50 results about "Nonrigid motion" patented technology

A method of analysing a sequence of images of a deformable object in non-rigid motion involves modeling the boundary using a non-rigid contour. A representation of movement of the contour through the sequence of images is calculated using a tracking space shape. The calculated movement representation is decomposed using an interpretational space shape that is different than the tracking space shape.

A semantic object tracking method tracks general semantic objects with multiple non-rigid motion, disconnected components and multiple colors throughout a vector image sequence. The method accurately tracks these general semantic objects by spatially segmenting image regions from a current frame and then classifying these regions as to which semantic object they originated from in the previous frame. To classify each region, the method perform a region based motion estimation between each spatially segmented region and the previous frame to computed the position of a predicted region in the previous frame. The method then classifies each region in the current frame as being part of a semantic object based on which semantic object in the previous frame contains the most overlapping points of the predicted region. Using this method, each region in the current image is tracked to one semantic object from the previous frame, with no gaps or overlaps. The method propagates few or no errors because it projects regions into a frame where the semantic object boundaries are previously computed rather than trying to project and adjust a boundary in a frame where the object's boundary is unknown.

Methods and apparatus for robust rigid and non-rigid motion tracking. An image, a next image, and a mask corresponding to an area in the image may be obtained. The area includes a plurality of points; each point indicates a location of the point in a position space and a color of the point in a color space. An iterative closest point algorithm may be applied that iteratively computes correspondences from a transformation and computes a new transformation from the correspondences. The algorithm tracks motion of the area in the image between the image and the next image. The algorithm matches points indicated by the mask to points in the next image in both position space and color space. An indication of an area in the next image that corresponds to the area in the image as tracked by the algorithm is generated.

The invention discloses a three-dimensional reconstruction method and system for combined optimization of the human body posture and the appearance model. The method comprises the following steps of performing depth map photographing on a human body to obtain a single depth image; converting the single depth image into a three-dimensional point cloud, and obtaining the three-dimensional point cloud, rebuilding model vertexes, and parameterizing matching point pairs among the human body model vertexes; according to the matching point pairs, building an energy function, and jointly solving non-rigid motion position transformation parameters and parameterization human body posture model parameters of each vertex on the rebuilt model; solving the energy function, and performing alignment on the rebuilt model and the three-dimensional point cloud according to the obtained result; updating and complementing the aligned model through the depth map to perform real-time human body dynamic three-dimensional rebuilding. The method can effectively improve the rebuilding real-time performance, robustness and accuracy and is high in expandability and simple and easy to implement.

The invention discloses a three-dimensional reconstruction method and device uniting rigid motion and non-rigid deformation. The method comprises the steps that photographing based on a depth camera is performed on a target object to obtain a single depth image; three-dimensional framework extraction is performed on a depth point cloud through a three-dimensional framework extraction algorithm; amatching point pair between a three-dimensional point cloud and each reconstruction model vertex is acquired; an energy function is established according to the matching point pairs and three-dimensional framework information, non-rigid motion position transformation parameters of each vertex on a reconstruction model are solved, and object framework parameters are optimized; GPU optimal solving is performed on the energy function to obtain non-rigid deformation of each surface vertex, and the reconstruction three-dimensional model in the previous frame is deformed according to the solving result, so that the deformed model is aligned to the three-dimensional point cloud in the current frame; and the updated model in the current frame is obtained to enter iteration of the next frame. Through the method, the instantaneity, robustness and accuracy of reconstruction can be effectively improved, extensibility is high, and the method is simple and easy to implement.

The invention discloses a skeleton tracking-based dynamic real-time three-dimensional reconstruction method and a skeleton tracking-based dynamic real-time three-dimensional reconstruction system. Themethod comprises the following steps: performing depth image shooting on a human body to acquire a single depth image; converting the single depth image into three-dimensional point cloud and acquiring a matched point pair between the three-dimensional point cloud and a reconstruction model vertex; establishing an energy function according to the matched points and jointly solving a non-rigid motion position conversion parameter and a human body skeleton motion parameter on each vertex on the reconstruction model; and solving the energy function, aligning the reconstruction model with the three-dimensional point cloud according to the solving result, and updating and complementing the aligned model by using the depth image to realize three-dimensional human body reconstruction. By the method, the human body can be shot by a depth image, so that the depth image is acquired to serve as system input information; furthermore, the function of performing real-time three-dimensional reconstruction is completed based on the depth image, and the method and the system are accurate and robust in solution and are simple and easy to realize.

The invention applies to the technical field of video processing and provides a video frame rate improvement method and device. The method comprises the steps of carrying out motion estimation on twoadjacent frames, thereby obtaining a motion vector of each pixel; segmenting a previous frame of image; clustering the motion vectors of all pixels, thereby obtaining a plurality of clustering centers; dividing the segmented areas into a plurality of areas according to the clustering centers, wherein the divided areas of which preset parameters are smaller than a first threshold are background areas, the divided areas of which the preset parameters are greater than or equal to the first threshold are motion areas, if the same object comprises the motion areas and the background areas and the preset parameters of the motion areas are smaller than a second threshold, the same object is a background object, otherwise, the same object is a motion object; finishing segmenting a foreground and abackground; carrying out image compensation; and inserting frames. According to a motion estimation algorithm based on sparse optical flow in the invention, on the basis of image segmentation, motionvector clustering is carried out on the pixels in the areas, the motion vectors of the foreground and the background are estimated, the motion compensation is realized, and the motion estimation accuracy of a nonrigid motion objet is improved.

The invention discloses a 3D synthesis fitting method and system. The method comprises the following steps: 1) obtaining two photos of a garment; 2) identifying a contour line and key nodes of the photos of the garment; 3) calculating the same fitting points of the two pictures for fitting, and generating a garment virtual three-dimensional model of the basic model; 4) carrying out depth image shooting on the human body to obtain a single depth image; 5) converting the single depth image into a three-dimensional point cloud, and obtaining matching point pairs between the three-dimensional point cloud and the vertex of the reconstruction model and between the three-dimensional point cloud and the vertex of the parameterized human body model; 6) establishing an energy function according to the matching point pair, and solving a non-rigid motion position transformation parameter and a parameterized human body posture model parameter of each vertex on the reconstruction model together, and7) solving the energy function, so that the 3D composite image generated based on the body data and the clothes data can be used for experiencing fitting conveniently and quickly.

The present invention discloses a method for generating an object space swept volume, relates to the fields of virtual simulation, computer aided manufacturing (CAM) and product lifecycle management (PLM), and in particular to a virtual model motion swept volume generation method. According to the method, a three-dimensional voxel method is adopted to obtain a swept volume, of an object, formed by motion transformation in a three-dimensional space, or called as an envelope volume, an envelope space, a swept space and a swept track. Compared with the current existing swept volume calculation method, the method provided by the present invention is applicable to rigid and nonrigid motion transformation of any complex three-dimensional shape, and can perform real-time three-dimensional display and surface reconstruction on a swept volume at each sampling moment during a motion transformation process. Besides, the method disclosed by the present invention further proposes accelerating a swept volume calculation process by adopting a massive parallel computing method, and the method is superior to the methods known in the art in the aspects of calculation efficiency, calculation accuracy and robustness of an algorithm.

The invention discloses a real-time reconstruction method and device for a hand and object interaction process, and the method comprises the following steps: carrying out the data segmentation of to-be-processed depth image data, obtaining a hand and object segmentation result, and obtaining gesture posture prediction data, and the hand and object segmentation result comprising object data and hand data; dividing the prediction data and the hand and object into constraint terms to optimize the unified energy function, so as to obtain a hand motion sequence and an object non-rigid motion sequence; and fusing the object data into the object model to obtain an object static model, and obtaining a real-time reconstruction result of the hand and object interaction process according to the handmotion sequence, the object non-rigid motion sequence and the object static model. The method can effectively solve the real-time reconstruction problem of hand and object interactive motion, and canobtain hand motion, object motion and object geometric models in real time.

The invention discloses a real-time human body dynamic three-dimensional reconstruction method and system driven by a clothes physical model, and the method comprises the steps: carrying out the photographing of a human body through a depth camera, and obtaining a color-depth image sequence; performing parameterized human body model matching, model surface non-rigid motion tracking and model updating based on depth fusion by using the input depth sequence; performing multi-view three-dimensional human body semantic segmentation based on a deep learning method by using the color image sequenceto obtain independent geometric models of different clothes, and forming a multi-layer human body model in combination with the parameterized human body model; according to the depth sequence input, performing human body motion tracking by using the double-layer human body surface to obtain corresponding human body posture information; conducting physical simulation on clothes movement according to human body movement, constructing depth fitting external force by combining input depth information, and restraining a clothes physical simulation result to be matched with depth input. The method is accurate and efficient in solution, and can realize human body dynamic three-dimensional reconstruction with clothes fine dynamic details.

The invention discloses a magnetic resonance imaging rectification method, device and equipment based on 3D shape and appearance measurement, and the method comprises the steps: collecting the shape and appearance information of a head part and a body part; obtaining the rigid and non-rigid movement information of a human body according to the shape and appearance information of the head part andthe body part; synchronously collecting the magnetic resonance data; and carrying out the movement rectification of human body imaging according to the rigid and non-rigid movement information of thehuman body through combining with the magnetic resonance imaging state. The method can achieve the precise measurement of the rigid and non-rigid movement of the human body according to the shape andappearance information of the head part and the body part, so as to achieve the movement rectification of human body imaging. The method is simpler in operation, can effectively speed up the imaging,improves the imaging quality, and improves the measurement precision.

The invention discloses a real-time dynamic human body three-dimensional reconstruction method based on an inward looking-around multi-RGBD camera, and the method comprises the following steps: S1, building a multi-RGBD camera group, calibrating and collecting data, and obtaining a high-precision model; S2, extracting an embedded node and parameterizing the embedded node; S3, binding embedded nodes to the 3D skeleton, solving motion parameters and optimizing the number of the parameters, and propagating the parameters to the embedded nodes; s4, solving the non-rigid motion; and S5, carrying out real-time mapping. The method is low in implementation cost, simple and convenient to build, high in automation degree and free of manual intervention under the condition of having no special requirements for wearing, action posture, amplitude and speed of a user in a daily scene, and a real-time dynamic high-definition human body three-dimensional model is obtained through a series of algorithms based on a GPU. The method can be widely applied to the fields of remote holographic communication, remote teaching, entertainment and the like.

The invention discloses a steady non-rigid motion reconstruction method, and relates to the field of three-dimensional reconstruction in computer vision, in particular to a steady non-rigid motion reconstruction method. By use of the method, the defects in the prior art that the value of an orthogonal discrete cosine base number K needs to be continuously debugged to obtain a reconstruction resultwhich approaches to a truth value to reduce in a true non-rigid reconstruction application so as to be difficult in use can be solved, statistics can be carried out to obtain a reconstruction resultthrough the calculation of a plurality of rectification bases on a premise that the orthogonal discrete cosine base number K does not need to be preset or debugged, and the applicability and the stability of a non-rigid reconstruction algorithm based on a trajectory base are enhanced.

The invention relates to the field of data compression, and discloses a compression method of a dynamic human body three-dimensional model sequence, electronic equipment and a medium, and the compression method comprises the following steps: dividing the three-dimensional model sequence into a plurality of model sequence segments, and selecting a first KF for each model sequence segment; encrypting the face grid of the first KF model to enable the density of the face grid to be greater than that of the body part grid; then collecting SED-nod for the face grid and the body part grid to form a complete SED-graph, wherein the distance between the face grid collection points is smaller than the distance between the body part grid collection points; performing blocked non-rigid motion solutionon the first KF model to realize non-rigid deformation in the front and rear frame directions; and keeping the texture coordinates of the triangular surface of the model in each model sequence segmentunchanged, and mapping the deformed model by using the original picture. According to the method, the data volume of the model sequence can be greatly compressed, the problem of serious jitter is solved, and the model quality is optimized.