CN108151712B - Human body three-dimensional modeling and measuring method and system - Google Patents
Human body three-dimensional modeling and measuring method and system Download PDFInfo
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- CN108151712B CN108151712B CN201711111048.XA CN201711111048A CN108151712B CN 108151712 B CN108151712 B CN 108151712B CN 201711111048 A CN201711111048 A CN 201711111048A CN 108151712 B CN108151712 B CN 108151712B
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- G—PHYSICS
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- A61B5/1079—Measuring physical dimensions, e.g. size of the entire body or parts thereof using optical or photographic means
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Abstract
The invention discloses a human body three-dimensional modeling and measuring method and a system, wherein the method comprises the following steps: acquiring a target human body depth map through a depth camera; calculating a point corresponding to each pixel in the target human body depth map to obtain a point cloud; matching every two adjacent frames of point clouds to perform point cloud optimization to obtain a global point cloud; solving the global point cloud to obtain a target character model; and acquiring a preset height horizontal plane, and measuring the target character model by calculating the girth of the target character model at the preset height horizontal plane to obtain a measured value of the target character model.
Description
Technical Field
The invention relates to the technical field of three-dimensional modeling and measurement, in particular to a human body three-dimensional modeling and measurement method and system.
Background
Image-based modeling is an extremely active area of research in the current computer graphics world, and has many unique advantages over traditional geometry-based modeling, primarily in that image-based modeling and rendering techniques can provide humans with the most natural way to achieve photorealism.
Three-dimensional modeling refers to the establishment of mathematical models suitable for computer representation and processing of three-dimensional objects, is the basis for processing, operation and analysis of the properties of the three-dimensional objects in a computer environment, and is also a key technology for establishing virtual reality expressing an objective world in a computer.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a human body three-dimensional modeling and measuring method and system;
the invention provides a human body three-dimensional modeling and measuring method, which comprises the following steps:
s1, acquiring a target human body depth map through a depth camera;
s2, calculating a point corresponding to each pixel in the target human body depth map to obtain a point cloud;
s3, matching every two adjacent frames of point clouds to perform point cloud optimization to obtain a global point cloud;
s4, solving the global point cloud to obtain a target character model;
and S5, acquiring a preset height level, and measuring the target character model by calculating the girth of the target character model at the preset height level to obtain a measured value of the target character model.
Preferably, step S3 specifically includes:
and (3) optimizing the point cloud by minimizing the rigid motion difference between the point cloud of the previous frame and the point cloud of the next frame through a least square method, and matching every two adjacent frames of point clouds to obtain the global point cloud.
Preferably, step S4 specifically includes:
and solving each point cloud in the global point cloud through a Poisson equation, wherein the position with the gradient change value larger than a preset threshold value in the solving process is the surface of the target person, and constructing a target person model through the obtained surface of the target person.
Preferably, step S5 specifically includes:
s51, acquiring a preset height horizontal plane, wherein the preset height horizontal plane is a horizontal plane taking the preset height as a z-axis coordinate in a three-dimensional coordinate system taking a sole tangent plane of the target character model as an xy plane and the height of the target character model as a z-axis;
s52, obtaining a half edge intersected with H in the target character model, and removing a reverse edge of the half edge to obtain a reserved set;
s53, acquiring a half A edge in the reserved set, searching the front side and the rear side of the reverse edge of the A edge to obtain adjacent truncated edges, storing the coordinates of the truncation points of the adjacent truncated edges, and deleting the reverse edge of the newly added truncated edge to obtain the girth;
s54, executing S52 and S53 operations on all the halves of the reserved set to obtain the measured value of the target character model.
Preferably, in step S52, the half is a derived half of one point;
preferably, in step S53, the front edge is an edge of the patch that points to the edge; the trailing edge is the edge on the patch that is pointed to by this edge.
A human body three-dimensional modeling and measuring system, comprising:
the depth map acquisition module is used for acquiring a target human body depth map through a depth camera;
the point cloud computing module is used for computing a point corresponding to each pixel in the target human body depth map to obtain a point cloud;
the point cloud optimization module is used for matching two adjacent frames of point clouds pairwise to perform point cloud optimization to obtain a global point cloud;
the model construction module is used for solving the global point cloud to obtain a target character model;
and the model measurement module is used for acquiring a preset height horizontal plane, and measuring the target character model by calculating the girth of the target character model at the preset height horizontal plane to obtain a measured value of the target character model.
Preferably, the point cloud optimization module is specifically configured to:
and (3) optimizing the point cloud by minimizing the rigid motion difference between the point cloud of the previous frame and the point cloud of the next frame through a least square method, and matching every two adjacent frames of point clouds to obtain the global point cloud.
Preferably, the model building module is specifically configured to:
and solving each point cloud in the global point cloud through a Poisson equation, wherein the position with the gradient change value larger than a preset threshold value in the solving process is the surface of the target person, and constructing a target person model through the obtained surface of the target person.
Preferably, the model measurement module comprises an acquisition subunit, a reservation set establishing subunit and a girth calculation subunit;
the acquisition subunit is used for acquiring a preset height horizontal plane, and the preset height horizontal plane is a horizontal plane taking the preset height as a z-axis coordinate in a three-dimensional coordinate system taking a sole tangent plane of the target character model as an xy plane and the height of the target character model as a z-axis;
a reserved set establishing subunit, configured to obtain a half of the target character model that intersects with H, and remove a reverse edge of the half to obtain a reserved set;
and the girth calculation subunit is used for acquiring a half A edge in the retention set, searching the front side and the rear side of the reverse edge of the A edge to obtain adjacent truncated edges, storing the coordinates of the truncation points of the adjacent truncated edges, deleting the reverse edge of the newly added truncated edge to obtain the girth, acquiring the other half pair, and repeatedly searching until all the half edges in the retention set are searched to obtain the measured value of the target character model.
Preferably, the reserved set creating subunit is specifically configured to: the half is a derived half of one point;
preferably, the girth calculation subunit is specifically configured to: the front edge is an edge pointing to the edge on the dough sheet; the trailing edge is the edge on the patch that is pointed to by this edge.
The method comprises the steps of obtaining a target human body depth map through a depth camera, calculating points corresponding to pixels of the target human body depth map to obtain point clouds, matching two adjacent frames of point clouds in pairs to perform point cloud optimization to obtain global point clouds, solving the global point clouds to obtain a target character model, obtaining a preset height horizontal plane, measuring the target character model through calculating the girth of the target character model at the preset height horizontal plane to obtain a measured value of the target character model, thus performing three-dimensional modeling and data measurement on a human body, performing multi-angle shooting on the human body by using the depth camera, calculating the human body three-dimensional model through the shot video/image, and measuring the model to obtain the girth of the human body model at any height, and completing complex three-dimensional modeling and measurement of the human body through low-cost depth map acquisition.
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FIG. 1 is a schematic flow chart of a human body three-dimensional modeling and measuring method according to the present invention;
fig. 2 is a schematic block diagram of a human body three-dimensional modeling and measuring system according to the present invention.
Detailed Description
Referring to fig. 1, the invention provides a human body three-dimensional modeling and measuring method, which comprises the following steps:
and step S1, acquiring a target human body depth map through the depth camera.
In a specific scheme, the depth camera is a camera capable of measuring the depth of a corresponding point of each pixel in a picture, namely the distance from the point to the optical center of the camera, while taking a normal picture.
Step S2, calculating a point corresponding to each pixel in the target human body depth map to obtain a point cloud;
in a specific scheme, the position of a point in a target human body depth map provides an azimuth angle of the point, and the depth provides a distance of the point, so that coordinates of the point are restored.
Step S3, performing point cloud optimization on two adjacent frames of point clouds to obtain global point clouds, which specifically comprises the following steps: and (3) optimizing the point cloud by minimizing the rigid motion difference between the point cloud of the previous frame and the point cloud of the next frame through a least square method, and matching every two adjacent frames of point clouds to obtain the global point cloud.
In the specific scheme, the cameras between two adjacent frames are set to move through a rigid body, namely a rotation and a translation, theoretically, the point clouds obtained by the two frames should have a corresponding rotation and translation difference, and the optimization problem is solved by using a least square method, so that the difference between the point cloud obtained by the previous frame and the point cloud obtained by the next frame is minimum after the point cloud obtained by the previous frame is transformed, the optimized point cloud is obtained, and the point clouds of the two adjacent frames are matched pairwise to obtain the global point cloud.
Step S4, solving the global point cloud to obtain a target character model, specifically including: and solving each point cloud in the global point cloud through a Poisson equation, wherein the position with the gradient change value larger than a preset threshold value in the solving process is the surface of the target person, and constructing a target person model through the obtained surface of the target person.
In the specific scheme, input data is set as a directed point set S, each point records the coordinate and the normal direction of the point set S, the indication function of the model is a continuous function, 1 is taken inside a target person, 0 is taken outside the target person, so that the target person has a trivial gradient in most cases, and the position with the gradient change value larger than a preset threshold value is the surface of the target person.
Step S5, obtaining a preset height level, measuring the target character model by calculating the girth of the target character model at the preset height level, and obtaining a measured value of the target character model, specifically including:
s51, acquiring a preset height horizontal plane, wherein the preset height horizontal plane is a horizontal plane taking the preset height as a z-axis coordinate in a three-dimensional coordinate system taking a sole tangent plane of the target character model as an xy plane and the height of the target character model as a z-axis;
s52, obtaining a half edge intersecting with H in the target character model, and removing a reverse edge of the half edge to obtain a reserved set, wherein the half edge is a derived half edge of one point;
s53, acquiring a half A edge in the reserved set, searching the front edge and the back edge of the reverse edge of the A edge to obtain adjacent truncated edges, storing the coordinates of the truncation points of the adjacent truncated edges, and deleting the reverse edge of the newly added truncated edge to obtain the girth, wherein the front edge is the edge pointing to the edge on the dough sheet, and the back edge is the edge pointing to the edge on the dough sheet by the edge;
s54, executing S52 and S53 operations on all the halves of the reserved set to obtain the measured value of the target character model.
In a specific scheme, the measurement of the target character model is realized by a half-edge data structure, namely, an edge in a normal mesh is divided into two reciprocal directed edges to describe, and for each triangular patch, the three edges forming the patch are connected end to end. Thus, as long as the information of a geometric element (point, half, triangular patch) is known, all the information in that part can be derived from it;
a half-edge data structure geometry comprising:
points describing, for each vertex, the three-dimensional coordinates, the normal, and a derived half of the point; half side: for each half, describing the point to which the half points; opposite side: the half opposite to the half; abutment surface: a triangular patch with the half as a boundary; the front side: an edge on the face pointing to the edge; then: the edge on the face pointed to by this edge. Triangular patch: describing any adjacent edge for the triangular patch;
the search algorithm comprises the following steps: the vertex V- > adjacent side A- > reverse side B- > rear C of B of A, wherein C is the next one next to A in the adjacent sides of V, all the adjacent sides can be obtained through the cyclic traversal, in the process, all the adjacent points of the point are obtained incidentally, and the degree of the point can also be obtained;
starting point of the edge: although the edges only describe the end point, but the starting point is readily available, the reverse edge of the edge A- > A B- > B end point V, where V is the starting point of the edge A;
three sides that make up a face: although only one edge is described, the edge describes the front and back edges, i.e., the other two edges that form the triangular patch, so that the patch is uniquely identified;
adjacent surface of the face: the vertices and sides forming the surface can be obtained from the surface, the sides diverged from each vertex form the adjacent surfaces of the surface, and the surfaces on which the reverse sides of each side are located are the three adjacent surfaces of the surface.
Referring to fig. 2, the present invention provides a human body three-dimensional modeling and measuring system, which includes:
and the depth map acquisition module is used for acquiring a target human body depth map through the depth camera.
In a specific scheme, the depth camera is a camera capable of measuring the depth of a corresponding point of each pixel in a picture, namely the distance from the point to the optical center of the camera, while taking a normal picture.
And the point cloud computing module is used for computing a point corresponding to each pixel in the target human body depth map to obtain a point cloud.
In a specific scheme, the position of a point in a target human body depth map provides an azimuth angle of the point, and the depth provides a distance of the point, so that coordinates of the point are restored.
The point cloud optimization module is used for performing point cloud optimization on pairwise matching of two adjacent frames of point clouds to obtain global point clouds, and is specifically used for: and (3) optimizing the point cloud by minimizing the rigid motion difference between the point cloud of the previous frame and the point cloud of the next frame through a least square method, and matching every two adjacent frames of point clouds to obtain the global point cloud.
In the specific scheme, the cameras between two adjacent frames are set to move through a rigid body, namely a rotation and a translation, theoretically, the point clouds obtained by the two frames should have a corresponding rotation and translation difference, and the optimization problem is solved by using a least square method, so that the difference between the point cloud obtained by the previous frame and the point cloud obtained by the next frame is minimum after the point cloud obtained by the previous frame is transformed, the optimized point cloud is obtained, and the point clouds of the two adjacent frames are matched pairwise to obtain the global point cloud.
The model building module is used for solving the global point cloud to obtain a target character model, and is specifically used for: and solving each point cloud in the global point cloud through a Poisson equation, wherein the position with the gradient change value larger than a preset threshold value in the solving process is the surface of the target person, and constructing a target person model through the obtained surface of the target person.
In the specific scheme, input data is set as a directed point set S, each point records the coordinate and the normal direction of the point set S, the indication function of the model is a continuous function, 1 is taken inside a target person, 0 is taken outside the target person, so that the target person has a trivial gradient in most cases, and the position with the gradient change value larger than a preset threshold value is the surface of the target person.
The model measurement module is used for acquiring a preset height level and measuring a target character model by calculating the girth of the target character model at the preset height level to obtain a target character model measurement value, and comprises an acquisition subunit, a reservation set establishment subunit and a girth calculation subunit;
the acquisition subunit is used for acquiring a preset height horizontal plane, and the preset height horizontal plane is a horizontal plane taking the preset height as a z-axis coordinate in a three-dimensional coordinate system taking a sole tangent plane of the target character model as an xy plane and the height of the target character model as a z-axis;
a reserved set establishing subunit, configured to obtain a half of the target character model that intersects with H, and remove a reverse edge of the half to obtain a reserved set, where the half is a derived half of one point;
and the girth calculation subunit is used for acquiring a half edge A in the retention set, searching the front edge and the back edge of the reverse edge of the edge A to obtain adjacent truncated edges, storing the coordinates of the truncation points of the adjacent truncated edges, deleting the reverse edge of the newly added truncated edge to obtain the girth, acquiring the other half pair, and repeatedly searching until all the half edges in the retention set are searched to obtain the target character model measured value, wherein the front edge is the edge pointing to the edge on the surface patch, and the back edge is the edge pointing to the edge on the surface patch.
In a specific scheme, the measurement of the target character model is realized by a half-edge data structure, namely, an edge in a normal mesh is divided into two reciprocal directed edges to describe, and for each triangular patch, the three edges forming the patch are connected end to end. Thus, as long as the information of a geometric element (point, half, triangular patch) is known, all the information in that part can be derived from it;
a half-edge data structure geometry comprising:
points describing, for each vertex, the three-dimensional coordinates, the normal, and a derived half of the point; half side: for each half, describing the point to which the half points; opposite side: the half opposite to the half; abutment surface: a triangular patch with the half as a boundary; the front side: an edge on the face pointing to the edge; then: the edge on the face pointed to by this edge. Triangular patch: describing any adjacent edge for the triangular patch;
the search algorithm comprises the following steps: the vertex V- > adjacent side A- > reverse side B- > rear C of B of A, wherein C is the next one next to A in the adjacent sides of V, all the adjacent sides can be obtained through the cyclic traversal, in the process, all the adjacent points of the point are obtained incidentally, and the degree of the point can also be obtained;
starting point of the edge: although the edges only describe the end point, but the starting point is readily available, the reverse edge of the edge A- > A B- > B end point V, where V is the starting point of the edge A;
three sides that make up a face: although only one edge is described, the edge describes the front and back edges, i.e., the other two edges that form the triangular patch, so that the patch is uniquely identified;
adjacent surface of the face: the vertices and sides forming the surface can be obtained from the surface, the sides diverged from each vertex form the adjacent surfaces of the surface, and the surfaces on which the reverse sides of each side are located are the three adjacent surfaces of the surface.
In the embodiment, a target human body depth map is obtained through a depth camera, points corresponding to pixels of the target human body depth map are calculated, point clouds are obtained, two adjacent frames of point clouds are matched in pairs to perform point cloud optimization, global point clouds are obtained, the global point clouds are solved to obtain a target character model, a preset height horizontal plane is obtained, the target character model is measured by calculating the girth of the target character model at the preset height horizontal plane to obtain a target character model measured value, therefore, a human body is subjected to three-dimensional modeling and data measurement, the human body is shot at multiple angles through the depth camera, the human body three-dimensional model is calculated through the shot video/image, the model is measured, the girth of the human body model at any height is obtained, and complicated human body three-dimensional modeling and measurement are completed through low-cost depth map collection.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (10)
1. A human body three-dimensional modeling and measuring method is characterized by comprising the following steps:
s1, acquiring a target human body depth map through a depth camera;
s2, calculating a point corresponding to each pixel in the target human body depth map to obtain a point cloud;
s3, matching every two adjacent frames of point clouds to perform point cloud optimization to obtain a global point cloud;
s4, solving the global point cloud to obtain a target character model;
s5, obtaining a preset height level, and measuring the target character model by calculating the girth of the target character model at the preset height level to obtain a measured value of the target character model;
step S5, specifically including:
s51, acquiring a preset height horizontal plane, wherein the preset height horizontal plane is a horizontal plane taking the preset height as a z-axis coordinate in a three-dimensional coordinate system taking a sole tangent plane of the target character model as an xy plane and the height of the target character model as a z-axis;
s52, obtaining a half edge intersected with H in the target character model, and removing a reverse edge of the half edge to obtain a reserved set;
s53, acquiring a half A edge in the reserved set, searching the front side and the rear side of the reverse edge of the A edge to obtain adjacent truncated edges, storing the coordinates of the truncation points of the adjacent truncated edges, and deleting the reverse edge of the newly added truncated edge to obtain the girth;
s54, executing S52 and S53 operations on all the halves of the reserved set to obtain the measured value of the target character model.
2. The human body three-dimensional modeling and measuring method according to claim 1, wherein the step S3 specifically includes:
and (3) optimizing the point cloud by minimizing the rigid motion difference between the point cloud of the previous frame and the point cloud of the next frame through a least square method, and matching every two adjacent frames of point clouds to obtain the global point cloud.
3. The human body three-dimensional modeling and measuring method according to claim 1, wherein the step S4 specifically includes:
and solving each point cloud in the global point cloud through a Poisson equation, wherein the position with the gradient change value larger than a preset threshold value in the solving process is the surface of the target person, and constructing a target person model through the obtained surface of the target person.
4. The three-dimensional modeling and measuring method for human body according to claim 1, wherein in step S52, said half is a derived half of a point.
5. The three-dimensional human body modeling and measuring method according to claim 1, wherein in step S53, the front edge is an edge of the patch that points to the edge; the trailing edge is the edge on the patch that is pointed to by this edge.
6. A human body three-dimensional modeling and measuring system is characterized by comprising:
the depth map acquisition module is used for acquiring a target human body depth map through a depth camera;
the point cloud computing module is used for computing a point corresponding to each pixel in the target human body depth map to obtain a point cloud;
the point cloud optimization module is used for matching two adjacent frames of point clouds pairwise to perform point cloud optimization to obtain a global point cloud;
the model construction module is used for solving the global point cloud to obtain a target character model;
the model measurement module is used for acquiring a preset height horizontal plane, and measuring the target character model by calculating the girth of the target character model at the preset height horizontal plane to obtain a measured value of the target character model;
the model measurement module comprises an acquisition subunit, a reservation set establishing subunit and a girth calculation subunit;
the acquisition subunit is used for acquiring a preset height horizontal plane, and the preset height horizontal plane is a horizontal plane taking the preset height as a z-axis coordinate in a three-dimensional coordinate system taking a sole tangent plane of the target character model as an xy plane and the height of the target character model as a z-axis;
a reserved set establishing subunit, configured to obtain a half of the target character model that intersects with H, and remove a reverse edge of the half to obtain a reserved set;
and the girth calculation subunit is used for acquiring a half A edge in the retention set, searching the front side and the rear side of the reverse edge of the A edge to obtain adjacent truncated edges, storing the coordinates of the truncation points of the adjacent truncated edges, deleting the reverse edge of the newly added truncated edge to obtain the girth, acquiring the other half pair, and repeatedly searching until all the half edges in the retention set are searched to obtain the measured value of the target character model.
7. The human three-dimensional modeling and measuring system of claim 6, wherein the point cloud optimization module is specifically configured to:
and (3) optimizing the point cloud by minimizing the rigid motion difference between the point cloud of the previous frame and the point cloud of the next frame through a least square method, and matching every two adjacent frames of point clouds to obtain the global point cloud.
8. The human three-dimensional modeling and measuring system of claim 6, wherein the model building module is specifically configured to:
and solving each point cloud in the global point cloud through a Poisson equation, wherein the position with the gradient change value larger than a preset threshold value in the solving process is the surface of the target person, and constructing a target person model through the obtained surface of the target person.
9. The human three-dimensional modeling and measurement system of claim 6, wherein the retention set creation subunit is specifically configured to: the half is the derived half of a point.
10. The human body three-dimensional modeling and measuring system of claim 6, wherein the girth calculating subunit is specifically configured to: the front edge is an edge pointing to the edge on the dough sheet; the trailing edge is the edge on the patch that is pointed to by this edge.
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