sequence is used as input data, camera parameters and camera loci are restored through detection and tracking of light stream feature points, extraction and matching of face feature points as well as camera calibration by utilizing a movement restoration structure technology, a face multilevel deformation model is proposed, and then a high-fidelity face three-dimensional model of a target face is obtained by texture mapping. According to the method, the face multilevel deformation model is proposed by combining the deformation model technology with the movement restoration structure technology, so that the reconstruction result highly similar to the target face can be achieved; meanwhile, the defect of surface noise appearing in the traditional movement restoration structure is overcome, and face details can be provided by utilizing the movement restoration structure; and the high-fidelity face model obtained by the reconstruction method is widely applied in the fields of face recognition, personalized customized games, virtual reality, security department and the like.

The invention discloses a three-dimensional facial reconstruction method based on multi-view cellphone selfie pictures. The three-dimensional facial reconstruction method includes automatically positioning mark points on selfie face images of a same person from n different angles; setting up a first energy function according to the mark points and solving a camera parameter Pk (k=1,....,N), wherein in the first energy function, I is pixel serial number, k is input image vision number, mi is the ith mark point, Xi is three-dimensional point coordinate corresponding to the ith mark point, and Pk is a projection transformation matrix from a three-dimensional point to the corresponding image; reconstructing a target function E=Edata+Ecolor+Esmooth according to the camera parameter, optimizing the target function and using a multi-tag image partition algorithm to solve the target function to obtain a three-dimensional facial model. By the three-dimensional facial reconstruction method, the accurate three-dimensional facial model can be reconstructed quickly by the cellphone selfie images.