CN112435080A - Virtual garment manufacturing equipment based on human body three-dimensional information - Google Patents
Virtual garment manufacturing equipment based on human body three-dimensional information Download PDFInfo
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- G06Q30/00—Commerce
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
Abstract
The embodiment of the invention provides virtual clothes making equipment, which comprises a human body three-dimensional information acquisition system, a human body database management system and a three-dimensional human body virtual fitting software system; the human body three-dimensional information acquisition system comprises one or more image acquisition devices; the human body database management system comprises a user account management system; a data analysis system; a garment model system adapted based on the three-dimensional size of the human body; a data security system; the three-dimensional human body virtual fitting software system comprises a three-dimensional human body display system; a three-dimensional garment model library system; a three-dimensional human body based garment adaptation system; a garment fabric system; adapting the display system; a business system. The method for three-dimensionally collecting the human body and making the clothes by utilizing the rotation mode of the multi-phase machine frame is put forward for the first time, so that the clothes making efficiency and effect are improved.
Description
Technical Field
The invention relates to the technical field of topography measurement, in particular to the technical field of 3D topography measurement.
Background
When performing 3D measurements, it is necessary to first acquire 3D information. Currently common methods include the use of machine vision and structured light, laser ranging, lidar. Structured light, laser ranging and laser radar all need an active light source to emit to a target object, and can affect the target object under certain conditions, and the light source cost is high. And the light source structure is more accurate, easily damages.
When three-dimensional acquisition of a human body is carried out and clothes are virtually made, the existing methods adopt structured light, laser ranging and laser radar. However, these methods all require emitting light to human body, which results in poor customer experience. Although infrared light is also used to illuminate the human body in the prior art, too much light illumination can also affect the health of the human body. And the above modes all need more complicated calibration to use, which makes the waiting time of the customer too long.
The machine vision mode is to collect the pictures of the object at different angles and match and splice the pictures to form a 3D model, so that the cost is low and the use is easy. In the prior art, it has also been proposed to use empirical formulas including rotation angle, object size, object distance to define camera position, thereby taking into account the speed and effect of the synthesis. However, when three-dimensional human body collection and clothing making are performed, a large amount of measurement work needs to be performed for different users, so that the working efficiency is extremely low. And each measurement brings a large amount of extra workload, and professional equipment is needed to accurately measure irregular human bodies. 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, an apparatus capable of accurately, efficiently and conveniently collecting a three-dimensional model of a human body for virtual garment making is urgently needed.
Disclosure of Invention
In view of the above, the present invention has been made to provide a virtual garment apparatus that overcomes or at least partially solves the above problems.
The embodiment of the invention provides virtual clothes making equipment, which comprises a human body three-dimensional information acquisition system, a human body database management system and a three-dimensional human body virtual fitting software system;
the human body three-dimensional information acquisition system comprises one or more image acquisition devices;
the human body database management system comprises a user account management system; a data analysis system; a garment model system adapted based on the three-dimensional size of the human body; a data security system;
the three-dimensional human body virtual fitting software system comprises a three-dimensional human body display system; a three-dimensional garment model library system; a three-dimensional human body based garment adaptation system; a garment fabric system; adapting the display system; a business system.
In alternative embodiments: the human body three-dimensional information acquisition system is used for acquiring human body images and synthesizing human body three-dimensional models according to the acquired images.
In alternative embodiments: the human body image acquisition comprises equipment starting, user information registration/login, user information uploading to a cloud, camera previewing starting and equipment photographing starting; the human body three-dimensional model synthesis comprises the steps of encrypting and uploading photos to a cloud end, and synthesizing the photos into the three-dimensional model.
In alternative embodiments: the three-dimensional human body virtual fitting software system comprises the calculation of the size of a human body three-dimensional model, the adaptation and the design of clothes.
In alternative embodiments: the size calculation of the human body three-dimensional model comprises the following steps:
reading data of the human body model; obtaining the effective space of the human body in the standing direction in the z-axis direction; equally dividing the effective space in the z-axis direction into n spaces; extracting plane coordinates (x, y) of dense point cloud on the equally divided points of the z axis; dividing the extracted data into n groups of data according to n equal parts, and numbering according to a certain sequence; calculating the spatial characteristics of each group of point clouds, and calculating the geometric parameters of the group of point clouds according to the coordinate values of the spatial point clouds; deducing a corresponding human body part by combining the z coordinates of the group of point clouds and the geometric characteristics of the human body; classifying a certain group or groups of point clouds into data of a specific part according to inference; according to the classification, calculating the geometrical characteristics of the point cloud of the specific part in detail; derivation of the dimensional data is calculated.
In alternative embodiments: garment adaptation and design includes:
encrypting and downloading the model to a local client; displaying a human body model; the human body model is matched with clothes in a three-dimensional mode; adjusting the size of the clothes; adjusting the fabric of the clothes; and (4) adapting to three-dimensional display.
In alternative embodiments: wherein the three-dimensional adaptation of the human body model and the clothes comprises:
acquiring coordinates (xn, yn, zn) of the neck center, coordinates (xs, ys, zs) of the waist center of the human body;
when the human body model is imported into the system, the human body is in a posture of correcting, namely the standing direction of the human body is taken as a z coordinate, the extending direction of the hand is taken as a y coordinate, and the direction of the face orientation is taken as an x coordinate;
when the clothes are modeled, the space coordinates of the clothes adopt the direction matched with a human body, the central position of the neck of the clothes is set as (0,0,0), and the central position of the waist of the trousers is set as (0,0, 0);
calculating the length, height and perimeter of each part of the clothes and setting the coordinates of the top end;
comparing the obtained size of the clothes with the size of the key part of the human body to obtain an amplification ratio parameter of the model;
adjusting the size and orientation of the garment and pants model based on the magnification ratio;
importing a garment model into the system;
translation of the model, adjusting the central point to (xn, yn, zn) and (xs, ys, zs) respectively,
and carrying out fine adjustment in a manual mode to finish matching.
In alternative embodiments: also includes ordering and business processing.
In alternative embodiments: the human body three-dimensional information acquisition system comprises one or more image acquisition devices, a rotating device, a bearing device and a rotation driving device;
the rotating device comprises a cross rod at the lower end and upright rods at the left side and the right side, and one or more image acquisition devices are arranged on the upright rods;
the lower end cross rod is arranged on the rotary driving device; the rotating driving device drives the upright rod of the rotating device to rotate around the human body;
the bearing device is used for bearing a human body.
In alternative embodiments: the included angle alpha of the optical axes of the image acquisition devices at two adjacent acquisition positions meets the following condition:
wherein, R is the distance from the rotation center to the surface of the target object, T is the sum of the object distance and the image distance during acquisition, d is the length or the width of a photosensitive element of the image acquisition device, F is the focal length of a lens of the image acquisition device, and u is an empirical coefficient.
Wherein u <0.498, preferably u <0.411, especially preferably u <0.359, in some applications u <0.281, or u <0.169, or u <0.041, or u <0.028 for better synthetic effect.
Invention and technical effects
1. The method for three-dimensionally collecting the human body and making the clothes by utilizing the rotation mode of the multi-phase machine frame is put forward for the first time, so that the clothes making efficiency and effect are improved.
2. The method has the advantages that the acquisition position of the camera is optimized by measuring the distance between the rotation center and the target object and the distance between the image sensing element and the target object, so that the speed and the effect of human body 3D construction are considered.
3. The automatic virtual garment making system and the method from three-dimensional acquisition of human bodies to full flow of garment adaptation and design are put forward for the first time (the specific method refers to the embodiment), and the design efficiency and effect are greatly improved.
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 illustrating an implementation manner of a human body three-dimensional information acquisition system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram illustrating another implementation manner of a human body three-dimensional information acquisition system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram illustrating a further implementation manner of a human body three-dimensional information acquisition system according to an embodiment of the present invention;
fig. 4 is a schematic diagram illustrating a landmark provided by an embodiment of the present invention.
The correspondence of reference numerals to the various components in the drawings is as follows:
the device comprises an image acquisition device 1, a rotating device 2, a carrying device 3, a rotating driving device 4, a telescopic rod 21 and a pitching device 22.
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.
Virtual garment system
The system comprises the following three parts: a. the human body three-dimensional information acquisition system, the human body database management system and the three-dimensional human body virtual fitting software system.
a. Human three-dimensional information acquisition system. The human body stands in the frame, and the color cameras take pictures of all parts of the human body under the driving of software. And the photo is transmitted to the cloud under the pushing of the software. And synthesizing the three-dimensional image of the photo at the cloud. The specific structure thereof will be described in detail below.
b. A human body database management system. The system comprises a user account management system, a database and a database, wherein the user account management system is used for managing user account information and establishing an account-based database; the data analysis system generates corresponding data of important sizes of clothes corresponding to the human body based on the three-dimensional data of the human body; an adapted garment model system based on the three-dimensional size of the human body; and the data security system is used for carrying out security protection on the account and the data of the human body.
c. A three-dimensional human body virtual fitting software system. Comprises a three-dimensional human body display system; a three-dimensional garment model library system; the clothes adapting system based on the three-dimensional human body can adjust the size of a model of the adapted clothes based on the human body according to the important size of the three-dimensional human body; the garment fabric system can adjust the fabric material and the color of the garment according to the preference of a customer; the three-dimensional animation system can display the adaptive effect of the human body under the dynamic state and store a dynamic effect picture; a clothing invoice and a business processing system.
Virtual garment making process
1. Human body image acquisition
The method comprises the steps of starting equipment, registering/logging user information, uploading the user information to a cloud, starting a camera for previewing and starting the equipment for photographing. The specific collection method will be described in detail below.
2. Human body three-dimensional model synthesis
The method comprises the steps of encrypting and uploading photos to a cloud end, and synthesizing the photos into a three-dimensional model.
3. Human three-dimensional model size calculation
Reading data of the human body model;
model data interpolation is adopted, so that point cloud data are denser, and subsequent slicing is facilitated;
extracting spatial data of dense point cloud;
obtaining an effective space in the standing direction (Z axis) of a human body, namely from what position of the Z axis to what position, an effective space point cloud exists;
equally dividing the space in which the z-axis is effective into n spaces;
extracting plane coordinates (x, y) of dense point cloud on the equally divided points of the z axis;
dividing the extracted data into n groups of data according to n equal parts, and numbering according to a certain sequence;
calculating the spatial characteristics of each group of point clouds, and calculating the length, width, mass center, roundness dispersion degree and other parameters of the group of point clouds according to the coordinate values of the spatial point clouds;
the corresponding human body part can be deduced by combining the z coordinates of the group of point clouds and the geometric characteristics of the human body;
classifying a certain group or groups of point clouds into data of a specific part according to the inference;
according to the classification, the geometrical characteristics of the point cloud of the specific part are calculated in detail, and the circumference or the width is calculated based on the geometrical characteristics, the circumferences or the widths of the positions corresponding to 10 key sizes of the clothes;
derivation of the dimensional data is calculated.
By the method, the size of the human body model can be calculated more accurately, the garment manufacturing accuracy is guaranteed, meanwhile, the calculation complexity is considered, and the calculation amount is reduced.
4. Garment adaptation and design
The method comprises the steps of encrypting and downloading a model to a local client, displaying the human body model, three-dimensionally matching the human body model with clothes, adjusting the size of the clothes, adjusting the fabric of the clothes, three-dimensionally displaying the matched clothes and the like.
Wherein the three-dimensional adaptation of the human body model and the clothes comprises:
obtaining coordinates (xn, yn, zn) of the neck and waist center of a human body (xs, ys, zs);
when the human body model is put into the system, the human body is put in a posture, namely the standing direction of the human body is taken as a z coordinate, the extending direction of the hand is taken as a y coordinate, and the direction of the face is taken as an x coordinate;
when the clothes are modeled, the space coordinates of the clothes adopt the direction matched with a human body, the central position of the neck of the clothes is set as (0,0,0), and the central position of the waist of the trousers is set as (0,0, 0);
calculating the length, height and perimeter of each part of the clothes and setting the coordinates of the top end;
comparing the obtained size of the clothes with the size of the key part of the human body to obtain a ratio amplification parameter of the model;
adjusting the size and orientation of the garment and pants model based on the magnification ratio;
importing a model into a system;
translation of the model, adjustment of the center point to (xn, yn, zn) (xs, ys, zs),
and carrying out fine adjustment in a manual mode to finish matching.
By the method, the matching of the human body and the clothes can be completed most quickly, excessive adjustment is prevented, and the matching efficiency and effect are improved.
5. Ordering and business processing.
Human body three-dimensional information acquisition system structure
In order to solve the above technical problem, an embodiment of the present invention provides a human body 3D information collecting apparatus, as shown in fig. 1, including one or more image collecting devices 1, a rotating device 2, a bearing device 3, and a rotation driving device 4.
The rotating device can be a rectangular frame, and a cross bar at the lower end of the rectangular frame is positioned at the lower part of the bearing device 3 and is connected with the rotating driving device 4. One or more image acquisition devices 1 are mounted on the vertical rods at the left end and the right end of the rectangular frame body. The image acquisition device can be installed on only one upright rod, or can be installed on two upright rods, or can be installed on one or more than one image acquisition device.
The lower end cross rod is installed on the rotary driving device and is parallel to the rotary surface, the rotary driving device is installed on the base, and the image acquisition devices are installed in sequence along the length of the vertical rod respectively. The vertical rod is parallel to the height direction of a human body, and the rotary driving device rotates the rotary rectangular frame body to rotate around the human body, so that the image acquisition devices at different positions on the vertical rod rotate around different heights of the human body respectively, and 360-degree images of different height parts of the human body are acquired. The images are sent to a processing unit to finally synthesize a 3D model of the target object.
The vertical rod of the rotating device is formed by combining a plurality of sections, and the sections can be mutually disassembled and stretched. And a locking screw is arranged between two adjacent sections. And according to the height of a user, after the positions of two adjacent upright columns reach a preset position, fastening the locking screws to relatively fix the positions of the two upright columns. The locking screw can be in a screw thread fastening type or a bolt type. The vertical rod can also be automatically telescopic and can be telescopic according to the height of a human body.
The image acquisition device is installed on the rod through the rotary table, so that the pitch angle of the image acquisition device on the rod can be adjusted.
The bearing device is disc-shaped and is used for the human body to stand. The bearing device is fixed on the base and does not rotate relatively. It will of course be appreciated that it is also possible to rotate the frame without rotation and with rotation of the carrier.
Wherein the rotation driving device is connected with the rotating shaft of the rotating device 2 and is driven to rotate by the rotation driving device 2. Of course, the rotation shaft of the rotation driving device 2 may also be connected to the rotation device by a reduction gear, for example, by a gear train or the like. When the image capturing apparatus 1 performs 360 ° rotation in the horizontal plane, it captures a corresponding human body image at a specific position (the specific capturing position will be described later in detail). The shooting can be performed synchronously with the rotation action, or shooting can be performed after the rotation of the shooting position is stopped, and the rotation is continued after the shooting is finished, and the like. The rotating device can be a motor, a stepping motor, a servo motor, a micro motor and the like. The rotating device (e.g., various motors) can rotate at a prescribed speed under the control of the controller and can rotate at a prescribed angle, thereby achieving optimization of the acquisition position, which will be described in detail below. Of course, the image acquisition device can be mounted on the rotating device in the existing equipment.
The swivel means may also be a U-shaped frame, i.e. without an upper cross bar, as shown in fig. 2.
Preferably, the vertical rod may be a telescopic rod 21 for extending and retracting in a direction perpendicular to the optical axis of the image capturing device 1, so that the image capturing device 1 can be positioned at different positions. At each position, the rotating scanning is carried out under the driving of the rotating device, so that a 3D model of the target object at the position can be constructed. After a certain position is scanned, the telescopic rod moves again, so that the image acquisition device 1 moves to another position, the scanning is repeatedly performed, and by analogy, the scanning is performed according to different height levels, and the construction of a 3D model of the height of the human body can be realized. Of course, the scanning may be performed only once, the scanning height may be adjusted by the telescopic device 4, and the 3D synthesis may be performed after the scanning height is adjusted to the position.
The telescopic device can be a telescopic sleeve, a telescopic slide rail and other telescopic structures. The expansion and contraction of the telescopic device can be manually adjusted and also can be expanded and contracted under the control of the control unit. The telescopic device may further comprise a telescopic motor for driving the telescopic unit (e.g. telescopic tube) to lengthen or shorten. After telescoping to the right position, the length of the telescoping device can be locked by the locking unit, so that stable support is provided for the rotating device. The locking unit may be a mechanical locking unit, such as a locking pin or the like, or an electrical locking unit, such as a locking of the telescopic device under control of the control unit.
The base is used for bearing the weight of the whole equipment.
The above device may further include a distance measuring device, the distance measuring device is fixedly connected to the image collecting device, and a direction of the distance measuring device is the same as an optical axis direction of the image collecting device. Of course, the distance measuring device can also be fixedly connected to the rotating device, as long as the distance measuring device can synchronously rotate along with the image acquisition device. Preferably, an installation platform can be arranged, the image acquisition device and the distance measurement device are both positioned on the platform, and the platform is installed on a rotating shaft of the rotating device and driven to rotate by the rotating device. The distance measuring device can use various modes such as a laser distance measuring instrument, an ultrasonic distance measuring instrument, an electromagnetic wave distance measuring instrument and the like, and can also use a traditional mechanical measuring tool distance measuring device. Of course, in some applications, the 3D acquisition device is located at a specific location, and its distance from the target object is calibrated, without additional measurements.
The device also comprises a light source which can be arranged on the periphery of the image acquisition device, the rotating device and the mounting platform. Of course, the light source may be separately provided, for example, a separate light source may be used to illuminate the target. Even when the lighting conditions are good, no light source is used. The light source can be an LED light source or 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, for example, the light sources are ring-shaped LED lamps around the lens. Since in some applications it is desirable to control the intensity of the light source. 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 order to facilitate the actual size measurement of the target object, a plurality of marking points can be arranged at the position of the target object. As in fig. 4, and the coordinates of these marked points are known.
Considering that the mark points have the properties of easy recognition, distinguishing, deformation resistance and the like, the mark points adopt a circular design, purple, blue, green, yellow and cyan are used as outer contours to be distinguished as colors, circles, crossed rectangles, triangles, rectangles and pentagons are contained to be geometrically distinguished, and the center red point is used for accurately positioning the position of a center point. The image of the mark point and the point number is shown in fig. 1.
The mark point A is formed by two concentric circles, a ring formed between the mark point A and the mark point A has different colors from the inner circle, and a red point is arranged at the center of the inner circle;
the outline of the mark point B is circular, the center of the circle is provided with a cross structure, the color of the interior of the circle is different from that of the cross structure, and the position of the center of the circle is provided with a red point;
the contour of the mark point C is circular, a triangular structure is inscribed in the center of the circle, the color of the interior of the circle is different from that of the triangular structure, and a red point is arranged at the center of the circle;
the outline of the marking point D is circular, a rectangular structure is inscribed in the center of the circle, the color of the interior of the circle is different from that of the rectangular structure, and a red point is arranged at the center of the circle;
the contour of the mark point D is circular, a pentagram structure is inscribed in the center of the circle, the color of the interior of the circle is different from that of the pentagram structure, and a red point is arranged at the center of the circle.
The absolute size of the 3D synthetic model is obtained by collecting the mark points and combining the coordinates thereof. These marking points may be previously set points or may be light points. The method of determining the coordinates of the points may comprise: using light ranging: and emitting light towards the target object by using the calibration device to form a plurality of calibration point light spots, and obtaining the coordinates of the calibration points through the known position relation of the optical ranging unit in the calibration device. The light is emitted towards the target object by using the calibration device, so that the light beam emitted by the light distance measuring unit in the calibration device falls on the target object to form a light spot. Since the light beams emitted from the light ranging units are parallel to each other, the positional relationship between the respective units is known. The two-dimensional coordinates in the emission plane of the plurality of light spots formed on the target object can be obtained. By performing the measurement by the light beam emitted from the optical ranging unit, the distance between each optical ranging unit and the corresponding light spot, that is, the depth information corresponding to the plurality of light spots formed on the target object can be obtained. I.e. the depth coordinate perpendicular to the emission plane, can be obtained. Thereby, three-dimensional coordinates of each spot can be obtained. Secondly, distance measurement and angle measurement are combined: and respectively measuring the distances of the plurality of mark points and the included angles between the mark points, thereby calculating respective coordinates. Using other coordinate measuring tools: such as RTK, global coordinate positioning systems, satellite-sensitive positioning systems, position and pose sensors, etc.
In another arrangement, as shown in figure 3, the camera may be adjusted in pitch in addition to having a telescoping function.
Wherein the image capturing device 1 is provided on the tilting device 22 so that the image capturing device 1 can be tilted in a vertical plane. The pitching device can be a roller, a gear, a bearing, a ball joint and the like. The optical axis of the image capturing device 1 is usually parallel to the pitch direction, but may be at an angle in some special cases. The pitch device can be manually adjusted and can also be driven by a motor to pitch and rotate, so that the precise pitch angle adjustment can be realized according to program control. The pitching device also comprises a locking mechanism which is used for locking the pitching device after the pitching angle is adjusted in place and the optical axis of the image acquisition device and the horizontal plane form a preset angle, so that the pitching device is prevented from rotating in the vertical direction again.
The pitching device is connected with the upright rod and is driven by the upright rod to rotate. Due to the adjustment of the pitching device, the optical axis of the image acquisition device and the horizontal plane form a certain included angle under normal conditions. This allows scanning of areas where the surface is not perpendicular to the horizontal. The pitching device is adjusted according to the condition that the surface of the human body part and the horizontal plane form an approximate included angle, so that the optical axis of the image acquisition device is perpendicular to the surface of the human body part as much as possible, and the acquisition accuracy of human body details is improved. Of course, it may also be parallel to the horizontal plane in special cases.
The pitching device generally satisfies that the pitching angle of the image acquisition device can be adjusted, and the image acquisition device is fixed after being rotated in place, so that the pitching device drives the image acquisition device to rotate. In some applications or products, the image acquisition device can be directly fixed at a specific angle of the preset pitching device, and the function of angle adjustment is not provided. That is, the optical axis of the image acquisition device is directly fixed to the tilting device (e.g., the stand) at a certain angle of tilt.
Of course, in addition to pitch adjustment, the camera may also be adjusted in translation in the horizontal direction, or directly translated a distance from the center of rotation using a fixed support.
3D information acquisition process
The user stands onA specified position is appointed in the human body three-dimensional information acquisition system,
the length of the telescopic device is controlled to enable the image acquisition device to be located at a preset position, the rotating device drives the image acquisition device to rotate at a certain speed, and the image acquisition device acquires images at a set position in the rotating process. At the moment, the rotation can not be stopped, namely, the image acquisition and the rotation are synchronously carried out; or stopping rotation at the position to be acquired, acquiring images, and continuing to rotate to the next position to be acquired after acquisition is finished. The rotating means may be driven by a program in a control unit set in advance. The device can also communicate with an upper computer through a communication interface, and the rotation is controlled through the upper computer. Particularly, the rotating device can be connected with a mobile terminal in a wired or wireless mode, and the rotating device is controlled to rotate through the mobile terminal (such as a mobile phone). The rotating device can set rotating parameters through the remote platform, the cloud platform, the server, the upper computer and the mobile terminal, and the rotating start and stop of the rotating device are controlled.
In order to ensure the efficiency and effect of the acquisition, the image acquisition devices with different heights on the vertical rod should meet certain conditions. This condition applies equally to the telescopic rod solution. Namely, the length of the telescopic rod is controlled to enable the image acquisition device to be located at another preset position, and the rotating device is repeated to enable the image acquisition device to acquire the user image around the position, so that the corresponding 3D model is constructed.
The position L of two adjacent image acquisition devices on the vertical rod, or the acquisition position of the first telescopic device and the acquisition position of the second telescopic device should enable the position L of the image acquisition equipment before and after stretching to meet the following conditions:
μ＜0.482
wherein L is the linear distance between the optical centers of the image acquisition devices at the acquisition positions at two adjacent positions; f is the focal length of the image acquisition device; d is the length or width of a photosensitive element (CCD) of the image acquisition device; m is the distance from the photosensitive element of the image acquisition device to the surface of the target object along the optical axis; μ is an empirical coefficient.
When the two positions are along the length direction of the photosensitive element of the image acquisition device, d is a rectangle; when the two positions are along the width direction of the photosensitive element of the image acquisition device, d is in a rectangular width.
When the image acquisition device is at any one of the two positions, the distance from the photosensitive element to the surface of the target object along the optical axis is taken as M.
As mentioned above, L should be a straight-line distance between the optical centers of the two image capturing devices, but since the optical center position 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, the axial center of the connection between the image capturing device and the pan/tilt head (or platform, support), and the center of the proximal or distal surface of the lens may be used in some cases instead, and the error caused by the displacement is found to be within an acceptable range through experiments, and therefore the above range is also within the protection scope of the present invention.
The image acquisition device acquires a plurality of images of a human body, sends the images into a remote platform, a cloud platform, a server, an upper computer and/or a mobile terminal through a communication device, and carries out 3D synthesis on a target object by using a 3D model synthesis method.
In particular, the distance measuring device may be used to measure the corresponding distance parameters in the relevant formula conditions, i.e. the distance from the center of rotation to the target object and the distance from the sensor element to the target object, before or simultaneously with the acquisition. And calculating the acquisition position according to a corresponding condition formula, and prompting a user to set rotation parameters or automatically setting the rotation parameters.
When the distance measurement is carried out before the collection, the rotating device can drive the distance measurement device to rotate, so that the two distances at different positions can be measured. And respectively averaging two distances measured by a plurality of measuring points, and taking the average value as a uniform distance value acquired at this time to be introduced into a formula. The average value can be obtained by using a sum average, a weighted average, other averaging methods, or a method of discarding outliers and then averaging.
When distance measurement is carried out in the acquisition process, the rotating device rotates to the first position to carry out image acquisition, the two distance values are measured at the same time, the two distance values are brought into a condition formula to calculate the interval angle, and the next acquisition position is determined according to the angle.
Optimization of image acquisition device position
When the rotating device drives the image acquisition device to rotate for acquisition, the image acquisition device can be rotated to different positions to meet certain conditions so as to take acquisition efficiency and synthesis quality into consideration. For this reason, the present invention has performed a large number of experiments, and it is concluded that an empirical condition that the interval of camera acquisition is preferably satisfied when acquisition is performed is as follows.
When 3D acquisition is carried out, the included angle alpha of the optical axis of the same image acquisition device at two adjacent positions on the horizontal plane meets the following condition:
wherein the content of the first and second substances,
r is the distance from the center of rotation to the surface of the target,
t is the sum of the object distance and the image distance during acquisition, namely the distance between the photosensitive unit of the image acquisition device and the target object.
d is the length or width of a photosensitive element (CCD) of the image acquisition device, and when the two positions are along the length direction of the photosensitive element, the length of the rectangle is taken as d; when the two positions are along the width direction of the photosensitive element, d takes a rectangular width.
And F is the focal length of the lens of the image acquisition device.
u is an empirical coefficient.
Usually, a distance measuring device, for example a laser distance meter, is arranged on the acquisition device. The optical axis of the distance measuring device is parallel to the optical axis of the image acquisition device, so that the distance from the acquisition device to the surface of the target object can be measured, and R and T can be obtained according to the known position relation between the distance measuring device and each part of the acquisition device by using the measured distance.
When the image acquisition device is at any one of the two positions, the distance from the photosensitive element to the surface of the target object along the optical axis is taken as T. In addition to this method, multiple averaging or other methods can be used, the principle being that the value of T should not deviate from the sum of the image distances from the object at the time of acquisition.
Similarly, when the image pickup device is in any one of the two positions, the distance from the rotation center to the surface of the object along the optical axis is defined as R. In addition to this method, multiple averaging or other methods can be used, with the principle that the value of R should not deviate from the radius of rotation at the time of acquisition.
In general, the size of an object is adopted as a method for estimating the position of a camera in the prior art. Since the object size will vary with the measurement object. For example, when a tall user and a small user acquire 3D information after the tall user acquires the 3D information, the size needs to be measured again and reckoning needs to be performed again. 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, 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. R, T is only a straight line distance that can be easily measured by conventional measuring methods such as a ruler and a laser rangefinder. Meanwhile, in the apparatus of the present invention, the capturing direction of the image capturing device (e.g., camera) and the direction of the rotation axis thereof are away from each other, that is, the lens is oriented substantially opposite to the rotation center. At the moment, the included angle alpha of the optical axis for controlling the image acquisition device to perform twice positions is easier, and only the rotation angle of the rotary driving motor needs to be controlled. Therefore, it is more reasonable to use α to define the optimal position. 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.
According to a number of experiments, u should be less than 0.498 in order to ensure the speed and effect of the synthesis, and for better synthesis effect, u is preferably <0.411, especially preferably <0.359, in some applications u <0.281, or u <0.169, or u <0.041, or u < 0.028.
Experiments were carried out using the apparatus of the invention, and some experimental data are shown below, in mm. (the following data are given by way of example only)
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 model synthesis method
A plurality of images acquired by the image acquisition device are sent to the processing unit, and a 3D model is constructed by using the following algorithm. The processing unit can be located in the acquisition equipment or remotely, such as a cloud platform, a server, an upper computer and the like.
The specific algorithm 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 mgIs the local gray average value, s, of the original imagegIs the local standard deviation of gray scale of the original image, mfFor the transformed image local gray scale target value, sfThe target value of the standard deviation of the local gray scale of the image after transformation. 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 the sparse three-dimensional point cloud of the target object and the position and posture data of the photographing camera by using a light beam method adjustment, namely obtaining model coordinate values of the sparse three-dimensional point cloud of the target object model and the position; 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 target object 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 object models. 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 algorithm used by the present invention, and the algorithm is matched with the image acquisition condition, and the time and quality of the synthesis are considered by using the algorithm. It will be appreciated that conventional 3D synthesis algorithms known in the art may be used with the solution of the invention.
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. 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.
The capture area in the present invention refers to a range in which an image capture device (e.g., a camera) can capture an image. The image acquisition device can 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, intelligent glasses, an intelligent watch, an intelligent bracelet and all devices with image acquisition functions.
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 (10)
1. A virtual garment apparatus, characterized in that: the human body three-dimensional information acquisition system, the human body database management system and the three-dimensional human body virtual fitting software system are included;
the human body three-dimensional information acquisition system comprises one or more image acquisition devices;
the human body database management system comprises a user account management system; a data analysis system; a garment model system adapted based on the three-dimensional size of the human body; a data security system;
the three-dimensional human body virtual fitting software system comprises a three-dimensional human body display system; a three-dimensional garment model library system; a three-dimensional human body based garment adaptation system; a garment fabric system; adapting the display system; a business system.
2. The apparatus of claim 1, wherein: the human body three-dimensional information acquisition system is used for acquiring human body images and synthesizing human body three-dimensional models according to the acquired images.
3. The apparatus of claim 2, wherein: the human body image acquisition comprises equipment starting, user information registration/login, user information uploading to a cloud, camera previewing starting and equipment photographing starting; the human body three-dimensional model synthesis comprises the steps of encrypting and uploading photos to a cloud end, and synthesizing the photos into the three-dimensional model.
4. The apparatus of claim 1, wherein: the three-dimensional human body virtual fitting software system comprises the calculation of the size of a human body three-dimensional model, the adaptation and the design of clothes.
5. The apparatus of claim 4, wherein: the size calculation of the human body three-dimensional model comprises the following steps:
reading data of the human body model; obtaining the effective space of the human body in the standing direction in the z-axis direction; equally dividing the effective space in the z-axis direction into n spaces; extracting plane coordinates (x, y) of dense point cloud on the equally divided points of the z axis; dividing the extracted data into n groups of data according to n equal parts, and numbering according to a certain sequence; calculating the spatial characteristics of each group of point clouds, and calculating the geometric parameters of the group of point clouds according to the coordinate values of the spatial point clouds; deducing a corresponding human body part by combining the z coordinates of the group of point clouds and the geometric characteristics of the human body; classifying a certain group or groups of point clouds into data of a specific part according to inference; according to the classification, calculating the geometrical characteristics of the point cloud of the specific part in detail; derivation of the dimensional data is calculated.
6. The apparatus of claim 4, wherein: garment adaptation and design includes:
encrypting and downloading the model to a local client; displaying a human body model; the human body model is matched with clothes in a three-dimensional mode; adjusting the size of the clothes; adjusting the fabric of the clothes; and (4) adapting to three-dimensional display.
7. The apparatus of claim 6, wherein: wherein the three-dimensional adaptation of the human body model and the clothes comprises:
acquiring coordinates (xn, yn, zn) of the neck center, coordinates (xs, ys, zs) of the waist center of the human body;
when the human body model is imported into the system, the human body is in a posture of correcting, namely the standing direction of the human body is taken as a z coordinate, the extending direction of the hand is taken as a y coordinate, and the direction of the face orientation is taken as an x coordinate;
when the clothes are modeled, the space coordinates of the clothes adopt the direction matched with a human body, the central position of the neck of the clothes is set as (0,0,0), and the central position of the waist of the trousers is set as (0,0, 0);
calculating the length, height and perimeter of each part of the clothes and setting the coordinates of the top end;
comparing the obtained size of the clothes with the size of the key part of the human body to obtain an amplification ratio parameter of the model;
adjusting the size and orientation of the garment and pants model based on the magnification ratio;
importing a garment model into the system;
translation of the model, adjusting the central point to (xn, yn, zn) and (xs, ys, zs) respectively,
and carrying out fine adjustment in a manual mode to finish matching.
8. The apparatus of claim 4, wherein: also includes ordering and business processing.
9. The apparatus of claim 1, wherein: the human body three-dimensional information acquisition system comprises one or more image acquisition devices, a rotating device, a bearing device and a rotation driving device;
the rotating device comprises a cross rod at the lower end and upright rods at the left side and the right side, and one or more image acquisition devices are arranged on the upright rods;
the lower end cross rod is arranged on the rotary driving device; the rotating driving device drives the upright rod of the rotating device to rotate around the human body;
the bearing device is used for bearing a human body.
10. The apparatus of claim 1, wherein: the included angle alpha of the optical axes of the image acquisition devices at two adjacent acquisition positions meets the following condition:
wherein R is the distance from the rotation center to the surface of the target object, T is the sum of the object distance and the image distance during acquisition, d is the length or the width of a photosensitive element of the image acquisition device, F is the focal length of a lens of the image acquisition device, and u is an empirical coefficient; wherein u <0.498, preferably u <0.411, especially preferably u <0.359, in some applications u <0.281, or u <0.169, or u <0.041, or u <0.028 for better synthetic effect.
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