CN110910491A - Three-dimensional human body modeling optimization method and system - Google Patents
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Abstract
The invention discloses a three-dimensional human body modeling optimization method, which comprises the following steps: acquiring a three-dimensional image of a target user, performing brightness detection on the three-dimensional image, identifying a shadow part and a reflection part, and marking the shadow part and the reflection part as influence factors; identifying the breast features in the three-dimensional image, determining a breast range and establishing a standard grid in the breast range; selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and carrying out simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid; and when all the influence factors in the standard grid are replaced by the development grid, stopping the simulation development, calculating the weight value of the replaced grid, and performing color adjustment on the grid with the abnormal weight value.
Description
Technical Field
The invention relates to the field of three-dimensional human body modeling, in particular to a three-dimensional human body modeling optimization method and system.
Background
In the field of clothes, the function of a human body can be improved only if the structure of the clothes is matched with the shape of a curved surface of the human body, and the clothes are comfortable and fit. The bra is a piece of clothing worn next to the skin, the human breast is a part with a large change of the human curved surface, the acquisition of the detail data of the breast is particularly important for the design of the bra, and the bra can be comfortable and beautiful only if the contour lines of the cups are matched with the breasts of the human body. However, the breast of the human body has no skeleton, the manual measurement is easy to cause deformation and bring inconvenience, and the difficulty of manually acquiring the detailed size of the breast is increased to a certain extent.
In the prior art, a three-dimensional human body modeling method is applied to design bra cups; the three-dimensional measurement technology is adopted to obtain a three-dimensional image of a user, and breast parameters of the user are identified by constructing a three-dimensional human body model, so that the three-dimensional size of the user is extracted, and corresponding bra cups are designed. However, in the process of obtaining the three-dimensional image, due to the irradiation of the light source and the influence of the shape of the outline of the breast, the acquired breast image is more or less prone to shadow and reflection, when the three-dimensional human body model identifies the breast image, the body part of the breast image at the shadow can be calculated, and the reflection part is ignored, so that the breast parameters obtained by identification and calculation are different from the actual parameters and have differences, the size of the designed bra cup cannot be well matched with the breast of the user, and the user experience is poor.
Disclosure of Invention
The invention provides a three-dimensional human body modeling optimization method and a three-dimensional human body modeling optimization system, wherein identification marks of a shadow part and a reflection part in a three-dimensional image are replaced and adjusted by combining a simulation development technology, so that the technical problem that errors exist in model identification calculation due to image shadow and reflection when a three-dimensional human body modeling method in the prior art identifies a breast image is solved, accurate adaptive replacement is carried out on the shadow part and the reflection part in the breast image, breast parameters obtained by identification calculation are more accurate, and bra cups with better adaptability are designed.
In order to solve the above technical problem, an embodiment of the present invention provides a three-dimensional human body modeling optimization method, including:
acquiring a three-dimensional image of a target user, performing brightness detection on the three-dimensional image, identifying a shadow part and a reflection part, and marking the shadow part and the reflection part as influence factors;
identifying the breast features in the three-dimensional image, determining a breast range and establishing a standard grid in the breast range;
selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and carrying out simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid;
and when all the influence factors in the standard grid are replaced by the development grid, stopping the simulation development, calculating the weight value of the replaced grid, and performing color adjustment on the grid with the abnormal weight value.
Preferably, the initial development grids are all selected to be grids without influence factors.
As a preferred scheme, the step of performing simulated development on the initial development grid to the target grid specifically includes:
setting RGB color level threshold values, and performing color level copying on the initial development grid through a simulator to obtain a corresponding development grid;
and moving the copied development grids to the grids closest to the current development grid for replacement in sequence until all the grids in the influence factors are replaced.
Preferably, the initial evolving grid is chosen to be a continuous grid.
As a preferred scheme, the calculating a weight value of the replaced grid, and performing color adjustment on the grid with an abnormal weight value specifically includes:
calculating and obtaining the weight value of each grid in the standard grid through an analytic hierarchy process;
comparing the weight value of the replaced grid with the weight value of the grid closest to the periphery of the replaced grid, and determining that the current grid is an abnormal grid when the difference value of the weight values exceeds a preset threshold value;
and performing color adjustment on the abnormal grid, wherein the color adjustment comprises gray level adjustment.
The embodiment of the invention also provides a three-dimensional human body modeling optimization system, which comprises:
the brightness detection module is used for acquiring a three-dimensional image of a target user, detecting the brightness of the three-dimensional image, identifying the positions of a shadow and a reflection and marking the positions as influence factors;
the grid establishing module is used for identifying the breast features in the three-dimensional image, determining the breast range and establishing a standard grid in the breast range;
the grid replacement module is used for selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and performing simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid;
and the abnormal adjustment module is used for stopping the simulation development and calculating the weight value of the replaced grid after all the influence factors in the standard grid are replaced by the development grid, and performing color adjustment on the grid with the abnormal weight value.
Preferably, the grid replacement module is configured to perform simulated development on an initial development grid to the target grid, and specifically includes:
setting RGB color level threshold values, and performing color level copying on the initial development grid through a simulator to obtain a corresponding development grid;
and moving the copied development grids to the grids closest to the current development grid for replacement in sequence until all the grids in the influence factors are replaced.
As a preferred scheme, the abnormal adjustment module is configured to calculate a weight value of the replaced grid, and perform color adjustment on the grid with an abnormal weight value, and specifically includes:
calculating and obtaining the weight value of each grid in the standard grid through an analytic hierarchy process;
comparing the weight value of the replaced grid with the weight value of the grid closest to the periphery of the replaced grid, and determining that the current grid is an abnormal grid when the difference value of the weight values exceeds a preset threshold value;
and performing color adjustment on the abnormal grid, wherein the color adjustment comprises gray level adjustment.
As a preferred scheme, the initial development grids are all grids without influence factors; the initial evolving grid is chosen to be a continuous grid.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; wherein the computer program, when running, controls an apparatus on which the computer readable storage medium is located to perform the three-dimensional human body modeling optimization method according to any one of the above.
An embodiment of the present invention further provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the three-dimensional human body modeling optimization method according to any one of the above items when executing the computer program.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the invention identifies marks at the shadow position and the reflection position in the three-dimensional image, combines the simulation development technology to replace and adjust the positions of the shadow position and the reflection position, and solves the technical problem that when the three-dimensional human body modeling method in the prior art identifies the breast image, the model identification calculation has errors due to the shadow and the reflection of the image, so that the shadow position and the reflection position in the breast image are accurately adaptively replaced, the breast parameters obtained by identification calculation are more accurate, and the bra cup with better adaptability is designed.
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FIG. 1: the steps of the three-dimensional human body modeling optimization method in the embodiment of the invention are a flow chart;
FIG. 2: the structural schematic diagram of the three-dimensional human body modeling optimization system in the embodiment of the invention is shown.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a preferred embodiment of the present invention provides a three-dimensional human body modeling optimization method, including:
s1, acquiring a three-dimensional image of a target user, performing brightness detection on the three-dimensional image, identifying the positions of a shadow and a reflection and marking the positions as influence factors. Firstly, a target image to be detected is collected, namely, the image is processed before the three-dimensional image is input into the three-dimensional human body model for identification. Graying a target image to be detected; then calculating the ratio of the gray average value and the variance of the gray image to obtain a brightness ratio; and comparing the brightness ratio with a preset threshold value, and performing brightness detection so as to evaluate whether the brightness of the image to be detected is abnormal.
And S2, identifying the breast features in the three-dimensional image, determining the breast range and establishing a standard grid in the breast range. According to the identification of the chest characteristics, the approximate range of the chest can be determined, and in order to make the technical scheme more optimal, a chest identification model can be established to accurately identify the chest range.
Specifically, the step of establishing the chest identification model may specifically include:
step one, collecting a mass of chest images as samples, and classifying training samples and testing samples.
And step two, establishing an initial model through third-party software, inputting a training sample into the initial model for training, and stopping training until the training times reach a training time threshold or the training accuracy reaches a training accuracy threshold.
And step three, inputting the test sample into the trained model for testing, and obtaining the optimized recognition model when the test times reach the test time threshold or the test accuracy reaches the test accuracy threshold.
At this time, the three-dimensional image is input to the recognition model, and the chest region can be precisely recognized.
S3, selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and carrying out simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid.
In this embodiment, the step of performing simulated development on the initial development grid to the target grid specifically includes: s31, setting RGB color level threshold values, and copying the color level of the initial development grid through a simulator to obtain a corresponding development grid; and S32, sequentially moving the copied development grids to the grids closest to the current development grid for replacement until all the grids in the influence factors are replaced.
In step S3, a simulation development process is performed using a cellular automaton. The Cellular Automata (CA) is a grid dynamics model with discrete time, space and state, and local space interaction and time causal relationship, and has the capability of simulating the space-time evolution process of a complex system. The grid is simulated and developed through a cellular automaton technology, and actually, a selected initial development grid is used as a central cell to develop to the outside. However, in the technical scheme, the development direction of the central unit cell is limited by arranging the standard grid, and the advantages of the method and the device are that the processing efficiency can be further improved, and the problem that the grid has errors in the replacement of the influence factors in the development process is solved. In the step of judging the completion of the replacement of the impact factors, the replacement objects of the development grids can be judged, when the replacement development of the two development grids meets each other, because the opposite side does not belong to the grid where the impact factors are located, the reproduction development is stopped until the last development grid meets each other, and at the moment, the replacement work of the impact factor area is completed.
In this embodiment, the initial development grids are selected to be grids without influence factors. In this embodiment, the initial evolving grid is chosen to be a continuous grid.
The grid without influence factors is selected as the initial development grid, so that the self-reproduction error of the grid in the reproduction and development process is avoided, namely the initial development grid contains the influence factors, so that the grids replaced later all have the influence factors, and the aim of eliminating the influence factors cannot be achieved. And the use of a continuous grid as the initial development grid is to further increase the processing efficiency. In the technical scheme, one development grid can be selected at least, but the efficiency is very low at the moment, and if a circle of continuous grids surrounding the influence factors are selected, the efficiency of seamless replacement can be achieved, and the replacement processing efficiency is greatly improved.
And S4, after all the influence factors in the standard grid are replaced by the development grid, stopping the simulation development, calculating the weight value of the replaced grid, and performing color adjustment on the grid with the abnormal weight value.
In this embodiment, the calculating a weight value of the replaced grid, and performing color adjustment on the grid with an abnormal weight value specifically includes: s41, calculating and obtaining the weight value of each grid in the standard grid through an analytic hierarchy process; s42, comparing the weight value of the replaced grid with the weight value of the grid closest to the periphery of the replaced grid, and determining that the current grid is an abnormal grid when the difference value of the weight values exceeds a preset threshold value; s43, performing color adjustment on the abnormal grid, wherein the color adjustment comprises gray level adjustment.
Analytic hierarchy process, AHP for short, refers to a decision-making method that decomposes elements always related to decision-making into levels such as targets, criteria, schemes, etc., and performs qualitative and quantitative analysis on the basis. The method is a hierarchical weight decision analysis method which is provided by the university of Pittsburgh, a university of American operational research, in the early 70 th century of the 20 th century and by applying a network system theory and a multi-target comprehensive evaluation method when researching the subject of 'power distribution according to the contribution of each industrial department to national welfare' for the United states department of defense. Firstly, dividing a decision target, a considered factor (decision criterion) and a decision object into a highest layer, a middle layer and a lowest layer according to the mutual relation among the decision target, the considered factor (decision criterion) and the decision object, and drawing a hierarchical structure diagram. The highest level refers to the purpose of the decision, the problem to be solved. The lowest layer refers to the alternative at decision time. The middle layer refers to the factor to be considered and the decision criterion. For two adjacent layers, the upper layer is called a target layer, and the lower layer is called a factor layer. Then, a judgment (pair-wise comparison) matrix, a level single ordering and consistency check thereof are constructed, and finally a level total ordering and consistency check thereof are carried out.
And calculating the weight values of the grids and comparing the threshold values, and determining the grids exceeding the threshold values as abnormal grids. And adjusting the abnormal grids, wherein the abnormal grids are mainly used for adjusting factors such as gray level and the like which influence the identification operation of the identification model so as to achieve the function of optimizing the image.
The invention identifies marks at the shadow position and the reflection position in the three-dimensional image, combines the simulation development technology to replace and adjust the positions of the shadow position and the reflection position, and solves the technical problem that when the three-dimensional human body modeling method in the prior art identifies the breast image, the model identification calculation has errors due to the shadow and the reflection of the image, so that the shadow position and the reflection position in the breast image are accurately adaptively replaced, the breast parameters obtained by identification calculation are more accurate, and the bra cup with better adaptability is designed.
Correspondingly, referring to fig. 2, an embodiment of the present invention further provides a three-dimensional human body modeling optimization system, including:
the brightness detection module is used for acquiring a three-dimensional image of a target user, detecting the brightness of the three-dimensional image, identifying the positions of a shadow and a reflection and marking the positions as influence factors;
the grid establishing module is used for identifying the breast features in the three-dimensional image, determining the breast range and establishing a standard grid in the breast range;
the grid replacement module is used for selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and performing simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid;
and the abnormal adjustment module is used for stopping the simulation development and calculating the weight value of the replaced grid after all the influence factors in the standard grid are replaced by the development grid, and performing color adjustment on the grid with the abnormal weight value.
In this embodiment, the grid replacement module is configured to perform simulated development on an initial development grid to the target grid, and specifically includes:
setting RGB color level threshold values, and performing color level copying on the initial development grid through a simulator to obtain a corresponding development grid;
and moving the copied development grids to the grids closest to the current development grid for replacement in sequence until all the grids in the influence factors are replaced.
In this embodiment, the abnormal adjustment module is configured to calculate a weight value of the replaced grid, and perform color adjustment on the grid with an abnormal weight value, where the step specifically includes:
calculating and obtaining the weight value of each grid in the standard grid through an analytic hierarchy process;
comparing the weight value of the replaced grid with the weight value of the grid closest to the periphery of the replaced grid, and determining that the current grid is an abnormal grid when the difference value of the weight values exceeds a preset threshold value;
and performing color adjustment on the abnormal grid, wherein the color adjustment comprises gray level adjustment.
In this embodiment, the initial development grids are all selected to be grids without influence factors; the initial evolving grid is chosen to be a continuous grid.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; wherein the computer program, when running, controls the device on which the computer-readable storage medium is located to execute the three-dimensional human body modeling optimization method according to any one of the above embodiments.
The embodiment of the present invention further provides a terminal device, where the terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the three-dimensional human body modeling optimization method according to any of the above embodiments when executing the computer program.
Preferably, the computer program may be divided into one or more modules/units (e.g., computer program) 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 for describing the execution process of the computer program in the terminal device.
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, a discrete Gate or transistor logic device, a discrete hardware component, etc., the general purpose Processor may be a microprocessor, or the Processor may be any conventional Processor, the Processor is a control center of the terminal device, and various interfaces and lines are used to connect various parts of the terminal device.
The memory mainly includes a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like, and the data storage area may store related data and the like. In addition, the memory may be a high speed random access memory, may also be a non-volatile memory, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, or may also be other volatile solid state memory devices.
It should be noted that the terminal device may include, but is not limited to, a processor and a memory, and those skilled in the art will understand that the terminal device is only an example and does not constitute a limitation of the terminal device, and may include more or less components, or combine some components, or different components.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (10)
1. A three-dimensional human body modeling optimization method is characterized by comprising the following steps:
acquiring a three-dimensional image of a target user, performing brightness detection on the three-dimensional image, identifying a shadow part and a reflection part, and marking the shadow part and the reflection part as influence factors;
identifying the breast features in the three-dimensional image, determining a breast range and establishing a standard grid in the breast range;
selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and carrying out simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid;
and when all the influence factors in the standard grid are replaced by the development grid, stopping the simulation development, calculating the weight value of the replaced grid, and performing color adjustment on the grid with the abnormal weight value.
2. The method of claim 1, wherein the initial development grids are selected to be grids that do not contain an impact factor.
3. The three-dimensional human modeling optimization method of claim 2, wherein the step of performing simulated development of the initial development grid to the target grid specifically comprises:
setting RGB color level threshold values, and performing color level copying on the initial development grid through a simulator to obtain a corresponding development grid;
and moving the copied development grids to the grids closest to the current development grid for replacement in sequence until all the grids in the influence factors are replaced.
4. The method of three-dimensional human modeling optimization according to claim 1, wherein said initial evolving grid is chosen as a continuous grid.
5. The three-dimensional human body modeling optimization method according to claim 1, wherein the calculating of the weight values of the replaced grids and the color adjustment of the grid with an abnormal weight value specifically include:
calculating and obtaining the weight value of each grid in the standard grid through an analytic hierarchy process;
comparing the weight value of the replaced grid with the weight value of the grid closest to the periphery of the replaced grid, and determining that the current grid is an abnormal grid when the difference value of the weight values exceeds a preset threshold value;
and performing color adjustment on the abnormal grid, wherein the color adjustment comprises gray level adjustment.
6. A three-dimensional human body modeling optimization system, comprising:
the brightness detection module is used for acquiring a three-dimensional image of a target user, detecting the brightness of the three-dimensional image, identifying the positions of a shadow and a reflection and marking the positions as influence factors;
the grid establishing module is used for identifying the breast features in the three-dimensional image, determining the breast range and establishing a standard grid in the breast range;
the grid replacement module is used for selecting a normal part around the influence factor in a standard grid as an initial development grid, taking the center of the influence factor as a target grid, and performing simulated development on the initial development grid to the target grid to replace the initial development grid with a development grid;
and the abnormal adjustment module is used for stopping the simulation development and calculating the weight value of the replaced grid after all the influence factors in the standard grid are replaced by the development grid, and performing color adjustment on the grid with the abnormal weight value.
7. The three-dimensional human modeling optimization system of claim 6, wherein the grid replacement module is configured to perform simulated development of an initial development grid to the target grid, and specifically comprises:
setting RGB color level threshold values, and performing color level copying on the initial development grid through a simulator to obtain a corresponding development grid;
and moving the copied development grids to the grids closest to the current development grid for replacement in sequence until all the grids in the influence factors are replaced.
8. The three-dimensional human body modeling optimization system according to claim 6, wherein the anomaly adjustment module is configured to calculate a weight value of the replaced grid, and perform color adjustment on the grid with an abnormal weight value, specifically including:
calculating and obtaining the weight value of each grid in the standard grid through an analytic hierarchy process;
comparing the weight value of the replaced grid with the weight value of the grid closest to the periphery of the replaced grid, and determining that the current grid is an abnormal grid when the difference value of the weight values exceeds a preset threshold value;
and performing color adjustment on the abnormal grid, wherein the color adjustment comprises gray level adjustment.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored computer program; wherein the computer program, when executed, controls an apparatus on which the computer-readable storage medium is located to perform the three-dimensional human body modeling optimization method according to any one of claims 1 to 5.
10. A terminal device comprising a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the three-dimensional body modeling optimization method according to any one of claims 1 to 5 when executing the computer program.
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