CN111445570B

CN111445570B - Customized garment design production equipment and method

Info

Publication number: CN111445570B
Application number: CN202010156499.0A
Authority: CN
Inventors: 左忠斌; 左达宇
Original assignee: Tianmu Aishi Beijing Technology Co Ltd
Current assignee: Tianmu Aishi Beijing Technology Co Ltd
Priority date: 2020-03-09
Filing date: 2020-03-09
Publication date: 2021-04-27
Anticipated expiration: 2040-03-09
Also published as: CN111445570A

Abstract

The embodiment of the invention provides a garment design device and method based on three-dimensional data, which comprises a human body three-dimensional data acquisition device, a three-dimensional model synthesis device and a three-dimensional model generation device, wherein the human body three-dimensional data acquisition device is used for acquiring a plurality of images of a human body and synthesizing a human body three-dimensional model by utilizing the images; the three-dimensional data acquisition device comprises an image acquisition device, and when the image acquisition device acquires a target object, two adjacent acquisition positions meet a preset condition. It is proposed for the first time to improve both the 3D synthesis speed and the synthesis precision by increasing the way in which the background plate rotates along with the camera in the clothing design apparatus, thereby reducing the waiting time so that the human body data can be more accurately used for clothing design.

Description

Customized garment design production equipment and method

Technical Field

The invention relates to the technical field of garment design, in particular to the field of garment design realized through a 3D appearance measurement technology.

Background

Currently, many solutions for custom-made garment design using three-dimensional customer data have emerged. The following solutions are mainly used: 1. with the structured light scheme, visible light or infrared light needs to be emitted to a human body, causing discomfort to a customer and requiring complicated calibration. 2. Machine vision is adopted, but the speed and the precision are slow.

Of course, in the prior art, it has been proposed to use empirical formulas including rotation angle, object size, and object distance to define the camera position, thereby achieving both the synthesis speed and the effect. However, in practical applications it is found that: unless a precise angle measuring device is provided, the user is insensitive to the angle and is difficult to accurately determine the angle; the size of the target is difficult to accurately determine, and particularly, the target needs to be frequently replaced in certain application occasions, each measurement brings a large amount of extra workload, and professional equipment is needed to accurately measure irregular targets. The measured error causes the camera position setting error, thereby influencing the acquisition and synthesis speed and effect; accuracy and speed need to be further improved.

Therefore, the following technical problems are urgently needed to be solved: the 3D synthesis speed and the synthesis precision can be improved simultaneously, and the reliability of basic data of clothing design is improved; low cost and no increase of complexity of equipment. Accurate garment processing data can be provided for customers, and personalized customization is realized.

Disclosure of Invention

In view of the above, the present invention has been developed to provide a garment design apparatus and method that overcomes, or at least partially solves, the above-identified problems.

The embodiment of the invention provides a garment design device and method based on three-dimensional data, which comprises a human body three-dimensional data acquisition device, a three-dimensional model synthesis device and a three-dimensional model generation device, wherein the human body three-dimensional data acquisition device is used for acquiring a plurality of images of a human body and synthesizing a human body three-dimensional model by utilizing the images;

the three-dimensional data acquisition device comprises an image acquisition device, and when the image acquisition device acquires a target object, two adjacent acquisition positions meet the following conditions:

wherein L is the linear distance between the optical centers of the two position image acquisition devices; f is the focal length of the image acquisition device; d is the rectangular length of the photosensitive element of the image acquisition device; t is the distance from the photosensitive element of the image acquisition device to the surface of the target along the optical axis; δ is the adjustment coefficient.

In alternative embodiments, δ <0.571, or δ <0.405, or δ <0.338, or δ < 0.296.

In an alternative embodiment, there are at least two image capturing devices.

In an alternative embodiment, at least two image capture devices are vertically aligned.

In an optional embodiment, the garment design device is further included for determining garment three-dimensional data by using the human body three-dimensional model.

In an alternative embodiment, the garment design device operates as follows: dividing points, lines and/or planes of a three-dimensional model of a human body according to the clothing design requirements; and secondly, generating final three-dimensional data of the garment according to the sizes of the points, the lines and/or the surfaces.

In an alternative embodiment, the method further comprises generating a two-dimensional cutting template from the three-dimensional data of the final garment.

In an optional embodiment, the final three-dimensional garment data is obtained by modifying on the basis of the standard three-dimensional garment data in operation two.

Another embodiment of the present invention further provides a three-dimensional garment database, which is obtained and stored by using the apparatus and method as claimed in any one of the above claims.

In an alternative embodiment, there is a customer private space for storing customer corresponding data.

Invention and technical effects

1. It is proposed for the first time to improve both the 3D synthesis speed and the synthesis precision by increasing the way in which the background plate rotates along with the camera in the clothing design apparatus, thereby reducing the waiting time so that the human body data can be more accurately used for clothing design.

2. By optimizing the position of the camera during acquisition, the 3D synthesis speed and the synthesis precision can be improved simultaneously, so that the waiting time is reduced, and the human body data can be more accurately used for garment design. When the position is optimized, the angle and the head size do not need to be measured, and the device is suitable for various crowds. More convenient and strong adaptability.

3. Through the design of the vertical multi-camera structure of the acquisition equipment, the whole body data of a human body can be acquired simultaneously, the speed is higher, the distortion is smaller, and the data is more accurate.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 is a schematic structural diagram of a three-dimensional data acquisition device for a half of a human body according to an embodiment of the present invention;

fig. 2 is another schematic structural diagram of a human body whole body three-dimensional data acquisition device according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of a composite fabric provided in an embodiment of the present invention;

the correspondence of reference numerals to the respective components is as follows:

the device comprises a background plate 1, an image acquisition device 2, a rotary beam 3, a rotary device 4, a support 5, a seat 6, a base 7, a transverse column 51, a vertical column 52, a waterproof wear-resistant layer 81, a soft skin-friendly layer 82 and a middle layer 83.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Human body half three-dimensional data acquisition equipment

Referring to fig. 1, the human body three-dimensional data acquisition apparatus includes a background plate 1, an image acquisition device 2, a rotating beam 3, a rotating device 4, a support 5, a seat 6, and a base 7.

The support comprises a cross column 51 and a vertical column 52, the vertical column 52 is connected with the base 7, the cross column 51 is connected with the rotating beam 3 through the rotating device 4, and therefore the rotating beam 3 can rotate 360 degrees under the driving of the rotating device 4. The background plate 1 and the image acquisition device 2 are positioned at two ends of the rotating beam 3 and are arranged oppositely, and the rotating beam 3 rotates synchronously and always keeps opposite arrangement.

The base is provided with a seat 6, and the seat 6 is positioned between the background plate 1 and the image acquisition device 2. When the person sits down, the body is located just near the axis of rotation and between the image capture device 2 and the background plate 1, and preferably the body portion is located on the optical axis of the image capture device 2. As each person is different in height, the position of the person in the field of view of the image acquisition device 2 can be adjusted by adjusting the height of the seat 6.

The adjustable seat 6 can be connected to the base by a manual adjustment device, for example, the seat 6 is connected to the base by a screw rod, and the height of the seat is adjusted by rotating the screw rod. Preferably, the lifting driving device is in data connection with the controller, and the height of the lifting device is controlled through the controller, so that the height of the seat is adjusted. The controller may be directly connected in the garment design device, for example may be prevented from being near the seat armrest to facilitate user adjustment. The controller may also be a mobile terminal such as a cell phone. Therefore, the mobile terminal is connected with the clothes design equipment, and the height of the seat can be controlled by controlling the lifting driving device in the mobile terminal. The mobile terminal can be operated by an operator or a user, is more convenient and is not limited by position. Of course, the controller may also be assumed by the upper computer, or by the server and the cluster server. Of course, the cloud platform may also be responsible for the network. The upper computers, the servers, the cluster servers and the cloud platforms can be shared with the upper computers, the servers, the cluster servers and the cloud platforms which are used for 3D synthesis processing, and double functions of control and 3D synthesis are achieved.

If only a body part is displayed, the absolute size of each part is not required as long as the body parts are in the correct proportions. However, for matching and designing the garment, if the absolute size of the body 3D model is not available, the actual matching and designing of the garment cannot be completed, and meaningful data cannot be provided for the final processing of the garment. In order to obtain the absolute size of the body 3D information, the user's body needs to be calibrated. However, if the user directly attaches the mark to the body of the user according to the conventional method, the user experience is not good. And other positions are difficult to be pasted with the marked points. Therefore, the present invention skillfully sets the mark points on the seat 6 and records the absolute distances of the mark points from each other. When the image acquisition device 2 is rotated to the back of the user, the marking points are acquired, and the size of the 3D body model is finally calculated according to the preset distance of the marking points. Meanwhile, the mark points are arranged at the position, so that the body information acquisition of the user is not influenced. Therefore, it is one of the inventions of the present invention, and the absolute distance of the body 3D information can be obtained while the user experience can be improved. Meanwhile, the mark point may be provided on the back or the side of the seat 6 as long as the image capturing device 2 can capture the position. The marking point may be a standard gauge block, that is, a marker having a certain spatial size and a predetermined absolute size. Of course, the corresponding standard gauge block may be arranged at other positions as long as the standard gauge block is within the visual field of the camera and is still relative to the human body. For example, an article containing known marker points may be worn by the user.

The image acquisition device 2 is used for acquiring an image of a target object, and may be a CCD, a CMOS, a camera, a video camera, an industrial camera, a monitor, a camera, a mobile phone, a tablet, a notebook, a mobile terminal, a wearable device, a smart glasses, a smart watch, a smart bracelet, or all devices with an image acquisition function. The image acquisition device comprises a camera body with a photosensitive element and a lens. Preferably, the camera body may employ an industrial camera. Industrial cameras have a smaller volume and simplify unwanted functions and have better performance than home cameras. The image acquisition means 2 may be connected to the processing unit so as to transfer the acquired image to the processing unit. The connection method includes a wired method and a wireless method, and the transmission is performed by a plurality of protocols such as a data line, a network cable, an optical fiber, 4G, and 5G, wifi, for example, and it is needless to say that the transmission may be performed by using a combination of these.

The device further comprises a processor, which may also be a processing unit, for synthesizing a 3D model of the object according to the plurality of images acquired by the image acquisition means and according to a 3D synthesis algorithm, to obtain 3D information of the object.

The processing unit obtains 3D information of the object from a plurality of images in the set of images (a specific algorithm is described in detail below). The processing unit may be directly disposed in the housing where the image capturing device is located, or may be connected to the image capturing device 2 through a data line or in a wireless manner. For example, an independent computer, a server, a cluster server, or the like may be used as a processing unit, and the image data acquired by the image acquisition device 2 may be transmitted thereto to perform 3D synthesis. Meanwhile, the data of the image acquisition device 2 can be transmitted to the cloud platform, and 3D synthesis is performed by using the powerful computing capability of the cloud platform.

The background plate 1 is entirely of a solid color, or mostly (body) of a solid color. In particular, the color plate can be a white plate or a black plate, and the specific color can be selected according to the color of the object body. The background plate 1 is generally a flat plate, and preferably also a curved plate, such as a concave plate, a convex plate, a spherical plate, and even in some application scenarios, the background plate 1 with a wavy surface; the plate can also be made into various shapes, for example, three sections of planes can be spliced to form a concave shape as a whole, or a plane and a curved surface can be spliced. In addition to the shape of the surface of the background plate 1 being variable, the shape of the edge thereof may be selected as desired. Typically rectilinear, to form a rectangular plate. But in some applications the edges may be curved.

The rotating beam 3 is connected with the fixed beam through the rotating device 4, the rotating device 4 drives the rotating beam 3 to rotate, so that the background plate 1 and the image acquisition device 2 at two ends of the beam are driven to rotate, however, no matter how the background plate rotates, the image acquisition device 1 and the background plate 2 are arranged oppositely, and particularly, the optical axis of the image acquisition device 1 penetrates through the center of the background plate 2.

The light source is arranged around the lens of the image acquisition device 2, can be an LED light source and can also be an intelligent light source, namely, the light source parameters are automatically adjusted according to the conditions of the target object and the ambient light. Usually, the light sources are distributed around the lens of the image capturing device 2, for example, the light sources are ring-shaped LED lamps around the lens. When the collected object is a human body, the intensity of the light source needs to be controlled, and human discomfort is avoided. In particular, a light softening means, for example a light softening envelope, may be arranged in the light path of the light source. Or the LED surface light source is directly adopted, so that the light is soft, and the light is more uniform. Preferably, an OLED light source can be adopted, the size is smaller, the light is softer, and the flexible OLED light source has the flexible characteristic and can be attached to a curved surface. In addition, the light source may also be arranged on the housing of the rotating beam 3 carrying the image capturing device 2.

Human body whole body three-dimensional data acquisition equipment

The apparatus may be used to capture images of the upper body of a human subject to synthesize, in a processor, the upper body three-dimensional data. This data is suitable for use as upper body garments, particularly garments worn over the waist. Like this the user can measure with the position of sitting when gathering, and is more comfortable indefatigability, and can prevent that the health from rocking the measuring error who causes. However, in many cases, it is necessary to obtain three-dimensional data of the whole body, which is data below the waist even when designing a jacket, and in this case, it is necessary to simply modify the structure of the equipment.

On the basis of the above-mentioned equipment, remove the seat, set up 2 or a plurality of image acquisition devices in the one end of rotatory crossbeam 3 simultaneously. As shown in fig. 2, the plurality of image capturing devices are arranged in a vertical direction, so that the upper and lower bodies of the human body can be captured at the same time in one capturing. The field of view ranges of the plurality of image capturing devices should overlap. Although a single camera can also acquire a large range through a wide-angle lens, the wide-angle lens covers the whole body of a person. But this leads to inevitable distortion of the image edges. Therefore, in order to acquire more accurate data, two image acquisition devices can be arranged in the vertical direction and synchronously rotate. At this time, the background plate at the other end of the rotating beam 3 should also extend in the vertical direction to ensure that the background is provided for the whole human body collection.

Of course, in some cases, besides the above-mentioned devices, a handheld device may also be used to acquire human body three-dimensional information, and in this case, it may be difficult to have a specified movement track, but the movement distance still satisfies the following limit of L.

3D acquisition camera (image acquisition device) position optimization

According to a number of experiments, the separation distance of the acquisitions preferably satisfies the following empirical formula:

when 3D acquisition is performed, the positions of two adjacent image acquisition devices 2, or two adjacent acquisition positions of the image acquisition devices 2 satisfy the following conditions:

wherein L is the linear distance between the optical centers of the two image acquisition devices; f is the focal length of the image acquisition device; d is the rectangular length of a photosensitive element (CCD) of the image acquisition device; t is the distance from the photosensitive element of the image acquisition device to the surface of the target along the optical axis; δ is the adjustment factor, δ < 0.696.

When the image pickup device 2 is at any one of the two positions, the distance from the photosensitive element to the surface of the object along the optical axis is taken as T. In addition to this method, in another case, L is A_n、A_n+1Linear distance between optical centers of two image capturing devices, and A_n、A_n+1Two image acquisition devices adjacent to each other_n-1、 A_n+2Two image acquisition devices and A_n、A_n+1The distances from the respective photosensitive elements of the two image acquisition devices to the surface of the target object along the optical axis are respectively T_n-1、T_n、T_n+1、T_n+2，T＝(T_n-1+T_n+T_n+1+T_n+2)/4. Of course, the average value may be calculated by using more positions than the adjacent 4 positions.

L should be a straight-line distance between the optical centers of the two image capturing devices, but since the position of the optical center of the image capturing device is not easily determined in some cases, the center of the photosensitive element of the image capturing device, the geometric center of the image capturing device 2, the axial center of the connection between the image capturing device 2 and the pan/tilt head (or platform, support), and the center of the proximal or distal surface of the lens may be used instead in some cases, and the error caused by the displacement is found to be within an acceptable range through experiments.

In general, parameters such as object size and angle of view are used as means for estimating the position of a camera in the prior art, and the positional relationship between two cameras is also expressed in terms of angle. Because the angle is not well measured in the actual use process, it is inconvenient in the actual use. Also, the size of the object may vary with the variation of the measurement object. For example, after 3D information of an adult body is collected, a child body needs to be collected again by measuring the size and reckoning. The inconvenient measurement and the repeated measurement bring errors in measurement, thereby causing errors in camera position estimation. According to the scheme, the experience conditions required to be met by the position of the camera are given according to a large amount of experimental data, so that the problem that the measurement is difficult to accurately measure the angle is solved, and the size of an object does not need to be directly measured. In the empirical condition, d and f are both fixed parameters of the camera, and corresponding parameters can be given by a manufacturer when the camera and the lens are purchased without measurement. And T is only a straight line distance, and can be conveniently measured by using a traditional measuring method, such as a ruler and a laser range finder. Therefore, the empirical formula of the invention enables the preparation process to be convenient and fast, and simultaneously improves the arrangement accuracy of the camera position, so that the camera can be arranged in an optimized position, thereby simultaneously considering the 3D synthesis precision and speed.

From the above experimental results and a lot of experimental experiences, it can be found that the value of δ should satisfy δ <0.571, and at this time, a part of 3D models can be synthesized, although a part cannot be automatically synthesized, it is acceptable in the case of low requirements, and the part which cannot be synthesized can be compensated manually or by replacing the algorithm. Particularly, when the value of δ satisfies δ <0.405, the balance between the synthesis effect and the synthesis time can be optimally taken into consideration; δ <0.338 can be chosen for better synthesis, where the synthesis time increases but the synthesis quality is better. Of course to further enhance the synthesis effect, δ <0.296 may be selected. Whereas, when δ is 0.671, synthesis is not possible. It should be noted that the above ranges are only preferred embodiments and should not be construed as limiting the scope of protection.

Moreover, as can be seen from the above experiment, for the determination of the photographing position of the camera, only the camera parameters (focal length f, CCD size) and the distance T between the camera CCD and the object surface need to be obtained according to the above formula, which makes it easy to design and debug the device. Since the camera parameters (focal length f, CCD size) are determined at the time of purchase of the camera and are indicated in the product description, they are readily available. Therefore, the camera position can be easily calculated according to the formula without carrying out complicated view angle measurement and object size measurement. Particularly, in some occasions, the lens of the camera needs to be replaced, and then the position of the camera can be obtained by directly replacing the conventional parameter f of the lens and calculating; similarly, when different objects are collected, the measurement of the size of the object is complicated due to the different sizes of the objects. By using the method of the invention, the position of the camera can be determined more conveniently without measuring the size of the object. And the camera position determined by the invention can give consideration to both the synthesis time and the synthesis effect. Therefore, the above-described empirical condition is one of the points of the present invention.

The above data are obtained by experiments for verifying the conditions of the formula, and do not limit the invention. Without these data, the objectivity of the formula is not affected. Those skilled in the art can adjust the equipment parameters and the step details as required to perform experiments, and obtain other data which also meet the formula conditions.

3D information acquisition method flow

The object is placed between the image capturing device 2 and the background plate 1. Preferably on the extension of the rotation axis of the rotation means 4, i.e. at the centre of the circle around which the image acquisition means 2 is rotated. Therefore, the distance between the image acquisition device 2 and the target object is basically unchanged in the rotation process, so that the situation that the image acquisition is not clear due to the drastic change of the object distance or the requirement on the depth of field of the camera is too high (the cost is increased) is avoided.

When the object is the upper body of a human body, a seat 6 may be placed between the image pickup device 2 and the background plate 1, and when the human body is seated, the body is positioned just near the rotation axis and between the image pickup device 2 and the background plate 1. The height of the area to be collected is different because each person is different in height. The position of the human body in the field of view of the image acquisition device 2 can be adjusted by adjusting the height of the seat 6. In addition to adjusting the height of the seat 6, the center of the target object can be ensured to be located at the center of the field of view of the image capturing device 2 by adjusting the height of the image capturing device 2 and the height of the background plate 1 in the vertical direction. For example, the background plate 1 may be moved up and down along a first mounting post and the horizontal bracket carrying the image capturing mechanism 2 may be moved up and down along a second mounting post. Typically, the movement of the background plate 1 and the image capturing device 2 is synchronized to ensure that the optical axis of the image capturing device passes through the center position of the background plate 1.

The size of the target object is greatly different in each acquisition. If the image acquisition device 2 acquires images at the same position, the ratio of the target object in the images can be changed greatly. For example, when the size of the object a is proper in the image, if the object B is changed to be a smaller object, the proportion of the object B in the image will be very small, which greatly affects the subsequent 3D synthesis speed and accuracy. Therefore, the image acquisition device 2 can be driven to move back and forth on the horizontal support, and the proportion of the target object in the picture acquired by the image acquisition device 2 is ensured to be proper. Meanwhile, the device can adapt to users with different body sizes in a mode of adjusting the focal length. But typically the body size is relatively fixed and therefore can be achieved with a fixed focal length.

3D Synthesis Process

According to the above-described acquisition method, the image acquisition device 2 acquires a set of images of the object by moving relative to the object;

the processing unit obtains 3D information of the object according to a plurality of images in the group of images. The specific algorithm is as follows. Of course, the processing unit may be directly disposed in the housing where the image capturing device 2 is located, or may be connected to the image capturing device 2 through a data line or in a wireless manner. For example, an independent computer, a server, a cluster server, or the like may be used as a processing unit, and image data acquired by the image acquisition device may be transmitted thereto to perform 3D synthesis. Meanwhile, the data of the image acquisition device can be transmitted to the cloud platform, and 3D synthesis is performed by utilizing the strong computing power of the cloud platform.

When the collected pictures are used for 3D synthesis, the existing algorithm can be adopted, and the optimized algorithm provided by the invention can also be adopted, and the method mainly comprises the following steps:

step 1: and performing image enhancement processing on all input photos. The contrast of the original picture is enhanced and simultaneously the noise suppressed using the following filters.

In the formula: g (x, y) is the gray value of the original image at (x, y), f (x, y) is the gray value of the original image at the position after being enhanced by the Wallis filter, and m_gIs the local gray average value, s, of the original image_gIs the local standard deviation of gray scale of the original image, m_fFor the transformed image local gray scale target value, s_fTo becomeAnd converting the target value of the local gray standard deviation of the image. c belongs to (0, 1) as the expansion constant of the image variance, and b belongs to (0, 1) as the image brightness coefficient constant.

The filter can greatly enhance image texture modes of different scales in an image, so that the quantity and the precision of feature points can be improved when the point features of the image are extracted, and the reliability and the precision of a matching result are improved in photo feature matching.

Step 2: and extracting feature points of all input photos, and matching the feature points to obtain sparse feature points. And extracting and matching feature points of the photos by adopting a SURF operator. The SURF feature matching method mainly comprises three processes of feature point detection, feature point description and feature point matching. The method uses a Hessian matrix to detect characteristic points, a Box filter (Box Filters) is used for replacing second-order Gaussian filtering, an integral image is used for accelerating convolution to improve the calculation speed, and the dimension of a local image characteristic descriptor is reduced to accelerate the matching speed. The method mainly comprises the steps of firstly, constructing a Hessian matrix, generating all interest points for feature extraction, and constructing the Hessian matrix for generating stable edge points (catastrophe points) of an image; secondly, establishing scale space characteristic point positioning, comparing each pixel point processed by the Hessian matrix with 26 points in a two-dimensional image space and a scale space neighborhood, preliminarily positioning a key point, filtering the key point with weak energy and the key point with wrong positioning, and screening out a final stable characteristic point; and thirdly, determining the main direction of the characteristic points by adopting the harr wavelet characteristics in the circular neighborhood of the statistical characteristic points. In a circular neighborhood of the feature points, counting the sum of horizontal and vertical harr wavelet features of all points in a sector of 60 degrees, rotating the sector at intervals of 0.2 radian, counting the harr wavelet feature values in the region again, and taking the direction of the sector with the largest value as the main direction of the feature points; and fourthly, generating a 64-dimensional feature point description vector, and taking a 4-by-4 rectangular region block around the feature point, wherein the direction of the obtained rectangular region is along the main direction of the feature point. Each subregion counts haar wavelet features of 25 pixels in both the horizontal and vertical directions, where both the horizontal and vertical directions are relative to the principal direction. The haar wavelet features are in 4 directions of the sum of the horizontal direction value, the vertical direction value, the horizontal direction absolute value and the vertical direction absolute value, and the 4 values are used as feature vectors of each sub-block region, so that a total 4 x 4-64-dimensional vector is used as a descriptor of the Surf feature; and fifthly, matching the characteristic points, wherein the matching degree is determined by calculating the Euclidean distance between the two characteristic points, and the shorter the Euclidean distance is, the better the matching degree of the two characteristic points is.

And step 3: inputting matched feature point coordinates, resolving sparse human body three-dimensional point cloud and position and posture data of a photographing camera by using a light beam method adjustment, namely obtaining sparse human body model three-dimensional point cloud and model coordinate values of the positions; and performing multi-view photo dense matching by taking the sparse feature points as initial values to obtain dense point cloud data. The process mainly comprises four steps: stereo pair selection, depth map calculation, depth map optimization and depth map fusion. For each image in the input data set, we select a reference image to form a stereo pair for use in computing the depth map. Therefore, we can get rough depth maps of all images, which may contain noise and errors, and we use its neighborhood depth map to perform consistency check to optimize the depth map of each image. And finally, carrying out depth map fusion to obtain the three-dimensional point cloud of the whole scene.

And 4, step 4: and reconstructing the curved surface of the human body by using the dense point cloud. The method comprises the steps of defining an octree, setting a function space, creating a vector field, solving a Poisson equation and extracting an isosurface. And obtaining an integral relation between the sampling point and the indicating function according to the gradient relation, obtaining a vector field of the point cloud according to the integral relation, and calculating the approximation of the gradient field of the indicating function to form a Poisson equation. And (3) solving an approximate solution by using matrix iteration according to a Poisson equation, extracting an isosurface by adopting a moving cube algorithm, and reconstructing a model of the measured point cloud.

And 5: full-automatic texture mapping of a mannequin. And after the surface model is constructed, texture mapping is carried out. The main process comprises the following steps: texture data is obtained to reconstruct a surface triangular surface grid of a target through an image; and secondly, reconstructing the visibility analysis of the triangular surface of the model. Calculating a visible image set and an optimal reference image of each triangular surface by using the calibration information of the image; and thirdly, clustering the triangular surface to generate a texture patch. Clustering the triangular surfaces into a plurality of reference image texture patches according to the visible image set of the triangular surfaces, the optimal reference image and the neighborhood topological relation of the triangular surfaces; and fourthly, automatically sequencing the texture patches to generate texture images. And sequencing the generated texture patches according to the size relationship of the texture patches to generate a texture image with the minimum surrounding area, and obtaining the texture mapping coordinate of each triangular surface.

It should be noted that the above algorithm is an optimization algorithm of the present invention, the algorithm is matched with the image acquisition condition, and the use of the algorithm takes account of the time and quality of the synthesis, which is one of the inventions of the present invention. Of course, it can be implemented using conventional 3D synthesis algorithms in the prior art, except that the synthesis effect and speed are somewhat affected.

Garment design and manufacture

Synthesizing a three-dimensional model of a human body according to the synthesis method, and carrying out personalized clothing design on the basis of the three-dimensional model, wherein the specific method comprises the following steps:

1. and dividing the three-dimensional model of the human body into special points, lines and planes according to the clothing design requirements.

The human body reference points at least comprise an anterior cervical point, a lateral cervical point, a posterior cervical point, a shoulder endpoint, a chest height point, an anterior axillary point, a posterior axillary point, a styloid point and a lateral malleolus point. The human body datum line at least comprises a neck line, a chest line, a waist line and a hip line. The common face includes at least a front panel, a back panel, two sleeves and a neckline. However, for complex garments or more intimate garment designs, further divisions of these base surfaces are required. For example, when the front cut piece is subdivided, the front neck point, the shoulder points, the chest height point, the front axillary point and the chest circumference line can be referred to; when the rear cut piece is subdivided, reference can be made to the back neck point, the shoulder points, the rear axillary points, the chest line and the like.

2. And (4) calling the three-dimensional data of the standard garment according to the sizes of the points, lines and surfaces in the previous step.

In the three-dimensional database of the clothes, a large amount of three-dimensional data of various types of clothes, such as shirts, skirts, trousers and the like, are stored. Even if trousers are used, the trousers are divided into western style trousers, jeans, sport trousers and the like, and even can be further divided into 8-minute sport trousers and the like. The three-dimensional data for these garments may be historical data for previous garment designs. Namely, after the three-dimensional modeling is carried out on the customer each time and the design of the clothing is finished, the three-dimensional data of the final clothing and the three-dimensional data (the sizes of corresponding points, lines and surfaces) of the human body of the customer are stored in the database to become standard data. Then after the three-dimensional data of the human body of the customer is obtained, the three-dimensional data of the clothes suitable for the customer can be found according to the sizes of the midpoint, the line and the plane of the human body model. The three-dimensional data of the corresponding clothes can be selected according to the type of the clothes customized by the user. And overlaying the selected three-dimensional data of the standard clothes on the three-dimensional model of the human body, and presenting the data to an operator. Certainly, the three-dimensional human body data of each client is unique, the same human body data cannot be found at this time, and the data similar to the human body data can be called as the three-dimensional standard garment data. In addition, the database can also set a private space for the customer, so that the three-dimensional data of the clothes designed for the customer is stored in the private space every time, and the data can be directly called when the next processing or design is carried out.

3. And adjusting the three-dimensional data of the standard clothes.

There are two reasons for the adjustment: the called standard three-dimensional garment data are not completely suitable for the three-dimensional human body data of the client (because the data of two persons cannot be completely consistent). ② the clothing needs more novel design. However, for any reason, the operator can operate the three-dimensional data of the standard garment according to the sizes of the points, the lines and the surfaces, and change the corresponding local data until the requirements of the customer on the style and the size are met.

4. And generating a two-dimensional cutting template from the three-dimensional data of the final garment.

And respectively stretching the three-dimensional surface corresponding to each area of the final three-dimensional clothing data to form a plurality of two-dimensional patterns, wherein the two-dimensional patterns are a plurality of two-dimensional cutting sample plates.

5. And setting the fabric, the color and the margin of the edge joint corresponding to each sample plate.

The fabric corresponding to each sample plate can be selected according to the user preference or the garment design requirement, such as cotton, hemp, real silk, flax, mulberry silk, terylene and the like. The fabrics can be called from a database for use. And simultaneously, corresponding colors can be selected for the fabrics. And finally, setting the margin of the sewing edge according to the actual sewing requirement of the clothes.

6. And sending the sample plate data to a processing workshop for processing.

The garment material can be the existing material, and can also be designed into a composite material according to the requirement, for example, the garment material comprises three layers. As shown in fig. 3, the outermost surface is a waterproof and wear-resistant layer 81, the innermost surface is a soft skin-friendly layer 82, and an intermediate layer 83 is arranged between the two layers. The middle layer can be an air layer for preventing heat loss. Heating fibers may also be provided to actively heat the garment.

In another embodiment, the middle layer is connected with the cold and hot air blower, so that the temperature of the fabric can be adjusted through the control of the cold and hot air blower, and the clothing with variable temperature is provided for a user.

The rotation movement of the invention is that the front position collection plane and the back position collection plane are crossed but not parallel in the collection process, or the optical axis of the front position image collection device and the optical axis of the back position image collection device are crossed but not parallel. That is, the capture area of the image capture device moves around or partially around the target, both of which can be considered as relative rotation. Although the embodiment of the present invention exemplifies more orbital rotation, it should be understood that the limitation of the present invention can be used as long as the non-parallel motion between the acquisition region of the image acquisition device and the target object is rotation. The scope of the invention is not limited to the embodiment with track rotation.

The adjacent acquisition positions refer to two adjacent positions on a movement track where acquisition actions occur when the image acquisition device moves relative to a target object. This is generally easily understood for the image acquisition device movements. However, when the target object moves to cause relative movement between the two, the movement of the target object should be converted into the movement of the target object, which is still, and the image capturing device moves according to the relativity of the movement. And then measuring two adjacent positions of the image acquisition device in the converted movement track.

The target object, and the object all represent objects for which three-dimensional information is to be acquired. The object may be a solid object or a plurality of object components. For example, the head, hands, etc. The three-dimensional information of the target object comprises a three-dimensional image, a three-dimensional point cloud, a three-dimensional grid, a local three-dimensional feature, a three-dimensional size and all parameters with the three-dimensional feature of the target object. Three-dimensional in the present invention means having XYZ three-direction information, particularly depth information, and is essentially different from only two-dimensional plane information. It is also fundamentally different from some definitions, which are called three-dimensional, panoramic, holographic, three-dimensional, but actually comprise only two-dimensional information, in particular not depth information.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components in an apparatus in accordance with embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications consistent with the principles of the invention may be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.

Claims

1. A dress designing equipment based on three-dimensional data which is characterized in that: the human body three-dimensional data acquisition device is used for acquiring a plurality of images of a human body and synthesizing a human body three-dimensional model by utilizing the images;

the garment design device is used for determining garment three-dimensional data by using the human body three-dimensional model;

2. The apparatus of claim 1, wherein: δ < 0.571.

3. The apparatus of claim 1, wherein: or δ < 0.405.

4. The apparatus of claim 1, wherein: or δ < 0.338.

5. The apparatus of claim 1, wherein: or δ < 0.296.

6. The apparatus of claim 1, wherein: the number of the image acquisition devices is at least two.

7. The apparatus of claim 1, wherein: at least two image acquisition devices are vertically arranged.

8. The apparatus of claim 1, wherein: the garment design device performs the following operations: dividing points, lines and/or planes of a three-dimensional model of a human body according to the clothing design requirements; and secondly, generating final three-dimensional data of the garment according to the sizes of the points, the lines and/or the surfaces.

9. The apparatus of claim 8, wherein: and generating a two-dimensional cutting template from the three-dimensional data of the final garment.

10. The apparatus of claim 8, wherein: and in the second operation, the final three-dimensional garment data is obtained by modifying the three-dimensional garment data on the basis of the standard three-dimensional garment data.

11. A clothes three-dimensional data storage device is characterized in that: the device is used for storing the three-dimensional data of the human body and the corresponding three-dimensional data of the clothes obtained by the device according to any one of claims 1 to 10.

12. The storage device of claim 11, wherein: and the client private space is used for storing corresponding data of the client.

13. A garment design method based on three-dimensional data is characterized in that: the human body three-dimensional data acquisition device is used for acquiring a plurality of images of a human body and synthesizing a human body three-dimensional model by utilizing the images;

14. The method of claim 13, wherein: δ < 0.571.

15. The method of claim 13, wherein: or δ < 0.405.

16. The method of claim 13, wherein: or δ < 0.338.

17. The method of claim 13, wherein: or δ < 0.296.

18. The method of claim 13, wherein: the number of the image acquisition devices is at least two.

19. The method of claim 13, wherein: at least two image acquisition devices are vertically arranged.

20. The method of claim 13, wherein: the garment design device performs the following operations: dividing points, lines and/or planes of a three-dimensional model of a human body according to the clothing design requirements; and secondly, generating final three-dimensional data of the garment according to the sizes of the points, the lines and/or the surfaces.

21. The method of claim 20, wherein: and generating a two-dimensional cutting template from the three-dimensional data of the final garment.

22. The method of claim 20, wherein: and in the second operation, the final three-dimensional garment data is obtained by modifying the three-dimensional garment data on the basis of the standard three-dimensional garment data.