CN104537183A - Pressure garment based on non-contact-type body scan and body common-even morphing algorithm - Google Patents

Pressure garment based on non-contact-type body scan and body common-even morphing algorithm Download PDF

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Publication number
CN104537183A
CN104537183A CN201510009299.1A CN201510009299A CN104537183A CN 104537183 A CN104537183 A CN 104537183A CN 201510009299 A CN201510009299 A CN 201510009299A CN 104537183 A CN104537183 A CN 104537183A
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China
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level
data point
point set
girth
pressure suits
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CN201510009299.1A
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王永荣
王云仪
王革辉
王敏
朱力甦
胡青云
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Donghua University
National Dong Hwa University
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Donghua University
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Abstract

The invention relates to a pressure garment based on a non-contact-type body scan and a body common-even morphing calculating method. Three-dimensional point cloud data of a human body surface without the pressure garment or with the pressure garment is obtained through a non-contact-type three-dimensional body scanner. The three-dimensional point data is converted into two-dimensional point data. The circumferences and the areas of all of girth cross sections are obtained through fourier series fit curve function. The difference between the circumferences and the areas of all of the girth cross sections with the pressure garment and the circumferences and the areas of all of the girth cross sections without the pressure garment are calculated. Therefore, a common-even deformation is obtained. According to the theory, a suit of the pressure garment and the human body common-even morphing calculating method are established. According to the practical application point of view, the pressure garment based on the non-contact-type body scan and the body common-even morphing algorithm are beneficial to the optimized design for the pressure garment such as a pressure medical stocking, the guidance for the clinic treatment on venous diseases, and the representation of the functions of the pressure garment.

Description

Based on pressure suits and the human body even deformation algorithm altogether of contactless humanbody scanning
Technical field
The present invention relates to the computing method of a kind of pressure suits based on non-contact 3-D body scans and the common mutation shape of human body, be applicable to various pressure suits and comprise leotard trousers, body shaping wear, compression medical socks, pressure bandage etc.
Background technology
Pressure suits, namely can produce the clothes of pressure at the privileged site of human body.Comprise there is chest enlarge, draw the abdomen, carry stern and U.S. leg-training effect body shaping wear; Have and improve lower limb blood circulation, the medical socks of alleviation and treatment venous disease function and bandage; There is microcirculation in promotion body, weaken muscle vibrations initiation energy loss, strengthen the leotard trousers of motion function as riding apparel etc.
Pressure suits are less than the clean body size of human body, wear the stretcher strain produced after human body in various degree, the generation in bond of human body corresponding site is necessarily compressed and metamorphosis, and pressure suits and human body fit tightly in interaction and reach a kind of common deformation degree, are namely defined as common mutation shape.Altogether mutation shape is not only relevant, also relevant with hypodermis mechanical property with human figure, anatomical structure and skin with the fabric performance of pressure suits, apparel construction.Altogether mutation shape will be the important direct or indirect evaluation index that pressure suits evaluate its body shaping, medical treatment, motion effect and human body comfort.
At present, in body shaping, the three-dimensional dimension change after having researcher to adopt contact type measurement human body to wear body modelling dress; Adopting the state before and after non-contact 3-D scanner scanning human body dress body shaping clothes, comprising girth, thickness and width, for characterizing slimming effect by the change in size in CAD software different degree of enclosing cross section as Geomagic, AUTOCAD etc. obtain.But contact type measurement error is large; CAD software is large based on tri patch acquisition of information degree of enclosing profile and actual variance, and can only obtain finite character cross section profile.Have researcher to adopt piecewise polynomial fitting leg profile curve at the same degree of enclosing of human body, fitting precision is subject to segmentation position and restricted number, and calculated amount is not suitable for greatly the contour curve matching that leg encloses degree more.Mentioning and correlative study in common mutation shape is not had in medical socks and leotard.Compression medical socks treatment venous disease depends on its constraint compression to human leg, and the common mutation shape indirectly-acting that this constraint compression causes, in Venous leg blood vessel, promotes venous return.Therefore, the calculating of even deflection contributes to the functional sign of perfect medical socks altogether.
Summary of the invention
In order to overcome above-mentioned the deficiencies in the prior art, the object of this invention is to provide the computing method of a kind of pressure suits based on non-contact 3-D body scans and the common mutation shape of human body.
In order to achieve the above object, technical scheme of the present invention there is provided a kind of pressure suits based on contactless humanbody scanning and human body even deformation algorithm altogether, comprises the steps:
Step 1, obtained the three dimensional point cloud not wearing human body target site under pressure suits state by non-contact 3-D body scans instrument, remove the data point irrelevant with this target site and noise thus form three-dimensional data point set:
Step 2, three-dimensional data point set is carried out layering on human height direction, and set the level attributes of every one deck, thus three-dimensional data point set is converted into target site various level 2-D data point set;
Step 3, to concentrate at the 2-D data point of each level, adopt fourier series to carry out the contour curve in matching cross section;
Step 4, the girth being calculated the contour curve of each level of not wearing under pressure suits state by fourier series matched curve function and area;
Step 5, wear pressure suits after, to utilize and step 1 to calculate girth and the area of the contour curve of each level of wearing under pressure suits state to the step that step 4 is identical;
The girth of contour curve of step 6, the girth calculating the contour curve of each level of not wearing under pressure suits state and area and the corresponding level of wearing under pressure suits state and the difference of area, thus draw common even deflection.
Preferably, in described step 2, step three-dimensional data point set being converted into target site various level 2-D data point set comprises:
Three-dimensional data point set comprises the three-dimensional rectangular coordinate (x, y, z) of each point, with human height direction for z-axis, carry out coordinate system transformation, be converted into cylindrical coordinates (r, θ, z), three-dimensional data point set is carried out layering in z-axis direction, from elemental height z 1start to be divided into a level every height Δ z, thus three-dimensional data point set is converted into target site various level 2-D data point set.
Preferably, in described step 3, in jth level, the matched curve of target site degree of enclosing cross section profile is r (θ, z j), then have:
r ( θ , z j ) = a 0 + Σ i = 1 n ( a i · cos ( i · θ ) + b i · sin ( i · θ ) ) , In formula, a 0, a i, b ibe the coefficient of fourier series, the larger then fitting precision of exponent number n of fourier series is larger.
Preferably, in described step 4, the girth of the contour curve of jth level is C (z j), then have:
C ( z j ) = ∫ 0 2 π r 2 ( θ , z j ) + r ′ 2 ( θ , z j ) dθ , In formula; R ' (θ, z j) be r (θ, z j) first order derivative;
The area of the contour curve of jth level is S (z j), then have:
S ( z j ) = ∫ 0 2 π 1 2 · r 2 ( θ , z j ) dθ .
The present invention obtains the three dimensional point cloud not wearing/wear body surface under pressure suits state by non-contact 3-D body scans instrument, transfer three-dimensional point data to two-dimensional points data again, girth and the area in respectively degree of enclosing cross section is obtained again by fourier series matched curve function, calculate and do not wear pressure suits and wear the girth of pressure suits in each degree of enclosing cross section and area difference, thus draw common even deflection.
The present invention sees theoretically, establishes the computing method of a set of pressure suits and the common mutation shape of human body; From the angle of practical application, contribute to optimal design pressure suits as compression medical socks, guiding clinical treatment venous disease, contribute to pressure suits functional characterization.
Embodiment
Below in conjunction with specific embodiment, set forth the present invention further.Should be understood that these embodiments are only not used in for illustration of the present invention to limit the scope of the invention.In addition should be understood that those skilled in the art can make various changes or modifications the present invention, and these equivalent form of values fall within the application's appended claims limited range equally after the content of having read the present invention's instruction.
Embodiments of the present invention relate to the computing method of a kind of pressure suits based on non-contact 3-D body scans and the common mutation shape of human body, and human body target position, for right leg, comprises the steps:
Step 1, obtained the three dimensional point cloud not wearing the right leg position of human body under pressure suits state by non-contact 3-D body scans instrument, comprise the three-dimensional rectangular coordinate value (x of each point, y, z), even deflection altogether will be calculated with right leg, therefore remove the data point irrelevant with right leg and noise, thus form three-dimensional (3D) data point set.
Step 2, with human height direction for z-axis, carry out coordinate system transformation, three-dimensional rectangular coordinate (x, y, z) be converted into cylindrical coordinates (r, θ, z).Ankle position is carried out layering to three-dimensional (3D) data point set at thigh position in z-axis direction, is z from z=100mm beginning label j(j=1,2,3 ...), choose every height Δ z=10mm, thus three-dimensional (3D) data point set is converted into right leg position various level two dimension (2D) data point set.
Step 3, concentrate at the 2-D data point of each level, adopt fourier series to carry out the contour curve in matching cross section, in jth level, the matched curve of target site degree of enclosing cross section profile is r (θ, z j), then have:
r ( θ , z j ) = a 0 + Σ i = 1 n ( a i · cos ( i · θ ) + b i · sin ( i · θ ) ) , In formula, a 0, a i, b ibe the coefficient of fourier series, the larger then fitting precision of exponent number n of fourier series is larger, and a preferred version is: n>=5, in the present embodiment, and n=7.
Step 4, the girth being calculated the contour curve of each level of not wearing under pressure suits state by fourier series matched curve function and area.The girth of the contour curve under the pressure suits state of not wearing of jth level is C u(z j), then have:
C ( z j ) = ∫ 0 2 π r 2 ( θ , z j ) + r ′ 2 ( θ , z j ) dθ , In formula; R ' (θ, z j) be r (θ, z j) first order derivative;
The area of the contour curve under the pressure suits state of not wearing of jth level is S u(z j), then have:
S u ( z j ) = ∫ 0 2 π 1 2 · r 2 ( θ , z j ) dθ .
Step 5, wear pressure suits after, to utilize and step 1 to calculate the girth C of the contour curve of each level of wearing under pressure suits state to the step that step 4 is identical w(z j) and area S w(z j).
The common mutation shape at step 6, calculating pressure clothes and human contact position.In each level, calculate and do not wear pressure suits and girth and the area difference of wearing pressure suits, namely in each level, the common even deflection at pressure suits and human contact position comprises girth difference and area difference, and wherein, the girth difference of jth level is Δ C (z j), the area difference of jth level is Δ S (z j), then there is Δ C (z j)=C u(z j)-C w(z j), Δ S (z j)=S u(z j)-S w(z j).
The present invention is further illustrated below with specific embodiment.
1. obtain cloud data by non-contact 3-D body scans
Volunteer does not wear/wears compression medical socks, by [TC] at the bottom right leg that instructs of experimental implementation person 2contactless humanbody three-dimensional scanner system scans, and obtains body surface 3 d scan data, saves as * .wrl file layout.[TC] 2beam scanner system scans the * .wrl file obtained and somatic data is divided into seven parts: Right Leg_FACES01, Left Leg_FACES01, Torso_FACES01, Left Arm_FACES01, Left Hand_FACES01, Right Arm_FACES01, Right Hand_FACES01, this seven part is all the three dimensional point cloud of human body surface, comprises the D coordinates value of each point.Choose the cloud data of right leg (RightLeg_FACES01).
The cloud data of 3D is carried out 2Dization process, namely from z in its z-axis direction layering 1=100mm starts, and gets Section Point Cloud data every 10mm.
2., in every level 2D data point set, adopt fourier series to carry out matching
Cylindrical coordinate is tied to every layer data conversion rectangular coordinate, in order to ensure the inside of coordinate origin at every layer of closed curve, carries out the translation of true origin.In every layer data, adopt 7 rank fourier series to carry out matching, under the state of not wearing compression medical socks, from z 1=100mm ..., z 60coefficient and the fitting correlation coefficient of=690mm are as follows:
Under wearing compression medical sock state, from z 1=100mm ..., z 60coefficient and the fitting correlation coefficient of=690mm are as follows:
3. calculate the common mutation shape of every level sectional profile curve lin
Calculate the perimeter value of each sectional profile curve lin, the girth difference under not wearing compression medical socks and wearing compression medical socks is as following table.
Calculate the area value of each sectional profile curve lin, the area difference under not wearing compression medical socks and wearing compression medical socks is shown as follows.

Claims (4)

1., based on pressure suits and the human body even deformation algorithm altogether of contactless humanbody scanning, comprise the steps:
Step 1, obtained the three dimensional point cloud not wearing human body target site under pressure suits state by non-contact 3-D body scans instrument, remove the data point irrelevant with this target site and noise thus form three-dimensional data point set, it is characterized in that:
Step 2, three-dimensional data point set is carried out layering on human height direction, and set the level attributes of every one deck, thus three-dimensional data point set is converted into target site various level 2-D data point set;
Step 3, to concentrate at the 2-D data point of each level, adopt fourier series to carry out the contour curve in matching cross section;
Step 4, the girth being calculated the contour curve of each level of not wearing under pressure suits state by fourier series matched curve function and area;
Step 5, wear pressure suits after, to utilize and step 1 to calculate girth and the area of the contour curve of each level of wearing under pressure suits state to the step that step 4 is identical;
The girth of contour curve of step 6, the girth calculating the contour curve of each level of not wearing under pressure suits state and area and the corresponding level of wearing under pressure suits state and the difference of area, thus draw common even deflection.
2. as claimed in claim 1 a kind of based on contactless humanbody scanning pressure suits and human body even deformation algorithm altogether, it is characterized in that: in described step 2, step three-dimensional data point set being converted into target site various level 2-D data point set comprises:
Three-dimensional data point set comprises the three-dimensional rectangular coordinate (x, y, z) of each point, with human height direction for z-axis, carry out coordinate system transformation, be converted into cylindrical coordinates (r, θ, z), three-dimensional data point set is carried out layering in z-axis direction, from elemental height z 1start to be divided into a level every height Δ z, thus three-dimensional data point set is converted into target site various level 2-D data point set.
3. as claimed in claim 1 a kind of based on contactless humanbody scanning pressure suits and human body even deformation algorithm altogether, it is characterized in that: in described step 3, in jth level, the matched curve of target site degree of enclosing cross section profile is r (θ, z j), then have:
r ( θ , z j ) = a 0 + Σ i = 1 n ( a i · cos ( i · θ ) + b i · sin ( i · θ ) ) , In formula, a 0, a i, b ibe the coefficient of fourier series, the larger then fitting precision of exponent number n of fourier series is larger.
4. as claimed in claim 1 a kind of based on contactless humanbody scanning pressure suits and human body even deformation algorithm altogether, it is characterized in that: in described step 4, the girth of the contour curve of jth level is C (z j), then have:
in formula; R ' (θ, z j) be r (θ, z j) first order derivative;
The area of the contour curve of jth level is S (z j), then have:
S ( z j ) = ∫ 0 2 π 1 2 · r 2 ( θ , z j ) dθ .
CN201510009299.1A 2015-01-08 2015-01-08 Pressure garment based on non-contact-type body scan and body common-even morphing algorithm Pending CN104537183A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106372344A (en) * 2016-09-05 2017-02-01 中山大学 Three-dimensional clothes transformation method based on feature size constrain and system thereof
CN110276121A (en) * 2019-06-18 2019-09-24 浙江理工大学 A kind of measurement method of dynamic dressing gap value

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106372344A (en) * 2016-09-05 2017-02-01 中山大学 Three-dimensional clothes transformation method based on feature size constrain and system thereof
CN110276121A (en) * 2019-06-18 2019-09-24 浙江理工大学 A kind of measurement method of dynamic dressing gap value

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