CN111076674B - Closely target object 3D collection equipment - Google Patents
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- CN111076674B CN111076674B CN201911288917.5A CN201911288917A CN111076674B CN 111076674 B CN111076674 B CN 111076674B CN 201911288917 A CN201911288917 A CN 201911288917A CN 111076674 B CN111076674 B CN 111076674B
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Abstract
The invention provides a short-distance target object 3D acquisition device, which comprises an acquisition area moving device, a target object acquisition device and a control device, wherein the acquisition area moving device is used for driving an acquisition area of an image acquisition device to generate relative motion with the target object; the image acquisition device is used for acquiring a group of images of the target object through the relative movement; the acquisition position of the image acquisition device accords with a preset condition. A3D acquisition and synthesis method for micro objects is firstly provided. By arranging the mode that the background plate rotates together, the synthesis speed and the synthesis precision can be simultaneously 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. The currently common method includes using a machine vision mode to collect pictures of an object from different angles, and matching and splicing the pictures to form a 3D model. When pictures at different angles are collected, a plurality of cameras can be arranged at different angles of the object to be detected, and the pictures can be collected from different angles through rotation of a single camera or a plurality of cameras. For example, in the Digital Emily project of the university of California, a spherical bracket is adopted, and hundreds of cameras are fixed at different positions and different angles on the bracket, so that 3D acquisition and modeling of a human body are realized. However, even with such devices, only human-sized object 3D information can be acquired and can only be used indoors. Meanwhile, the use of a large number of cameras causes great difficulty in installation and debugging of the whole device, and the device is very expensive. If a smaller volume of object is to be photographed (e.g. a fingerprint, or even an object under a microscope), it is difficult to mount such a large number of cameras because the space left for the cameras is relatively limited because the object is too small. And the acquisition equipment is designed for a single size, and once the size of the object is greatly changed, the acquisition equipment cannot work.
Moreover, for 3D acquisition of a minute object, even if the rotation mode is used for shooting, the shooting position is arbitrarily selected, which causes deterioration of the synthesis time and the synthesis effect.
In addition, it is proposed in the prior art to define the camera position by using an empirical formula including a rotation angle, a target size, and an object distance, so as to take account of the combination speed and effect. For small-size targets, it is difficult to measure the size of the target, and if the target needs to be measured before 3D acquisition and synthesis each time, extra burden is brought, and the accuracy is difficult to guarantee. Meanwhile, in practical application, the following are found: 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: for the 3D acquisition and synthesis of tiny objects, the synthesis speed and the synthesis precision can be greatly improved simultaneously; the method is convenient to operate, does not need to use professional equipment or measure too much, and can quickly obtain the optimized camera position.
Disclosure of Invention
In view of the above, the present invention has been developed to provide a collecting device that overcomes, or at least partially solves, the above-mentioned problems.
The invention provides a 3D acquisition device for a close-range target object,
the acquisition area moving device is used for driving the acquisition area of the image acquisition device to move relative to the target object;
the image acquisition device is used for acquiring a group of images of the target object through the relative movement;
the acquisition position of the image acquisition device meets the following conditions:
<0.582
wherein L is the linear distance between the optical centers of the two adjacent image acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width of the 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; to adjust the coefficients.
The invention also provides a device for 3D acquisition of a close-range target object,
the image acquisition devices are arranged around the target object and are used for acquiring a plurality of images of the target object in different directions;
the acquisition position of the image acquisition device meets the following conditions:
<0.582
wherein L is the linear distance between the optical centers of the two adjacent image acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width of the 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; to adjust the coefficients.
Optionally, a background plate is arranged on the opposite side of the image acquisition device.
Optionally, the acquisition area moving device is a rotating device, and drives the image acquisition device and/or the target object to rotate.
Optionally, the rotating device is a rotating disc and/or a rotating arm.
Optionally, the lens of the image acquisition device is a macro lens or a micro lens.
Optionally, the device further comprises an object stage, wherein the object stage is of a concentric structure capable of being lifted in a partitioned mode.
Optionally <0.412, preferably < 0.335.
The invention also provides a 3D synthesis device or method, or a 3D identification/alignment device or method, using any of the apparatus.
The invention also provides an accessory manufacturing method or device using any one of the devices.
Invention and technical effects
1. A3D acquisition and synthesis method for micro objects is firstly provided.
2. By arranging the mode that the background plate rotates together, the synthesis speed and the synthesis precision can be simultaneously improved.
3. Aiming at the 3D acquisition and synthesis of the micro objects, the positions of the cameras for acquiring pictures are optimized, so that the synthesis speed and the synthesis precision can be simultaneously improved. When the position is optimized, the angle and the target size do not need to be measured, and the applicability is stronger.
4. The objective table structure convenient for micro-distance collection is arranged, so that the objective table structure can adapt to targets with various sizes.
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 rotation mode of an image acquisition device of an image acquisition apparatus according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a concentric stage according to an embodiment of the present invention;
FIG. 3 is a top view of a concentric circle stage in a stowed position according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a target object rotation mode of the image capturing device according to the embodiment of the present invention;
FIG. 5 is a schematic diagram of a multi-camera configuration of an image capture device;
fig. 6 is a schematic structural diagram of a background board of the image capturing device according to the embodiment of the present invention;
the reference numbers relate to the components of the apparatus as follows:
the device comprises an object stage 1, a rotating device 2, a base 3, an image acquisition device 4 and a background plate 5.
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.
In order to solve the above technical problem, an embodiment of the present invention provides a short-distance target 3D acquisition apparatus, including an image acquisition device and a rotation device. The image acquisition device is used for acquiring a group of images of the target object through the relative movement of an acquisition area of the image acquisition device and the target object; and the acquisition area moving device is used for driving the acquisition area of the image acquisition device to generate relative motion with the target object. The collection area is the effective field range of the image collection device.
Rotation mode of image acquisition device
Referring to fig. 1, the apparatus includes a circular stage 1 for carrying a minute object; the rotating device 2 can be a rotating arm which is in a bent shape, and the horizontal lower section part is rotationally fixed on the base 3, so that the vertical upper section part rotates around the objective table 1; the image acquisition device 4 is used for acquiring images of the target object and is arranged at the upper section of the rotating arm, and the special image acquisition device 4 can rotate along the rotating arm in an up-and-down pitching manner so as to adjust an acquisition angle.
The object is fixed on the object stage 1, and the rotating device 2 drives the image acquisition device 4 to rotate around the object. The rotating device 2 can drive the image acquisition device 4 to rotate around the target object through the rotating arm. Of course, the rotation is not necessarily a complete circular motion, and can be only rotated by a certain angle according to the acquisition requirement. The rotation does not necessarily need to be circular motion, and the motion track of the image acquisition device 4 can be other curved tracks as long as the camera can shoot the object from different angles.
The rotating device 2 may be a turntable, a track, or other forms, so that the image capturing device 4 may move.
The image capturing device 4 is used for capturing an image of an object, and may be a fixed focus camera or a zoom camera. In particular, the camera may be a visible light camera or an infrared camera. The lens of the image acquisition device 4 is a macro lens, and the distance from the target object is very short during shooting. In particular, the lens of the image acquisition device 4 may be a microscope lens, so that the device is able to synthesize a 3D model of a microsized object.
The table top of the object stage 1 is a concentric structure, and as shown in fig. 2-3, the size of the table top of the object stage can be selected according to the size of the object. For example, when the size of the target object is 1cm, the stage is kept with a table top with the diameter of 2cm to be lifted, and a table top with the periphery larger than 2cm is lowered to the base. Since the image capturing device 4 is located closer to the object, this arrangement allows sufficient rotation space for the image capturing device. The mesas may be provided in concentric circles of various diameter sizes, e.g., 1cm, 2cm, 5cm, 10cm, etc., as desired. This is also one of the points of the present invention.
The rotating arm comprises at least two sections, a horizontal lower section part and a vertical upper section part. The top end of the horizontal lower section part is arranged on the base through a bearing and is used for rotating around the center of the base. The horizontal lower section part can be of a telescopic structure, so that the rotating radius of the rotating arm can be conveniently adjusted. The vertical upper section part is driven by the horizontal lower section part and rotates around the objective table 1, so that the image acquisition device 4 on the vertical upper section part is driven to acquire. The vertical upper section part can also be of a telescopic structure, so that the acquisition height can be conveniently adjusted. The horizontal lower section and the vertical upper section are not limited to strict horizontal and vertical, and may be inclined within a reasonable range. For example, the horizontal lower section may extend outwardly from the center of the base at an upward angle of inclination.
Rotation mode of target
In addition to the above, in some cases, the camera may be fixed, and referring to fig. 4, the stage 1 carrying the object is rotated, so that the direction of the object facing the image capturing device is changed at any moment, thereby enabling the image capturing device to capture images of the object from different angles.
The rotating arm is fixed on the base, and the objective table can be connected with the base through the rotating shaft so as to rotate.
In this case, the calculation may still be performed according to the condition of converting the motion into the motion of the image capturing device, so that the motion conforms to a corresponding empirical formula (which will be described in detail below). For example, in a scenario where the stage rotates, it may be assumed that the stage is stationary and the image capture device rotates. The distance of the shooting position when the image acquisition device rotates is set by using an empirical formula, so that the rotating speed of the image acquisition device is deduced, the rotating speed of the object stage is reversely deduced, the rotating speed is conveniently controlled, and 3D acquisition is realized.
And the processor is also called as a processing unit and is used for synthesizing a 3D model of the target object according to a plurality of images acquired by the image acquisition device and a 3D synthesis algorithm to obtain 3D information of the target object.
Optical axis rotation mode
In order to enable the image acquisition device to acquire images of the target object in different directions, the image acquisition device and the target object can be kept still, and the image acquisition device and the target object can be rotated by rotating an optical axis of the image acquisition device. For example: the collecting area moving device is an optical scanning device, so that the collecting area of the image collecting device and the target object generate relative motion under the condition that the image collecting device does not move or rotate. The acquisition area moving device also comprises a light deflection unit which is driven by machinery to rotate, or is driven by electricity to cause light path deflection, or is distributed in space in multiple groups, so that images of the target object can be acquired from different angles. The light deflection unit may typically be a mirror, which is rotated to collect images of the target object in different directions. Or a reflector surrounding the target object is directly arranged in space, and the light of the reflector enters the image acquisition device in turn. Similarly to the foregoing, the rotation of the optical axis in this case can be regarded as the rotation of the virtual position of the image pickup device, and by this method of conversion, it is assumed that the image pickup device is rotated, so that the calculation is performed using the following empirical formula.
Multiple camera mode
It can be understood that, besides the camera and the object move relatively to each other, so that the camera can shoot images of the object at different angles, as shown in fig. 5, a plurality of cameras can be arranged at different positions around the object, so that the images of the object at different angles can be shot simultaneously.
Setting a background plate
In the rotational setting, a background plate 5 may also be incorporated in the device. As shown in fig. 6, the background plate 5 is located opposite the image pickup device 4 and rotates synchronously when the image pickup device rotates, and remains stationary when the image pickup device 4 is stationary. For example, another rotating arm with the same structure is arranged on the opposite side of the rotating arm for installing the image acquisition device 4 and is used for bearing the background plate 5, and the two rotating arms rotate synchronously. Of course, the two rotating arms may be integrally constructed.
So that the image of the object captured by the image capturing device 4 is all backed by the background plate 5. The background plate is all solid or mostly (body) solid. 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 5 is generally a flat plate, and preferably a curved plate, such as a concave plate, a convex plate, a spherical plate, and even in some application scenarios, a background plate 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.
Light source
Typically, the light sources are distributed around the lens of the image capturing device 4, for example, the light sources are ring-shaped LED lamps around the lens. Since in some applications the object to be acquired is a human body, the intensity of the light source needs to be controlled to avoid discomfort to the human body. 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. The light source may also be positioned at other locations that provide uniform illumination of the target. The light source 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.
Image acquisition device position optimization
When 3D collection is carried out, the optical axis directions of the image collection devices at different collection positions are changed relative to a target object, and the positions of two adjacent image collection devices or two adjacent collection positions of the image collection devices meet the following conditions:
<582
wherein L is the linear distance between the optical centers of the two adjacent image acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width of the 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; to adjust the coefficients.
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 T. In addition to this method, in another case, L is An、An+1Linear distance between optical centers of two image capturing devices, and An、An+1Two image acquisition devices adjacent to each othern-1、An+2Two image acquisition devices and An、An+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 Tn-1、Tn、Tn+1、Tn+2，T＝(Tn-1+Tn+Tn+1+Tn+2)/4. Of course, the average value may be calculated by using more positions than the adjacent 4 positions.
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.
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, when the head of a child is collected after 3D information on the head of an adult is collected, the head size needs to be measured again and calculated 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, 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, and the specific experimental data is shown in the following.
A camera: MER-2000-19U3M/C
| Serial number | Delta value | Time of synthesis | Area of synthesis region |
| 1 | 0.6978 | 2.2min | / |
| 2 | 0.5818 | 2.8min | 65％ |
| 3 | 0.4112 | 3.0min | 90％ |
| 4 | 0.3341 | 3.5min | 100％ |
From the above experimental results and a lot of experimental experience, it can be derived that the value should satisfy <0.582, and at this time, part of the 3D model can be synthesized, and although part of the model cannot be synthesized automatically, it is acceptable in the case of low requirement, and the part which cannot be synthesized can be compensated manually or by replacing the algorithm. When the value satisfies <0.412 in particular, the balance between the synthesis effect and the synthesis time can be optimally taken into consideration; to obtain better synthesis results, one can choose <0.334, where the synthesis time is increased but the synthesis quality is better. On the other hand, 0.697 is not yet synthesized. 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 synthesis method
After the image acquisition equipment acquires images of a target object in multiple directions through the image acquisition device 4, the images are transmitted to the processor in a data transmission mode. The processor may be located locally or the image may be uploaded to a cloud platform using a remote processor. The synthesis of the 3D model is performed in the processor using the following method.
According to the above-described acquisition method, the image acquisition device 4 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 4 is located, or may be connected to the image capturing device 4 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 4 may be transmitted thereto to perform 3D synthesis. Meanwhile, the data of the image acquisition device 4 can be transmitted to the cloud platform, and 3D synthesis is performed by using the powerful computing capability 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 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 sparse human face three-dimensional point cloud and position and posture data of a photographing camera by using a light beam method adjustment, namely obtaining model coordinate values of the sparse human face model three-dimensional point cloud 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 a human face curved surface 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: and (4) fully-automatic texture mapping of the human face model. 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.
Accessory matching and making
After 3D information of the target object is collected and the 3D model is synthesized, accessories matched with the target object can be manufactured for the target object according to the 3D data.
For example, a microscopic lens is used to take 360 ° images of cells, so as to synthesize a three-dimensional model of the cells, and the data of the three-dimensional model can be used to make a solid model of the cells in a scaling-up manner for scientific research and teaching.
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.
Although the image capturing device captures an image in the above embodiments, the image capturing device is not understood to be applicable to only a group of pictures made of a single picture, and this is merely an illustrative manner for facilitating understanding. The image acquisition device can also acquire video data, and directly utilize the video data or intercept images from the video data to carry out 3D synthesis. However, the shooting position of the corresponding frame of the video data or the captured image used in the synthesis still satisfies the above empirical formula.
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.
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 (20)
1. A close-range target 3D acquisition device is characterized in that:
the acquisition area moving device is used for driving the acquisition area of the image acquisition device to move relative to the target object;
the image acquisition device is used for acquiring a group of images of the target object through the relative movement;
the acquisition position of the image acquisition device meets the following conditions:
<0.582
wherein L is the linear distance of the optical center of the image acquisition device at two adjacent acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width 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; to adjust the coefficients.
2. The apparatus of claim 1, wherein: the opposite side of the image acquisition device is provided with a background plate.
3. The apparatus of claim 1, wherein: the acquisition area moving device is a rotating device and drives the image acquisition device and/or the target object to rotate.
4. The apparatus of claim 3, wherein: the rotating device is a rotating disc and/or a rotating arm.
5. The apparatus of claim 1, wherein: the lens of the image acquisition device is a macro lens or a microscope lens.
6. The apparatus of claim 1, wherein: the device also comprises an object stage which is of a concentric structure capable of lifting in a divided area mode.
7. The apparatus of claim 1, wherein: < 0.412.
8. The apparatus of claim 1, wherein: < 0.335.
9. A 3D synthesis apparatus, using the device of any one of claims 1-8.
10. A 3D identification device, characterized in that a device according to any of claims 1-8 is used.
11. A 3D identification method, characterized in that a device according to any of claims 1-8 is used.
12. A close-range target 3D acquisition device is characterized in that:
the image acquisition devices are arranged around the target object and are used for acquiring a plurality of images of the target object in different directions;
the acquisition position of the image acquisition device meets the following conditions:
<0.582
wherein L is the linear distance between the optical centers of the two adjacent image acquisition positions; f is the focal length of the image acquisition device; d is the rectangular length or width 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; to adjust the coefficients.
13. The apparatus of claim 12, wherein: the opposite side of the image acquisition device is provided with a background plate.
14. The apparatus of claim 12, wherein: the lens of the image acquisition device is a macro lens or a microscope lens.
15. The apparatus of claim 12, wherein: the device also comprises an object stage which is of a concentric structure capable of lifting in a divided area mode.
16. The apparatus of claim 12, wherein: < 0.412.
17. The apparatus of claim 12, wherein: < 0.335.
18. A 3D synthesis apparatus, using the device of any of claims 12-17.
19. A 3D identification device, characterized in that a device according to any of claims 12-17 is used.
20. A 3D identification method, characterized in that a device according to any of claims 12-17 is used.
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| CN201911288917.5A CN111076674B (en) | 2019-12-12 | 2019-12-12 | Closely target object 3D collection equipment |
| PCT/CN2020/134763 WO2021115301A1 (en) | 2019-12-12 | 2020-12-09 | Close-range target 3d acquisition apparatus |
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| CN111076674B (en) * | 2019-12-12 | 2020-11-17 | 天目爱视（北京）科技有限公司 | Closely target object 3D collection equipment |
| CN111678429B (en) * | 2020-06-09 | 2022-02-22 | 江苏瑞奇海力科技有限公司 | Microscopic measurement system and microscopic measurement method |
| CN112254669B (en) * | 2020-10-15 | 2022-09-16 | 天目爱视（北京）科技有限公司 | Intelligent visual 3D information acquisition equipment of many bias angles |
| CN112254671B (en) * | 2020-10-15 | 2022-09-16 | 天目爱视（北京）科技有限公司 | Multi-time combined 3D acquisition system and method |
| CN112253913B (en) * | 2020-10-15 | 2022-08-12 | 天目爱视（北京）科技有限公司 | Intelligent visual 3D information acquisition equipment deviating from rotation center |
| CN112484663B (en) * | 2020-11-25 | 2022-05-03 | 天目爱视（北京）科技有限公司 | Intelligent visual 3D information acquisition equipment of many angles of rolling |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1793780A (en) * | 2005-12-05 | 2006-06-28 | 天津大学 | Measuring splice method and device of large three-dimensional body shape based on splicing target |
| CN201258235Y (en) * | 2008-08-21 | 2009-06-17 | 机械科学研究院浙江分院有限公司 | Multi-column lifting type operating platform |
| CN103075960A (en) * | 2012-12-30 | 2013-05-01 | 北京工业大学 | Multi-visual-angle great-depth micro stereo visual-features fusion-measuring method |
| CN206362712U (en) * | 2016-12-28 | 2017-07-28 | 京瓷精密工具（珠海）有限公司 | A kind of sword frontier inspection measurement equipment |
| CN109035379A (en) * | 2018-09-10 | 2018-12-18 | 天目爱视（北京）科技有限公司 | A kind of 360 ° of 3D measurements of object and information acquisition device |
| CN109443235A (en) * | 2018-11-02 | 2019-03-08 | 滁州市云米工业设计有限公司 | A kind of industrial design product collecting device for outline |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3852704B2 (en) * | 2004-03-15 | 2006-12-06 | 住友金属鉱山株式会社 | Method and apparatus for recognizing three-dimensional shape of object |
| CN101074876A (en) * | 2007-06-26 | 2007-11-21 | 北京中星微电子有限公司 | Method and device for automatically measuring distance |
| JP2010014699A (en) * | 2008-06-05 | 2010-01-21 | Toppan Printing Co Ltd | Shape measuring apparatus and shape measuring method |
| CN104299261B (en) * | 2014-09-10 | 2017-01-25 | 深圳大学 | Three-dimensional imaging method and system for human body |
| US9560345B2 (en) * | 2014-12-19 | 2017-01-31 | Disney Enterprises, Inc. | Camera calibration |
| KR101635892B1 (en) * | 2015-10-08 | 2016-07-04 | 엘지전자 주식회사 | Head Mount Display Device |
| CN106657971A (en) * | 2016-11-24 | 2017-05-10 | 文闻 | 360-degree 3D panoramic shooting device and shooting method |
| CN108253938B (en) * | 2017-12-29 | 2020-01-24 | 武汉大学 | TBM rock breaking slag digital close-range photogrammetry recognition and inversion method |
| CN110553585A (en) * | 2018-09-05 | 2019-12-10 | 天目爱视（北京）科技有限公司 | 3D information acquisition device based on optical array |
| CN111062987A (en) * | 2018-09-05 | 2020-04-24 | 天目爱视（北京）科技有限公司 | Virtual matrix type three-dimensional measurement and information acquisition device based on multiple acquisition regions |
| CN109658497B (en) * | 2018-11-08 | 2023-04-14 | 北方工业大学 | Three-dimensional model reconstruction method and device |
| CN109801374B (en) * | 2019-01-14 | 2023-02-24 | 盾钰（上海）互联网科技有限公司 | Method, medium, and system for reconstructing three-dimensional model through multi-angle image set |
| CN211373522U (en) * | 2019-12-12 | 2020-08-28 | 天目爱视（北京）科技有限公司 | Short-distance 3D information acquisition equipment and 3D synthesis, microscopy and attachment manufacturing equipment |
| CN111076674B (en) * | 2019-12-12 | 2020-11-17 | 天目爱视（北京）科技有限公司 | Closely target object 3D collection equipment |
-
2019
- 2019-12-12 CN CN201911288917.5A patent/CN111076674B/en active Active
-
2020
- 2020-12-09 WO PCT/CN2020/134763 patent/WO2021115301A1/en active Application Filing
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1793780A (en) * | 2005-12-05 | 2006-06-28 | 天津大学 | Measuring splice method and device of large three-dimensional body shape based on splicing target |
| CN201258235Y (en) * | 2008-08-21 | 2009-06-17 | 机械科学研究院浙江分院有限公司 | Multi-column lifting type operating platform |
| CN103075960A (en) * | 2012-12-30 | 2013-05-01 | 北京工业大学 | Multi-visual-angle great-depth micro stereo visual-features fusion-measuring method |
| CN206362712U (en) * | 2016-12-28 | 2017-07-28 | 京瓷精密工具（珠海）有限公司 | A kind of sword frontier inspection measurement equipment |
| CN109035379A (en) * | 2018-09-10 | 2018-12-18 | 天目爱视（北京）科技有限公司 | A kind of 360 ° of 3D measurements of object and information acquisition device |
| CN109443235A (en) * | 2018-11-02 | 2019-03-08 | 滁州市云米工业设计有限公司 | A kind of industrial design product collecting device for outline |
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