CN106780619A - A kind of human body dimension measurement method based on Kinect depth cameras - Google Patents
A kind of human body dimension measurement method based on Kinect depth cameras Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/30196—Human being; Person
Abstract
The invention discloses a kind of measuring method of the human dimension based on Kinect depth cameras, belong to technical field of machine vision；It is comprised the steps of：(1), depth camera is demarcated；Original depth image is up-sampled, can realize that automatically extracting angle point information completes to demarcate by OpenCV；(2), depth image treatment；Using joint bilateral filtering algorithm, depth image quality is lifted using high-resolution coloured image, reduce the noise jamming in depth image；(3), the fusion of point cloud and skeleton point acquisition of information；(4), human dimension is calculated.While reducing system cost, it is ensured that the required precision of custom made clothing, make characteristics of human body's recognizer simpler using human body skeleton point information, effectively increase the operational efficiency of software systems.
Description
Technical field
The invention belongs to field of machine vision, it is related to a kind of 3 D human body key feature chi based on Kinect depth cameras
Very little measuring method, can be applied to the aspects such as intelligent clothing customization, internet electronic fitting.
Background technology
Comply with internet+the tendency of the day, the industry such as computer, clothes manufacture sale industry, video display animation is just quick
To intelligent development, many enterprises, teaching, scientific research institution are increasing to somatometric demand, 3D anthropometric scanning application
Field it is more and more extensive.Meanwhile, 3D anthropometric scanning technology will change the operational mode of many traditional industries.
At present, conventional three-dimensional body dimension metering system have three-dimensional human body measurement systems using 16 Asus Xtion,
Use the static measuring system and the measuring system of 3D anthropometric scanning instrument of 3 Kinect.16 measuring system costs of Xtion
High and precision is low, the measuring system price of 3 Kinect is high, and 3D anthropometric scanning instrument price is even more up to hundreds of thousands, and price is held high
It is expensive.And the present invention only needs a Kinect and the rotating disk just can to reach the requirement of custom made clothing.
In terms of positioning, traditional measurement mode judges whether it is bifurcation and judgement using Y-axis section by calculating angle
There is algorithm complexity, the low problem of efficiency in the methods such as the algorithm positioning perineum of the number of closed geometry figure, armpit.Microsoft
The Kinect depth cameras of release can calculate 25 human body key skeleton point positions by depth image.The present invention utilizes bone
Bone point information determines some key feature reference positions, and three numerical characteristics of axle according to the point accurately determine characteristics of human body
Position simultaneously calculates human dimension, and algorithm is simpler, in hgher efficiency, and it is more accurate to position.
The content of the invention
It is an object of the invention to provide a kind of 3 D human body critical size measuring method based on Kinect depth cameras, solution
Body scans low precision present in prior art of having determined is high with system cost, and part characteristics of human body recognizes difficult and human body chi
Very little computation complexity problem high.
To achieve the above object, the present invention and configures one first by single Kinect depth cameras as scanning device
Portion's rotating disk, to realize scanning of the single depth camera to human body, effectively reduces the hardware cost of system；Secondly human body is being obtained
The skeleton point cloud data of human body initial attitude is obtained while cloud data, for passing through in human body dimension measurement module
Skeleton point determines some characteristics of human body positions, improves the computational efficiency of the system.
To improve scanning accuracy, Kinect depth cameras are demarcated first, depth camera is demarcated primarily to really
Determine the intrinsic parameter and distortion factor of camera, distortion correction can be carried out to the depth image for getting after each parameter determination.
Secondly depth image is processed, including depth image data analysis, the visualization and enhancing of depth data
The related contents such as treatment, to improve the quality of depth image.
Then point cloud chart picture is obtained using the depth image after treatment, and will be adjacent using ICP (iteration closest approach) algorithm
Point cloud chart picture carries out registration, so that coordinate system residing for the first amplitude point cloud image is as world coordinate system and carries out a cloud fusion.Obtaining
Take point cloud chart as while, obtain the crucial skeleton point point cloud information of human body initial attitude, it is crucial with quick obtaining part human body
Feature.
Finally, this method human body data cloud is pre-processed using the skeleton point information for getting, to human body
Four limbs are split, fast searching human body key feature；It is transversely to the machine direction respectively on human body point cloud model flat with level
Row section, analyzes section feature, and layering dividing processing is carried out to three-dimensional (3 D) manikin automatically according to section feature；It is determined that based on clothes
The measurement index of system is set, each characteristics of human body of automatic identification calculates human dimension.
The present invention compared with art methods, while reducing system cost, it is ensured that the precision of custom made clothing will
Ask, make characteristics of human body's recognizer simpler using human body skeleton point information, effectively increase the operational efficiency of software systems.
Brief description of the drawings
Fig. 1 is first kind feature point diagram of the present invention；
Fig. 2 is Equations of The Second Kind feature point diagram of the present invention；
Fig. 3 is present system flow chart；
Fig. 4 is present invention point cloud fusion flow chart；
Fig. 5 is the postrotational point cloud chart of left arm of the present invention；
Fig. 6 is the section line figure before convex closure computing of the present invention；
Fig. 7 is the line drawing after convex closure computing of the present invention；
Fig. 8 is armpit schematic cross-section；
Fig. 9 is the skeleton point in original point cloud chart；
Specific embodiment
The present invention is described in detail with reference to the accompanying drawings and detailed description.
The entire protocol of the inventive method includes：
1. depth camera is demarcated
Demarcated using Zhang Shi standardizations, the depth image of multiple different angles is obtained using Kinect depth cameras.To original
Beginning depth image is up-sampled, and depth image resolution ratio is improved, in order to extracted with high accuracy angle point.By on scaling board each
Corresponding relation between the picture point of characteristic point and its image plane, i.e., complete to demarcate by every homography matrix of image, can pass through
OpenCV realizes that automatically extracting angle point information completes to demarcate.
2. depth image treatment
Using joint bilateral filtering algorithm, depth image quality is strengthened using high-resolution coloured image, subtracted
Noise jamming in few depth image.
3. a cloud is merged and skeleton point acquisition of information
Adjacent point cloud chart picture is carried out into registration using ICP (iteration closest approach) algorithms, is calculated residing for a certain amplitude point cloud image
Coordinate system shoots each width relative to the spin matrix and translation vector of previous adjacent point cloud chart coordinate system as residing for obtain
The relative attitude of the camera of point cloud chart picture, and using coordinate system residing for the first amplitude point cloud image as human body point cloud model after fusion
Coordinate system, carries out the fusion of cloud, obtain point cloud chart as while, obtain the crucial skeleton point point cloud letter of human body initial attitude
Breath, with fast searching to human body key feature.Point cloud fusion flow chart is as shown in figure 4, skeleton point such as Fig. 9 in original point cloud chart
It is shown.
4. human dimension is calculated
1) pre-process
The following noise of removal foot：The point cloud that x coordinate value is approximately equal to the x values of crown point is found, y values is carried out from big to small
Sequence, calculates the y value differences of former and later two points, and the y values of less that point are ground wherein in corresponding two points of largest interval
The y values in face, remove below foot and put cloud on this basis.
2) rigid body translation of 3 D human body point cloud
So that, for X-axis is positive, top is positive Y-axis on the left of human body, front is oriented Z axis forward direction, and sole is XOZ planes, is entered
The rigid body translation of row point cloud.
Q=RS+T
Q is the human body point cloud matrix after rigid body translation, and S is original human body point cloud matrix, and R is the spin matrix of 3*3,
T is the translation vector of 3*1.
Method based on skeleton point translation rotation human body
Because kinect is uncertain with the relative position of human body, the human body data cloud that fusion is produced can be caused in coordinate system
In position do not know.
It with the data of the skeleton point obtained from kinect is foundation that this method is, the data to cloud data and skeleton point are entered
Row rigid body translation, by the human body point Cloud transform of certain position in coordinate system to a kind of position of standard, in order to follow-up people
Body dimensional measurement.
The process of conversion is foundation skeleton point, calculates the angle of skeleton point and reference axis, and all skeleton points and coordinate
The relative position of origin, and in this, as the parameter of rigid body translation, during manikin and all skeleton points transformed into coordinate system
Determination position.
3) human body layering
(1) human body point converge conjunction Q=(x, y, z) | x ∈ (xl,xu),y∈(yl,yu),z∈(zl,zu)}。
(2) the array QX, QY (the point cloud of said three-dimensional body) of the layering set of human body point cloud.
Wherein, QXi=(x, y, z) | and x ∈ [dx*i, dx* (i+1)), y ∈ (yl,yu),z∈(zl,zu) (parallel YOZ cuts
The point cloud in face).
QYi=(x, y, z) | x ∈ (xl,xu),y∈[dy*i,dy*(i+1)),z∈(zl,zu) (the point in parallel YOZ sections
Cloud)
Dx, dy represent interlamellar spacing, and l represents lower bound, and u represents the upper bound.
So far, three-dimensional point set changes into the array QX, QY of multiple two-dimensional section collection.
4) human body segmentation
For the human body point cloud chart by above-mentioned treatment.We need to extract following first kind characteristic point for human body point
Cut.
First kind characteristic point：P1(perineum point), P2(left armpit point), P3(right armpit point), P4(left acromion point), P5(right shoulder
Peak dot), P6(left SNP SIDE NECK POINT), P7(right SNP SIDE NECK POINT).
First kind characteristic point acquisition methods
After determining perineum point and armpit point general location and x coordinate value bound using skeleton point, according to multiple human bodies
Longitudinal section QXi, dimensionality reduction operation is carried out to each intersecting surface.Operation result is synthesized into a point set, dimensionality reduction is carried out to point set again
Operation just can obtain perineum point and armpit point.And acromion point and SNP SIDE NECK POINT equally can be according to human body point cloud intersecting surface and the points
The corresponding dimensionality reduction operation of characteristic use is obtained.First kind feature point extraction result is as shown in Figure 1.
Dimensionality reduction operation is as follows,
Computing of the point set of one dimensional line to zero dimension point：
X (y/z) maximum (small) values of point set P are found and return to the point.
Computing of the point set of two-dimensional surface to zero dimension point：
The point away from reference line L closest (remote) is taken out in the point set P of two-dimensional surface and the point is returned.
The skeleton point and human body proportion that wherein each point value bound and search datum mark are obtained by kinect determine.The party
Method thinking is succinct, calculates rapid, registration.
Human body segmentation's method
Split both arms first, look for armpit point.
Travel through all of point, find out in human height's ratio 0.68 and on institute a little, operation afterwards is based on this
A little points, equivalent to the only lookup more than chest locations.
In x-axis positive direction, every very little x values scope traversal point within this range, the minimum point Y of record y-coordinateminN。
I.e. equivalent to vertical section is done, the minimum point on section is found out.
Find out [Ymin1,Ymin2…YminN] in maximum Ymax=Max { Ymin1,Ymin2…YminN, YmaxAs left armpit
The y-coordinate value of point, it is possible thereby to left armpit point is found, as shown in Figure 8.
X coordinate value according to left armpit point does vertical section segmentation left arm.Similarly in the negative semiaxis segmentation right arms of x.
Then split both legs, look for perineum point.
All of point is traveled through, the maximum point i.e. head peak of y values is found, its x value is recorded.
The y values of point of human height's ratio at 0.5 are found out, is screened out all outside this x values left and right 10cm scope, in y
It is worth the point outside upper and lower 10cm scopes.
For all points for screening, every very little x values scope traversal point within this range, record y value minimums
Point YminN。
Find out [Ymin1,Ymin2…YminN] in maximum Ymax=Max { Ymin1,Ymin2…YminN, YmaxAs perineum point
Y-coordinate value, it is possible thereby to find perineum point.
Horizontal cross-section segmentation both legs are done by the y-coordinate value of perineum point.Left and right arms can be carried out according to acromion point and armpit point
Segmentation.Left and right leg can be split according to perineum point.
So far human body segmentation is completed.Generate left leg, right leg, left arm, the point cloud of right arm and the body without left and right arms.After rotation
Left arm point cloud it is as shown in Figure 5.
5) feature location and Size calculation
With reference to GB GB1610-2008 and actual custom made clothing demand for the definition of human dimension, choose following 37
Size is calculated.
Highly：Height, cervical vertebra point is high, and left (right side) shoulder height, breastheight, waist is high, and stern is high, and perineum point is high, and left (right side) knee height is left
(right side) ankle is high.
Width：Shoulder breadth, chest breadth, waist is wide, hip breadth.
Thickness：Chest depth, waist is thick, hip depth.
Degree of enclosing：Neck circumference, bust, waistline, hip circumference, left (right side) thigh rhizosphere, left (right side) elbow encloses, left (right side) wrist circumference, left (right side)
Upper-arm circumference, left (right side) arm rhizosphere, left (right side) knee circumference, left (right side) ankle encloses.
Angle：Shoulder angle
First, we calculate Equations of The Second Kind characteristic point.
Equations of The Second Kind characteristic point：Crown point, sole point, cervical vertebra point, waist point, stern point, left (right side) wrist point, left (right side) elbow point is left
(right side) knee point, left (right side) ankle point
Equations of The Second Kind feature point calculating method
Crown point, sole point, cervical vertebra point, waist point, stern point can operate acquisition by dimensionality reduction.
Wrist point, elbow point, knee point, ankle point can be obtained by skeleton point.
Equations of The Second Kind feature point extraction result is as shown in Figure 2.Here is the computational methods of needles of various sizes.Height calculation method
Height calculation results are the corresponding height (y-coordinate value) of its characteristic point.
Width calculation method
Shoulder breadthWherein L (pix,piZ) ＜ 0, PiIt is by SPL, SPR, 3 points of CerP determined
Characteristic face by the orderly point after G (convex closure) computing.Wherein, SPLIt is left acromion point, SPRIt is right acromion point, CerP is cervical vertebra
Point, L represents SPL, SPR2 points of plane and straight line equations for being determined, piX, piZ represents PiX coordinate and z coordinate.
Remaining width calculation result is the width (x directions minimax value difference) of characteristic face where its characteristic point.
THICKNESS CALCULATION method
Thickness calculations are the thickness (z directions minimax value difference) of characteristic face where its characteristic point.Degree of enclosing calculating side
Method
Degree of enclosing result of calculation is G (convex closure) operation result of characteristic face where its characteristic point, and wherein G operation is as follows.
The method that degree of enclosing is calculated by characteristic face：
(I) determine to carry out required result medium filtering or mean filter or do not filter according to required position
(II) one-dimensional profile line is asked for using algorithm of convex hull
The point of required intersecting surface is processed first with algorithm of convex hull, so as to remove internal point, only retains peripheral point
Point converge conjunction, exclude internal noise interference, the tight state of tape during the real measurement of simulation reduces measurement error.So far,
One-dimensional profile line is obtained by two-dimensional surface.Convex closure effect such as Fig. 6, shown in 7.
(III) cubic spline interpolation fitting is carried out to result so that contour line is more smoothed
(IV) ask for enclosing length
It is that the point from characteristic point to converge appoint in conjunction and takes one to enclose long mode of asking at unordered when being in a cloud contour line
Result is initialized as 0 by individual point as current point, and then greed selects the point nearest from current point, and asks between 2 points
Distance is added in result, the current point put as greed selection next time that greed selection is obtained, iteration the method, Zhi Daoji
All of point is calculated.Last o'clock to first distance of point is finally calculated, and the distance is added in result.
When step (I) algorithm of convex hull uses Garham ' s Scan algorithms to carry out convex closure, institute's invocation point cloud is orderly point cloud,
The current point of Garham ' s Scan institutes invocation point cloud and the distance of next point can be directly calculated, using next point as current point,
Iteration this step.Last o'clock to first distance of point is finally calculated, and the distance is added in result.So can be with profit
Avoid seeking a cloud again sequence so as to improve arithmetic speed with Garham ' s Scan algorithmic characteristics.
Angle computation method
Left shoulder angle
Wherein NRPLxIt is left SNP SIDE NECK POINT x coordinate value, NRPLyIt is left SNP SIDE NECK POINT y-coordinate value, SPLxIt is left acromion point x coordinate
Value, SPLyIt is left acromion point y-coordinate value.
Error analysis：
In 1cm, angular error meets the requirement of custom made clothing to scale error within 5 degree.
The standard deviation of error measures stability in tolerance interval with preferable.
Claims (2)
1. a kind of measuring method of the human dimension based on Kinect depth cameras, it is characterised in that it is comprised the steps of：
(1), depth camera is demarcated
Demarcated using Zhang Shi standardizations, the depth image of multiple different angles is obtained using Kinect depth cameras.To original depth
Degree image is up-sampled, and image resolution ratio is improved, in order to extracted with high accuracy angle point；By each characteristic point on scaling board and
Corresponding relation between the picture point of its image plane, i.e., complete to demarcate by every homography matrix of image, can be by OpenCV realities
Angle point information is now automatically extracted to complete to demarcate；
(2), depth image treatment
Using joint bilateral filtering algorithm, depth image quality is lifted using high-resolution coloured image, reduced deep
Noise jamming in degree image；
(3), the fusion of point cloud and skeleton point acquisition of information
Adjacent point cloud chart picture is carried out into registration using ICP algorithm, coordinate system residing for a certain amplitude point cloud image is calculated relative to previous
The spin matrix and translation vector of adjacent point cloud chart coordinate system as residing for, the camera of each amplitude point cloud image is shot to obtain
Relative attitude, and a cloud, as the coordinate system of human body point cloud model after fusion, is carried out using coordinate system residing for the first amplitude point cloud image
Fusion.Obtain point cloud chart as while, obtain human body initial attitude crucial skeleton point point cloud information, with fast searching to people
Body key feature.
(4), human dimension is calculated.
2. a kind of measuring method of human dimension based on Kinect depth cameras according to claim 1, its feature exists
In its principle：Turn as scanning device, and configuration one first by the Kinect depth cameras that single Microsoft releases
Disk, to realize scanning of the single depth camera to human body, effectively reduces the hardware cost of system；Secondly human body point cloud is being obtained
The skeleton point cloud data of human body initial attitude is got while data, for passing through bone in human body dimension measurement module
Bone point determines some characteristics of human body positions, improves the computational efficiency of software systems；
To improve scanning accuracy, Kinect depth cameras are demarcated first, depth camera is demarcated primarily to determining phase
The intrinsic parameter and distortion factor of machine, distortion correction can be carried out after each parameter determination to the depth image for getting；
Secondly depth image is processed, including depth image data analysis, depth data visualization and enhancing treatment
Etc. related content, to improve the quality of depth image；
Then point cloud chart picture is obtained using the depth image after treatment, and adjacent point cloud chart picture is carried out into registration using ICP algorithm,
So that coordinate system residing for the first amplitude point cloud image is as world coordinate system and carries out a cloud fusion；Obtain point cloud chart as while,
The crucial skeleton point point cloud information of human body initial attitude is obtained, with fast searching to human body key feature；
Finally, this method human body data cloud is pre-processed using the skeleton point information for getting, to human limb
Split, fast searching human body key feature；Made on the longitudinal direction of human body point cloud model a large amount of decile distances perpendicular to
The parallel cut of longitudinal direction, analyzes section feature, and layered shaping is carried out to three-dimensional (3 D) manikin automatically according to section feature；Determine base
In the measurement index of custom made clothing, each characteristics of human body of automatic identification calculates human dimension.
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