CN110986757B - Three-dimensional human body scanning method, device and system - Google Patents
Three-dimensional human body scanning method, device and system Download PDFInfo
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- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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- G—PHYSICS
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/33—Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/30—Determination of transform parameters for the alignment of images, i.e. image registration
- G06T7/38—Registration of image sequences
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- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
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Abstract
The invention provides a three-dimensional human body scanning method, a device and a system, wherein the method comprises the following steps: calibrating two cameras inside each measuring head on a single column; calibrating external parameters of the at least three measuring heads; respectively projecting structured light to a measured human body in a single-upright-column horizontal rotation mode, and respectively collecting structured light images corresponding to the measured human body; carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body; aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body; and extracting the specified parameters of the measured human body according to the three-dimensional model. Through 360 all-round human scans of rotation of stand, increased the flexibility of data acquisition, reduce camera quantity simultaneously, reduce the hardware cost to need not mark the camera again after the equipment removes, but equipment optional shift position does not influence measuring precision.
Description
Technical Field
The invention relates to the technical field of human body scanning, in particular to a three-dimensional human body scanning method, device and system.
Background
In the related art, the three-dimensional scanning equipment mostly adopts four columns to collect human body picture data for calculation, wherein four side heads are fixed on each column of the four columns, each side head at least comprises 2 cameras, and under the condition that the positions of the cameras are fixed, the three-dimensional scanning equipment can only collect image data at fixed positions, so that the flexibility of data collection is reduced to a great extent, and the whole equipment needs to be recalibrated when any one column is moved, so that the complexity of the mobile equipment is increased. In addition, the four-column human body scanning requires a relatively large space for arranging hardware equipment, cannot be used under the condition of small space, and is not beneficial to random movement and transportation.
Furthermore, four side heads need to be arranged on each upright post of the existing four-upright-post human body scanning equipment and human body pictures are collected at the same time for calculation, so that the number of the cameras is four times that of single-post human body scanning, and the hardware cost is naturally four times that of the single-post human body scanning equipment. Therefore, a computer is required to have better expansibility, and 16 side heads can be connected at the same time, in this case, besides the complicated wiring of hardware equipment, each camera in the 16 side heads needs to respectively acquire pictures for internal reference calibration and then external reference calibration, and the calibration needs to be carried out again when the position of any one stand column changes, and the calibration complexity of the camera is increased.
Disclosure of Invention
The invention provides a three-dimensional human body scanning method, a device and a system for solving the problems in the related art.
The technical scheme adopted by the invention is as follows:
a three-dimensional human body scanning method comprises the following steps: s1: calibrating two cameras inside each measuring head on a single upright column, wherein the single upright column consists of at least three measuring heads distributed from top to bottom; s2: calibrating external parameters of the at least three measuring heads, wherein the external parameters are used for determining camera position coordinates among the three measuring heads; s3: respectively projecting structured light to a measured human body in a single-upright-column horizontal rotation mode, and respectively collecting structured light images corresponding to the measured human body, wherein the single-upright-column horizontal rotation mode is determined through a preset rule, and the preset rule corresponds to at least one of the following parameters: the shape of the measured human body, the standing posture of the measured human body and the motion state of the measured human body; s4: carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body; s5: aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body; s6: and extracting the specified parameters of the measured human body according to the three-dimensional model.
Optionally, the projecting the structured light to the detected human body respectively in a manner of horizontal rotation of the single column, and respectively collecting the structured light images corresponding to the detected human body includes: s11: the single upright posts are arranged to project the structured light to the measured human body according to different horizontal rotation angles; s12: and acquiring a structural optical image of the detected human body corresponding to each horizontal rotation angle.
Optionally, aligning each three-dimensional point cloud to the same coordinate system to obtain the three-dimensional model of the measured human body includes: s21: obtaining two camera images at different positions through rotation of the single upright post, and determining a rotation translation transformation matrix; s22: and acquiring the three-dimensional model of the measured human body in the same coordinate system according to the rotation and translation transformation matrix.
Optionally, the two cameras inside each measuring head on the calibration order column comprise: the method for calibrating the two cameras of each measuring head in the mode of binding and adjusting the internal and external parameters comprises the following steps: s31: acquiring a camera image group of a calibration plate at least ten different positions or postures under the two camera view fields, wherein the calibration plate is provided with coding points and non-coding points; s32: identifying the image coordinates of the coding points and the coding values corresponding to the non-coding points according to the camera image group; s33: calculating the relative position relation of any two groups of camera images in the camera image group and reconstructing the object space coordinates of the coding mark points; s34: calculating the positions of the other groups of camera image groups according to the obtained relative position relationship of the two groups of camera image groups, and reconstructing the object coordinates of the non-coding mark points based on the positions of all the groups of camera image groups; s35: and carrying out integral iterative optimization on the internal parameters and the external parameters of the two cameras, the object space coordinates of the coding mark points and the object space coordinates of the non-coding mark points by a binding adjustment optimization algorithm to obtain the internal and external parameters between the two cameras of the measuring head.
Optionally, the calibrating the external parameters of the three measuring heads comprises: calibrating the external parameters of the measuring head by adopting an external parameter binding adjustment mode, wherein the calibrating of the external parameters of the measuring head by adopting the external parameter binding adjustment mode specifically comprises the following steps: s41: the two cameras of each measuring head acquire camera images of two different positions of a calibration plate by moving the single upright post, wherein the calibration plate is provided with coding points and non-coding points; s42: calculating the relative position relation of any two groups of camera images and reconstructing the object space coordinates of the coding mark points; s43: calculating the positions of the other groups of camera images according to the obtained relative position relationship of the two groups of camera images, and reconstructing the object space coordinates of the non-coding mark points based on the positions of all the groups of camera images; s44: and carrying out integral iterative optimization on the external parameters of the measuring heads, the object space coordinates of the coding mark points and the object space coordinates of the non-coding mark points by adopting an external parameter binding adjustment optimization algorithm to obtain the external parameters among the measuring heads.
The present invention also provides a three-dimensional human body scanning device, comprising: the first calibration module is used for calibrating two cameras in each measuring head on a single upright post, wherein the single upright post consists of at least three measuring heads distributed from top to bottom; the second calibration module is used for calibrating external parameters of the three measuring heads, wherein the external parameters are used for determining camera position coordinates among the three measuring heads; the first acquisition module is used for projecting structured light to a detected human body respectively in a single-upright-column horizontal rotation mode and acquiring structured light images corresponding to the detected human body respectively, wherein the single-upright-column horizontal rotation mode is determined through a preset rule, and the preset rule corresponds to at least one of the following parameters: the shape of the measured human body, the standing posture of the measured human body and the motion state of the measured human body; the second acquisition module is used for carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body; the third acquisition module is used for aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body; and the extraction module is used for extracting the specified parameters of the measured human body according to the three-dimensional model of the measured human body.
The present invention also provides a three-dimensional human body scanning system, comprising: the measuring unit is used for acquiring a structured light image of a measured human body and transmitting the structured light image to the processing unit; the processing unit is used for receiving and processing the structural light image of the measured human body, and the processing comprises the following steps: carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body; aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body; and extracting the specified parameters of the measured human body according to the three-dimensional model.
Optionally, the measurement unit comprises: the single upright post is used for arranging at least three measuring heads; the measuring head comprises two cameras and a structured light projector and is used for acquiring a structured light image corresponding to the measured human body; and the rotating platform is connected with the single upright post and used for the tested human body to stand.
Optionally, the measurement unit further comprises: the power supply unit is used for supplying power to the measuring unit; and the calibration unit comprises a calibration plate, wherein the calibration plate is provided with a coding point and a non-coding point and is used for calibrating the measurement unit.
The invention also provides a computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of the above.
The invention has the beneficial effects that: the three-dimensional human body scanning method, the device and the system are provided, the omnibearing human body scanning is realized by rotating the upright column by 360 degrees, the flexibility of data acquisition is improved, the number of cameras is reduced, and the hardware cost is reduced; moreover, the camera does not need to be calibrated again after the equipment is moved, the position of the equipment can be moved at will, and the measurement precision is not influenced. Furthermore, the module is highly integrated between the projection device and the camera, so that the hardware deployment difficulty is reduced; hardware equipment is integrally formed, is calibrated at one time and is disassembled and assembled at a later stage, and recalibration calculation is not needed, so that the maintenance cost is reduced; the method overcomes the limitations of the traditional measuring method in the aspects of measuring range, measuring efficiency, measuring precision and the like, and realizes non-contact rapid measurement.
Drawings
Fig. 1 is a schematic diagram of a three-dimensional human body scanning method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a method for collecting a light image of a measured human body structure according to an embodiment of the present invention.
FIG. 3 is a method for obtaining a three-dimensional model of a human body under test according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a method for calibrating two cameras of a measuring head according to an embodiment of the present invention.
FIG. 5 is a schematic diagram of a method for calibrating a measuring head according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a speckle matching method in an embodiment of the invention.
FIG. 7 is a schematic diagram of a method for obtaining a three-dimensional model of a human body according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of a body measurement system in an embodiment of the invention.
Fig. 9 is a schematic diagram of another anthropometric system in an embodiment of the invention.
Fig. 10 is a schematic structural diagram of a measurement unit in an embodiment of the present invention.
Fig. 11 is a flowchart of a method of anthropometric measurement in an embodiment of the present invention.
FIG. 12 is a flow chart of a method of calibration in an embodiment of the present invention.
FIG. 13 is a schematic diagram of a three-dimensional model of a human body in an embodiment of the invention.
FIG. 14 is a schematic view of a three-dimensional human body scanning device according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the embodiments of the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or be indirectly connected to the other element. The connection may be for fixation or for circuit connection.
It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in an orientation or positional relationship indicated in the drawings for convenience in describing the embodiments of the present invention and to simplify the description, and are not intended to indicate or imply that the referenced device or element must have a particular orientation, be constructed in a particular orientation, and be in any way limiting of the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of the present invention, "a plurality" means two or more unless specifically limited otherwise.
Example 1
In this alternative embodiment, camera calibration and point cloud registration are first described.
Regarding camera calibration: in image measurement and machine vision applications, in order to determine the correlation between the three-dimensional geometric position of a certain point on the surface of a space object and the corresponding point in an image, a geometric model of camera imaging needs to be established, the geometric model parameters are camera parameters, and the process of solving the camera parameters is called camera calibration.
The distortion coefficient can be obtained through camera calibration (because the distortion exists more or less after imaging through a lens and the like), and the corresponding relation between a space coordinate system and an image coordinate system can also be obtained. Therefore, the accuracy of the camera calibration result directly affects the accuracy of the result generated by the camera work, and the camera calibration is a precondition for the subsequent work of the three-dimensional scanning.
Regarding point cloud registration: and (4) obtaining coordinate transformation through calculation, and uniformly integrating point cloud data under different viewing angles to a specified coordinate system through rigid transformation such as rotation and translation. In this case, two point clouds subjected to registration may be completely overlapped with each other through a position transformation such as rotational translation, so that the two point clouds belong to rigid transformation, i.e., the shape and the size are completely the same, but the coordinate positions are different. In other words, the point cloud registration is to find the coordinate position transformation relationship between two point clouds.
The basic input and output of point cloud registration are as follows: two rigidly transformed point clouds comprising: the method comprises the steps of obtaining a source point cloud (source) and a target point cloud (target), wherein the source point cloud and the target point cloud are the same in shape and size, and registering the point clouds to obtain a rotational translation transformation Matrix RT for short, wherein the Matrix RT Matrix represents the position transformation relation of the two point clouds, namely the source point cloud can be transformed to the position of the target point cloud through the RT, so that the source point cloud and the target point cloud can be superposed.
As shown in fig. 1, a three-dimensional human body scanning method includes the following steps:
s1: calibrating two cameras inside each measuring head on a single upright column, wherein the single upright column consists of at least three measuring heads distributed from top to bottom;
it will be appreciated that in one embodiment of the invention, a single column fixes the field of view of the measuring head from top to bottom in sequence; and then calibrating the two cameras in each measuring head in a mode of binding and adjusting internal and external parameters.
S2: calibrating external parameters of the at least three measuring heads, wherein the external parameters are used for determining camera position coordinates among the three measuring heads;
by calibrating the camera and the measuring head, the distortion coefficient can be obtained (because the distortion is more or less after imaging through a lens and the like), and the corresponding relation between a space coordinate system and an image coordinate system can also be obtained. Therefore, the accuracy of the calibration result directly affects the accuracy of the generated result, and the good calibration is the premise for making the follow-up work of the three-dimensional scanning.
S3: respectively projecting structured light to a measured human body in a single-upright-column horizontal rotation mode, and respectively collecting structured light images corresponding to the measured human body, wherein the single-upright-column horizontal rotation mode is determined through a preset rule, and the preset rule corresponds to at least one of the following parameters: the shape of the measured human body, the standing posture of the measured human body and the motion state of the measured human body;
in one embodiment of the invention, the single upright post may be rotated by a uniform angle; it is also possible to rotate the single upright at different angles each time. The experimental result shows that the scanning result is more accurate compared with the scanning result of uniform angles due to different angles of rotation every time.
It can be understood that the shape of the measured human body, the standing posture of the measured human body, and the motion state of the measured human body affect the preset rules, for example, the amount of information collected by the person with the large shape and the person with the small shape at an angle is different. Whatever the rule used, the aim is to collect the image of the human body under test in a comprehensive way. Selecting a preset rule by taking the rule as a judgment standard. In a particular embodiment, for a smaller person, the acquisition may be performed once on the front (i.e. 0 °, if the body to be tested is facing the single upright), once on the back (i.e. 180 °), once on each of the two sides (i.e. 90 ° and 270 °); for persons with larger outlines, the number of image acquisitions needs to be increased.
In the above example, when the human body faces the single upright post and stands upright and is still, the measured human body is not standing upright in many cases, the number of times of acquisition needs to be determined according to the specific standing posture of the measured human body, and the purpose is to acquire a full structured light image of the human body.
When the detected human body is not static, a certain motion posture is kept, for example, stepping or jogging or even circling can be performed in situ, and at the moment, only the single upright post needs to be rotated to collect the structural light image of the human body, so that more images can be collected, and the single upright post is arranged to collect at more angles by a certain rotation angle.
S4: carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body;
s5: aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body;
namely, three-dimensional point cloud data under different visual angles are uniformly integrated under an appointed coordinate system through rigid transformation such as rotation and translation, and a three-dimensional model of the measured human body is obtained.
S6: and extracting the specified parameters of the measured human body according to the three-dimensional model.
The specified parameters herein include, but are not limited to, size information of the human body, such as height, waist circumference, shoulder width, and the like.
Through the steps, under the condition of a rotatable single upright post, the specified parameters of the measured human body can be obtained by firstly calibrating the camera and the measuring head of the measuring head, then obtaining the human body structure light image and further obtaining the three-dimensional model of the human body. Compared with four columns in the related art, the method is simpler in acquisition mode and greatly saves cost.
As shown in fig. 2, the projecting the structured light to the human body to be detected respectively in a manner of horizontal rotation of the single column, and collecting the structured light images corresponding to the human body to be detected respectively includes:
s11: the single upright posts are arranged to project the structured light to the measured human body according to different horizontal rotation angles;
s12: and acquiring a structural optical image of the detected human body corresponding to each horizontal rotation angle.
Experiments prove that the scanning results of different horizontal rotation angles are more accurate compared with the scanning results of uniform horizontal rotation angles. The present invention preferably uses different horizontal rotation angles, but should not be considered as a limitation of the present invention, and in fact, the rotation angles may be set in various ways as long as a full-scale human body structure light image is acquired.
As shown in fig. 3, aligning each three-dimensional point cloud to the same coordinate system to obtain the three-dimensional model of the measured human body includes:
s21: obtaining two camera images at different positions through rotation of the single upright post, and determining a rotation translation transformation matrix;
s22: and acquiring the three-dimensional model of the measured human body in the same coordinate system according to the rotation and translation transformation matrix.
The rotational translation transformation Matrix RT Matrix is called RT for short, and the Matrix represents the position transformation relation of two point clouds, namely, the source point cloud can be transformed to the position of the target point cloud through the RT, so that the source point cloud and the target point cloud can be superposed.
As shown in fig. 4, the two cameras inside each measuring head on the calibration order column include: the method for calibrating the two cameras of each measuring head in the mode of binding and adjusting the internal and external parameters comprises the following steps:
s31: acquiring a camera image group of a calibration plate at least ten different positions or postures under the two camera view fields, wherein the calibration plate is provided with coding points and non-coding points;
it will be appreciated that the above described collection may result in ten sets of data, and that in order to make the calibration more accurate, more than ten sets of data may be collected, the more data collected the more accurate the calibration.
S32: identifying the image coordinates of the coding points and the coding values corresponding to the non-coding points according to the camera image group;
the image coordinates of the encoded points and the encoded values corresponding to the non-encoded points are identified by image processing techniques, which may be the methods in the prior art and are not limited herein. Here, at least ten sets of camera image groups are obtained in the recognition step S31.
S33: calculating the relative position relation of any two groups of camera images in the camera image group and reconstructing the object space coordinates of the coding mark points;
the relative position relationship between any two groups of images is calculated by a relative orientation algorithm, and it is understood that other feasible methods may be adopted, and are not limited herein.
From the camera image group in which at least ten sets of the encoding points and the non-encoding points are identified in step S32, arbitrary two sets of calculated relative positional relationships are selected.
S34: calculating the positions of the other groups of camera image groups according to the obtained relative position relationship of the two groups of camera image groups, and reconstructing the object coordinates of the non-coding mark points based on the positions of all the groups of camera image groups;
the positions of the remaining sets of the camera image groups are oriented by the direct linear transformation and the pyramid method, and the remaining sets are images except the two sets of camera images calculated in S33 in all the captured camera images.
S35: and carrying out integral iterative optimization on the internal parameters and the external parameters of the two cameras, the object space coordinates of the coding mark points and the object space coordinates of the non-coding mark points by a binding adjustment optimization algorithm to obtain the internal and external parameters between the two cameras of the measuring head.
It will be appreciated that here the calibration is performed for both cameras of the measuring head.
As shown in fig. 5, the calibrating the external parameters of the three measuring heads includes: calibrating the external parameters of the measuring head by adopting an external parameter binding adjustment mode, wherein the calibrating of the external parameters of the measuring head by adopting the external parameter binding adjustment mode specifically comprises the following steps:
s41: the two cameras of each measuring head acquire camera images of two different positions of a calibration plate by moving the single upright post, wherein the calibration plate is provided with coding points and non-coding points;
here the RT rototranslation matrix is determined by a single-upright rotation to obtain two camera images at different positions.
S42: calculating the relative position relation of any two groups of camera images and reconstructing the object space coordinates of the coding mark points;
s43: calculating the positions of the other groups of camera images according to the obtained relative position relationship of the two groups of camera images, and reconstructing the object space coordinates of the non-coding mark points based on the positions of all the groups of camera images;
s44: and carrying out integral iterative optimization on the external parameters of the measuring heads, the object space coordinates of the coding mark points and the object space coordinates of the non-coding mark points by adopting an external parameter binding adjustment optimization algorithm to obtain the external parameters among the measuring heads.
The calibration of the measuring head is completed through the steps, and the camera and the measuring head are calibrated at the moment. It is to be understood that the calibration methods given above are exemplary and may be performed using other calibration methods in the related art.
In one embodiment of the invention, the camera employs structured light that is speckle or grating.
As shown in fig. 6, the speckle matching is included inside the camera of the measuring head, which specifically includes the following steps:
s51: carrying out coarse matching by adopting a seed point diffusion method;
s52: and performing fine matching by adopting a digital image correlation method.
It is understood that the coarse matching and the fine matching may be performed on the raster image, which is not described herein.
As shown in fig. 7, step S5 includes the following steps:
s61: fusing each three-dimensional point cloud to obtain a human body point cloud outline model;
s62: and carrying out triangular gridding packaging and hole filling on the human body point cloud outline model to obtain the human body three-dimensional model.
By the above method, the method of the invention at least comprises the following advantages:
1. the method adopts a structured light projection measurement method, is harmless to human skin, healthy and free of radiation.
2. The invention overcomes the limitations of the traditional measuring method in the aspects of measuring range, measuring efficiency, measuring precision and the like, and realizes non-contact rapid measurement.
3. The invention reduces the number of cameras and hardware cost by rotating the upright post 360 degrees to the omnibearing human body scanning system.
4. The single-upright-column arrangement cameras are adopted, the human body image data in all directions are collected in a 360-degree rotation mode, and the flexibility of data collection of the equipment is improved.
5. The measuring head is arranged only by one upright column, so that the cost of the core part of the measuring head is reduced, the camera does not need to be calibrated again after the equipment is moved, the position of the equipment can be moved randomly, and the measuring precision is not influenced.
Example 2
As shown in fig. 8, the present invention also provides a three-dimensional human body scanning system, comprising:
the measuring unit is used for acquiring a structured light image of a measured human body and transmitting the structured light image to the processing unit;
the processing unit is used for receiving and processing the structural light image of the measured human body, and the processing comprises the following steps:
carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body;
aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body;
and extracting the specified parameters of the measured human body according to the three-dimensional model.
It is understood that the system further comprises a calibration unit for calibrating the measurement unit. The calibration unit may comprise a calibration plate with encoded dots and non-encoded dots.
The system provided by the invention at least comprises the following advantages:
1. the projection device and the camera used in the method are highly integrated into a module, so that the hardware deployment difficulty is reduced.
2. The method provided by the invention has the advantages that hardware equipment is integrally formed, once calibration is realized, later-stage disassembly and assembly are realized, re-calibration calculation is not needed, and the maintenance cost is reduced.
In an embodiment of the invention, further comprising a memory in which a computer program is stored which is executable on said processor. Such as a program that acquires images. The processor, when executing the computer program, implements the steps in the various embodiments of the anthropometric method described above, such as steps S4-S6 shown in fig. 1. Or, the processor implements the functions of the modules/units in the embodiments of the apparatuses when executing the computer program, for example, performs three-dimensional dense point cloud reconstruction on the structured light image of each human body to obtain a three-dimensional point cloud of the human body; aligning each three-dimensional point cloud to a coordinate system to obtain a three-dimensional model of the human body; and extracting the size of the human body according to the three-dimensional model of the human body.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program in the anthropometric system. For example, the computer program can be divided into a three-dimensional dense point cloud reconstruction module, a three-dimensional model acquisition module and a human body size acquisition module, and the specific functions of the modules are as follows: carrying out three-dimensional dense point cloud reconstruction on each structured light image of the human body to obtain a three-dimensional point cloud of the human body; aligning each three-dimensional point cloud to a coordinate system to obtain a three-dimensional model of the human body; and extracting the size of the human body according to the three-dimensional model of the human body.
The processing unit can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The anthropometric system may include, but is not limited to, a processor unit, a measurement unit. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a anthropometric system and does not constitute a limitation to the anthropometric system apparatus and may include more or less components than those shown, or some components in combination, or different components, for example the anthropometric system may also include input output devices, network access devices, buses, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center for the body measurement system, with various interfaces and lines connecting the various parts of the overall body measurement system.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the body measurement system by operating or executing the computer programs and/or modules stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
As shown in fig. 9, in an alternative embodiment of the present invention, the anthropometric system further comprises: the power supply unit is used for supplying power to the measuring unit, and the single upright post of the human body measuring system after power supply can rotate and can also carry out human body measurement; and the calibration unit comprises a calibration plate, wherein the calibration plate is provided with a coding point and a non-coding point and is used for calibrating the measurement unit. The power supply unit may be an electrical control box.
Example 3
As shown in fig. 10, the measuring unit in the body measuring system of the present invention includes:
the single upright column 1 is used for arranging at least three measuring heads;
the measuring head 2 comprises two cameras and a structured light projector and is used for acquiring a structured light image corresponding to the measured human body;
and the rotary table 3 is connected with the single upright post and used for the tested human body to stand.
In an alternative embodiment of the present invention, a support is further included for supporting the single upright. The figure includes four measuring heads, and in practice, the invention of the present application can be implemented as long as 3 or more than 3 measuring heads are included.
As shown in fig. 11, the human body measurement using the human body measurement system of the present invention includes the steps of:
step 1, rotating the view field of a measuring head;
the field of view of the fixed position single column measuring head is limited, and the field of view is not enough to cover the human body. In the step, the upright cameras are arranged in a rotating mode, so that on one hand, the view fields formed by all the measuring heads can cover the height of a human body; on the other hand, the 360-degree rotating upright post can fully cover the human body.
In the invention, the cameras are integrated in a very small measuring head, and the relative positions such as the included angle between the cameras cannot be changed, thereby increasing the difficulty of the overall layout of the multiple measuring heads and the difficulty of camera calibration. The invention adopts a ten-parameter calibration model, firstly calibrates the internal parameters of two black and white cameras inside each measuring head, simplifies the calibration model, and can start measuring only by once calibrating the external parameters of the measuring head before actual measurement, thereby greatly simplifying the calibration model, smoothly performing the calibration process, improving the calibration precision, and completing the accurate positioning of all measuring head positions when the calibration state is about 12 photos.
In the exemplary embodiment of the invention, the internal and external parameters of the cameras in the four measuring heads on the upright post are calibrated by adopting the plane calibration plate. The calibration plate is used for carrying out silk-screen printing on coding points and non-coding points in advance, the calibration plate is placed in the center position of the measuring head during calibration, images of the calibration plate are collected respectively, the position of the calibration plate is changed after each calibration plate is collected, the calibration plate is collected until ten images are collected, then three-dimensional point information on the calibration plate is identified, internal parameters are resolved, images of the calibration plate are collected for four measuring heads simultaneously, and absolute external parameters of the measuring head are obtained through external parameter transmission. And finally, rotating the stand column by a certain angle, collecting the calibration plate image for the measuring head again, and calculating a unit angle RT matrix.
As shown in fig. 12, the calibration process specifically includes the steps of:
1. placing a calibration plate with coding points and non-coding mark points in a field of view of a camera, and moving the calibration plate to obtain camera images of the calibration plate at ten different positions and postures;
2. identifying image coordinates of non-coding points in the ten groups of images and coding values corresponding to the coding points through image processing;
3. calculating the relative position relation of any two groups of images through a relative orientation algorithm in photogrammetry, and reconstructing object coordinates of the coding mark points;
4. orienting other groups of image positions by a direct linear transformation method and a pyramid method, and reconstructing object space coordinates of the non-coding mark points;
5. internal parameters and external parameters of the camera are adjusted through a binding optimization algorithm;
6. simultaneously acquiring calibration plate images for the measuring heads;
7. through image processing, identifying image coordinates of non-coding points in the ten groups of images and coding values corresponding to the coding points, calculating the relative position relation of any two groups of images through a relative orientation algorithm in photogrammetry, reconstructing object coordinates of coding mark points, and determining the position of a camera;
8. rotating the upright column by a certain angle, simultaneously acquiring calibration plate images for the measuring head, and calculating a common point set in two sets of depth data through depth point cloud calibration;
9. calculating a rotation angle component and a translation component according to the rotation angle of the upright column around the Y axis;
XR rotating shaft coordinate system coordinate
XC camera coordinate system coordinate
The rotation matrix from R (R _ out) camera coordinate system to rotating shaft coordinate system is a right multiplication matrix
Translation matrix from coordinate system of T (T) camera to coordinate system of rotary shaft as row vector
*XR＝(XC*R+T)*RX
Converting R into conventional left-multiplication rotation matrix, namely transpose R 'of original matrix'
The formula is changed into the form
*XR＝RX'*(R'*XC+T)
And 3, carrying out three-dimensional dense point cloud reconstruction by using the calibrated measuring head to obtain a human body three-dimensional model.
As shown in fig. 13, a calibrated human body three-dimensional scanning device with multiple measuring heads is used for distributed dense reconstruction of three-dimensional point cloud, point cloud models of the multiple measuring heads are fused to obtain a human body point cloud contour model, triangular meshing encapsulation and hole filling are performed on the human body point cloud contour model to generate a three-dimensional solid model, and the three-dimensional solid model is subjected to subsequent optimization processing such as smooth denoising and the like to obtain the human body three-dimensional model shown in the figure.
And 4, extracting the size of the human body model according to the human body three-dimensional model.
In the step, according to characteristic parameters on the human body three-dimensional model, the size data which can be used in downstream industries can be accurately extracted according to basic size data required by the clothing industry and the definition of the sizes on the three-dimensional model.
Example 4
As shown in fig. 14, the present invention also provides a three-dimensional human body scanning device, comprising:
the first calibration module is used for calibrating two cameras in each measuring head on a single upright post, wherein the single upright post consists of at least three measuring heads distributed from top to bottom;
the second calibration module is used for calibrating external parameters of the three measuring heads, wherein the external parameters are used for determining camera position coordinates among the three measuring heads;
the first acquisition module is used for projecting structured light to a detected human body respectively in a single-upright-column horizontal rotation mode and acquiring structured light images corresponding to the detected human body respectively, wherein the single-upright-column horizontal rotation mode is determined through a preset rule, and the preset rule corresponds to at least one of the following parameters: the shape of the measured human body, the standing posture of the measured human body and the motion state of the measured human body;
the second acquisition module is used for carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body;
the third acquisition module is used for aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body;
and the extraction module is used for extracting the specified parameters of the measured human body according to the three-dimensional model of the measured human body.
The module integrated with the anthropometric system may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several equivalent substitutions or obvious modifications can be made without departing from the spirit of the invention, and all the properties or uses are considered to be within the scope of the invention.
Claims (7)
1. A three-dimensional human body scanning method is characterized by comprising the following steps:
s1: calibrating two cameras inside each measuring head on a single upright column, wherein the single upright column consists of at least three measuring heads distributed from top to bottom; the two cameras inside each measuring head on the calibration single column comprise: the method for calibrating the two cameras of each measuring head in the mode of binding and adjusting the internal and external parameters comprises the following steps:
s31: acquiring a camera image group of a calibration plate at least ten different positions or postures under the two camera view fields, wherein the calibration plate is provided with coding points and non-coding points;
s32: identifying the image coordinates of the non-coding points and the coding values corresponding to the coding points according to the camera image group;
s33: calculating the relative position relation of any two groups of camera images in the camera image group and reconstructing the object space coordinates of the coding points;
s34: calculating the positions of the other groups of camera images according to the obtained relative position relationship of the two groups of camera images, and reconstructing the object coordinates of the non-coding points based on the positions of all the groups of camera images;
s35: performing integral iterative optimization on internal parameters and external parameters of the two cameras, the object space coordinates of the coding points and the object space coordinates of the non-coding points by a binding adjustment optimization algorithm to obtain internal and external parameters between the two cameras of the measuring head; s2: calibrating external parameters of the at least three measuring heads, wherein the external parameters are used for determining camera position coordinates among the at least three measuring heads; the calibrating the external parameters of the at least three measuring heads comprises: calibrating the external parameters of the measuring head by adopting an external parameter binding adjustment mode, wherein the calibrating of the external parameters of the measuring head by adopting the external parameter binding adjustment mode specifically comprises the following steps:
s41: the two cameras of each measuring head acquire camera images of two different positions of a calibration plate by moving the single upright post, wherein the calibration plate is provided with coding points and non-coding points;
s42: calculating the relative position relation of any two groups of camera images and reconstructing the object space coordinates of the coding points;
s43: calculating the positions of the other groups of camera images according to the obtained relative position relationship of the two groups of camera images, and reconstructing the object coordinates of the non-coding points based on the positions of all the groups of camera images;
s44: performing integral iterative optimization on the external parameters of the measuring heads, the object space coordinates of the coding points and the object space coordinates of the non-coding points by adopting an external parameter binding adjustment optimization algorithm to obtain external parameters among the measuring heads;
s3: respectively projecting structured light to a measured human body in a single-upright-column horizontal rotation mode, and respectively collecting structured light images corresponding to the measured human body, wherein the single-upright-column horizontal rotation mode is determined through a preset rule, and the preset rule corresponds to at least one of the following parameters: the shape of the measured human body, the standing posture of the measured human body and the motion state of the measured human body;
s4: carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body;
s5: aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body;
s6: and extracting the specified parameters of the measured human body according to the three-dimensional model.
2. The three-dimensional human body scanning method of claim 1, wherein the projecting the structured light to the human body to be detected respectively by the single column rotating horizontally and collecting the structured light image corresponding to the human body to be detected respectively comprises:
s11: the single upright posts are arranged to project the structured light to the measured human body according to different horizontal rotation angles;
s12: and collecting the structured light image of the detected human body corresponding to each horizontal rotation angle.
3. The method of claim 1, wherein aligning each of the three-dimensional point clouds to a coordinate system to obtain a three-dimensional model of the human body comprises:
s21: obtaining two camera images at different positions through rotation of the single upright post, and determining a rotation translation transformation matrix;
s22: and acquiring the three-dimensional model of the measured human body in the same coordinate system according to the rotation and translation transformation matrix.
4. A three-dimensional body scanning device, comprising:
the first calibration module is used for calibrating two cameras in each measuring head on a single upright post, wherein the single upright post consists of at least three measuring heads distributed from top to bottom; the two cameras inside each measuring head on the calibration single column comprise: the method for calibrating the two cameras of each measuring head in the mode of binding and adjusting the internal and external parameters comprises the following steps:
s11: acquiring a camera image group of a calibration plate at least ten different positions or postures under the two camera view fields, wherein the calibration plate is provided with coding points and non-coding points;
s12: identifying the image coordinates of the non-coding points and the coding values corresponding to the coding points according to the camera image group;
s13: calculating the relative position relation of any two groups of camera images in the camera image group and reconstructing the object space coordinates of the coding points;
s14: calculating the positions of the other groups of camera images according to the obtained relative position relationship of the two groups of camera images, and reconstructing the object coordinates of the non-coding points based on the positions of all the groups of camera images;
s15: performing integral iterative optimization on internal parameters and external parameters of the two cameras, the object space coordinates of the coding points and the object space coordinates of the non-coding points by a binding adjustment optimization algorithm to obtain internal and external parameters between the two cameras of the measuring head; the second calibration module is used for calibrating external parameters of the at least three measuring heads, wherein the external parameters are used for determining the camera position coordinates among the at least three measuring heads; the calibrating the external parameters of the at least three measuring heads comprises: calibrating the external parameters of the measuring head by adopting an external parameter binding adjustment mode, wherein the calibrating of the external parameters of the measuring head by adopting the external parameter binding adjustment mode specifically comprises the following steps:
s21: the two cameras of each measuring head acquire camera images of two different positions of a calibration plate by moving the single upright post, wherein the calibration plate is provided with coding points and non-coding points;
s22: calculating the relative position relation of any two groups of camera images and reconstructing the object space coordinates of the coding points;
s23: calculating the positions of the other groups of camera images according to the obtained relative position relationship of the two groups of camera images, and reconstructing the object coordinates of the non-coding points based on the positions of all the groups of camera images;
s24: performing integral iterative optimization on the external parameters of the measuring heads, the object space coordinates of the coding points and the object space coordinates of the non-coding points by adopting an external parameter binding adjustment optimization algorithm to obtain external parameters among the measuring heads; the first acquisition module is used for projecting structured light to a detected human body respectively in a single-upright-column horizontal rotation mode and acquiring structured light images corresponding to the detected human body respectively, wherein the single-upright-column horizontal rotation mode is determined through a preset rule, and the preset rule corresponds to at least one of the following parameters: the shape of the measured human body, the standing posture of the measured human body and the motion state of the measured human body;
the second acquisition module is used for carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body;
the third acquisition module is used for aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body;
and the extraction module is used for extracting the specified parameters of the measured human body according to the three-dimensional model of the measured human body.
5. A three-dimensional body scanning system for implementing the method of any of claims 1-3, comprising:
the measuring unit is used for acquiring a structured light image of a measured human body and transmitting the structured light image to the processing unit; the measurement unit includes: the single upright post is used for arranging at least three measuring heads; the measuring head comprises two cameras and a structured light projector and is used for acquiring a structured light image corresponding to the measured human body; the rotating platform is connected with the single upright post and used for the tested human body to stand;
the calibration unit comprises a calibration plate, the calibration plate is provided with coding points and non-coding points and is used for calibrating the measurement unit;
the processing unit is used for receiving and processing the structural light image of the measured human body, and the processing comprises the following steps:
carrying out three-dimensional dense point cloud reconstruction on the acquired structured light image corresponding to each detected human body to obtain three-dimensional point cloud corresponding to the detected human body;
aligning each three-dimensional point cloud to the same coordinate system to obtain a three-dimensional model of the measured human body;
and extracting the specified parameters of the measured human body according to the three-dimensional model.
6. The three dimensional body scanning system of claim 5, further comprising:
and the power supply unit is used for supplying power to the measuring unit.
7. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 3.
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| CN111932670B (en) * | 2020-08-13 | 2021-09-28 | 北京未澜科技有限公司 | Three-dimensional human body self-portrait reconstruction method and system based on single RGBD camera |
| CN112577447B (en) * | 2020-12-07 | 2022-03-22 | 新拓三维技术(深圳)有限公司 | Three-dimensional full-automatic scanning system and method |
| CN112729156A (en) * | 2020-12-24 | 2021-04-30 | 上海智能制造功能平台有限公司 | Data splicing and system calibration method of human body digital measuring device |
| CN113379893B (en) * | 2021-05-27 | 2022-02-11 | 杭州小肤科技有限公司 | Method for synthesizing 3D face model by utilizing optical reflection |
| CN113483661B (en) * | 2021-07-06 | 2023-06-30 | 广东南方数码科技股份有限公司 | Point cloud data acquisition method, device, equipment and storage medium |
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