Scanning data processing method, device, equipment and medium

Abstract

The disclosed embodiments relate to a scanning data processing method, device, equipment and medium, wherein the method comprises: obtaining multiple frames of images to be processed including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values, processing is performed based on the multiple frames of images to be processed, all three-dimensional coordinate points in the same coordinate system are obtained in combination with the current camera posture, all three-dimensional coordinate points are measured and processed to obtain target three-dimensional coordinate points, and the target position transformation relationship is determined based on the target three-dimensional coordinate points and the distribution true values. The above technical solution is adopted to determine the target position transformation relationship based on the distribution true values ​​pre-set for the auxiliary feature points and the three-dimensional coordinate points calculated by scanning, so that the relative positions between the scanning rods can be accurately located, thereby improving the data processing efficiency and accuracy in the oral scanning scenario.

Description

Technical Field

[0001] The present disclosure relates to the field of intraoral scanning technology, and in particular to a scanning data processing method, device, equipment and medium. Background Art

[0002] Typically, in the restoration scenario of missing teeth in the oral cavity, a scanning rod is used to scan and determine the implant position.

[0003] In the related art, due to the limitation of the scanning range of oral scanning, a multi-data splicing solution is usually used when scanning intra-oral data. Due to the existence of cumulative errors, the overall accuracy of the model is ultimately low. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a scan data processing method, device, equipment and medium.

[0005] The present disclosure provides a method for processing scan data, the method comprising:

[0006] Acquire multiple frames of to-be-processed images including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values;

[0007] Processing is performed based on the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system;

[0008] Performing measurement processing on all the three-dimensional coordinate points to obtain the target three-dimensional coordinate point;

[0009] Based on the target three-dimensional coordinate points and the distribution true value, the target position transformation relationship is determined.

[0010] The present disclosure also provides a scanning data processing device, the device comprising:

[0011] An image acquisition module, used to acquire multiple frames of to-be-processed images including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values;

[0012] An image processing module, used for processing the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system;

[0013] A measurement processing module, used to measure and process all the three-dimensional coordinate points to obtain a target three-dimensional coordinate point;

[0014] The determination module is used to determine the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value.

[0015] An embodiment of the present disclosure also provides an electronic device, which includes: a processor; a memory for storing executable instructions of the processor; the processor is used to read the executable instructions from the memory and execute the instructions to implement the scan data processing method provided by the embodiment of the present disclosure.

[0016] The embodiment of the present disclosure further provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program is used to execute the scan data processing method provided by the embodiment of the present disclosure.

[0017] Compared with the prior art, the technical solution provided by the embodiment of the present disclosure has the following advantages: the scanning data processing solution provided by the embodiment of the present disclosure obtains multiple frames of images to be processed including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values, and are processed based on the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system, and all three-dimensional coordinate points are measured and processed to obtain the target three-dimensional coordinate points, and the target position transformation relationship is determined based on the target three-dimensional coordinate points and the distribution true values. By adopting the above technical solution, the target position transformation relationship is determined based on the distribution true values ​​pre-set for the auxiliary feature points and the three-dimensional coordinate points calculated by scanning, so that the relative positions between the scanning rods can be accurately located, thereby improving the data processing efficiency and accuracy in the oral scanning scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0019] Figure 1 An application scenario diagram of scanning data processing provided by an embodiment of the present disclosure;

[0020] Figure 2 A flowchart of a scan data processing method provided by an embodiment of the present disclosure;

[0021] Figure 3 A flowchart of another scan data processing method provided by an embodiment of the present disclosure;

[0022] Figure 4 A flowchart of another scan data processing method provided by an embodiment of the present disclosure;

[0023] Figure 5 A schematic diagram of the structure of a scanning data processing device provided by an embodiment of the present disclosure;

[0024] Figure 6A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0026] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0027] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0028] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0029] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0030] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0031] In practical applications, in the scenario of restoring missing teeth in the oral cavity, due to the limitation of the scanning range of the oral scan, a multi-data splicing solution is usually used when scanning the intra-oral data. Due to the existence of cumulative errors, the overall accuracy of the model is ultimately not high.

[0032] In view of the above problems, the present disclosure proposes a scanning data processing method, which can be applied to Figure 1 In the application environment shown. Figure 1An application scenario diagram of scanning data processing provided for an embodiment of the present disclosure, the application environment includes: installing multiple intraoral scanning rods in a target oral cavity, the intraoral scanning rods including: a scanning rod component 11, an auxiliary component 12 connected to the scanning rod component 11, auxiliary feature points are provided on the scanning rod component 11 and / or the auxiliary component 12, the scanning rod component 11 is adapted to an implant installed in the target oral cavity, and the intraoral scanning rod is installed in the target oral cavity by adapting and installing the scanning rod component 11 and the implant.

[0033] Among them, the auxiliary components 12 of any two intraoral scanning rods among the multiple intraoral scanning rods are adapted to each other, so that when any two intraoral scanning rods 10 are adjacently installed in the oral cavity, the auxiliary feature points on the two auxiliary components are continuously distributed, and the true value coordinate points of the auxiliary feature points can be obtained in advance through, for example, a SLR photogrammetry system, a three-coordinate measuring machine, etc. In theory, the three-dimensional coordinate points corresponding to the scanned image correspond one to one with the true value coordinate points of the auxiliary feature points obtained in advance.

[0034] As an example scenario, multiple intraoral scanning rods are installed in the target mouth, and the intraoral scanning rods include a scanning rod component for connecting to the implant and an auxiliary component connected to the scanning rod. The intraoral scanning rod is provided with a target feature, and the target feature is continuously distributed on the scanning rod and / or the auxiliary component, and the target feature is not distributed on one side of the scanning rod and / or the auxiliary component.

[0035] Specifically, the intraoral scanner scans the target oral cavity, obtains multiple frames of images, and transmits them to the data processing module for data processing. The data processing module executes the following method:

[0036] Acquire multiple frames of images, and acquire initial three-dimensional data of the target oral cavity based on the multiple frames of images, wherein the initial three-dimensional data includes an initial point set of the target oral cavity and three-dimensional coordinate measurement values ​​of target features in the same coordinate system;

[0037] Obtain the preset model of the intraoral scanning rod, which includes the three-dimensional coordinate true value of the target feature in the same coordinate system and the real point set of the intraoral scanning rod (the three-dimensional coordinate true value of each point)

[0038] Based on the correspondence between the three-dimensional coordinate measurement value and the true value of the target feature, the initial point set of the target oral cavity and the real point set of the intraoral scanning rod are spliced;

[0039] The positioning information of the intraoral scanning rod is determined based on the real point set of the spliced ​​intraoral scanning rod. The positioning information of the intraoral scanning rod is the positioning information of the implant. The tooth is designed based on the positioning information so that the designed tooth can be adapted and installed with the implant.

[0040] Specifically, by acquiring multiple frames of images to be processed including auxiliary feature points, wherein the auxiliary feature points have corresponding distribution true values, processing is performed based on the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system, all three-dimensional coordinate points are measured and processed to obtain target three-dimensional coordinate points, and based on the target three-dimensional coordinate points and the distribution true values, the target position transformation relationship is determined, and the target position transformation relationship is determined based on the distribution true values ​​pre-set for the auxiliary feature points and the three-dimensional coordinate points calculated by scanning, so that the relative positions between the scanning rods can be accurately located, thereby improving the data processing efficiency and accuracy in the oral scanning scenario.

[0041] Specifically, Figure 2 The present invention provides a flow chart of a scan data processing method provided by an embodiment of the present invention. The method can be executed by a scan data processing device, wherein the device can be implemented by software and / or hardware and can generally be integrated in an electronic device. Figure 2 As shown, the method includes:

[0042] Step 101: Acquire multiple frames of to-be-processed images including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values.

[0043] The scanning rod comprises a scanning rod body and an auxiliary feature body, and the scanning rod body is provided with auxiliary feature points; or the scanning rod body has no auxiliary feature points, and the auxiliary feature body between the scanning rod bodies is provided with auxiliary feature points.

[0044] Among them, the target oral cavity refers to the oral cavity where dental implants are required, and intraoral scanning is required to locate the implantation points in the oral cavity. The auxiliary components of any two intraoral scanning rods among multiple intraoral scanning rods are installed adjacent to each other in the target oral cavity in advance, and the auxiliary feature points on the two auxiliary components are continuously distributed, so that the target oral cavity can be scanned intraorally to obtain multiple frames of images to be processed.

[0045] Among them, the target oral cavity can be scanned by a handheld oral scanner (monocular or binocular camera), that is, multiple frames of images to be processed are obtained by taking pictures, for example, dozens of frames of images to be processed are collected per second, and the collection can be cyclic.

[0046] In the disclosed embodiment, the scanning rod is a feature object including auxiliary feature points, wherein the auxiliary feature points can uniquely identify a feature, i.e., auxiliary feature points are provided on the scanning rod, and each auxiliary feature point can uniquely identify a corresponding position feature on the scanning rod. For example, target feature a and target feature b are provided at position 1 and position 2 on the scanning rod, respectively, and target feature a can uniquely identify the position feature of position 1 on the scanning rod, and target feature b can uniquely identify the position feature of position 2 on the scanning rod.

[0047] It is understandable that different shapes, colors, two-dimensional codes, etc. on the scanning rod that have unique identification of corresponding position features on the scanning rod can be used as auxiliary feature points.

[0048] Specifically, the distribution true value of the auxiliary feature points or the distribution true value of the auxiliary feature points of computer-aided design, that is, the coordinate value of the auxiliary feature points, can be obtained through higher precision equipment, such as a SLR photogrammetry system, a three-coordinate measuring machine, etc.

[0049] In the disclosed embodiment, each scanned image to be processed includes at least a preset number of auxiliary feature points to indicate the continuity of the distribution of the auxiliary feature points, thereby ensuring the accuracy of subsequent calculations, wherein the preset number can be set according to the application scenario.

[0050] For example, the preset number is 3. When the scanned image to be processed includes 2 auxiliary feature points, it means that the auxiliary feature points are distributed discontinuously. When the scanned image to be processed includes 3 or more auxiliary feature points, it means that the auxiliary feature points are distributed continuously.

[0051] In the disclosed embodiments, there are many ways to obtain multiple frames of images to be processed. In some implementations, multiple frames of images to be processed are obtained by controlling a monocular camera to rotate in a certain direction while scanning the target oral cavity at a certain frequency.

[0052] In other embodiments, the binocular camera is controlled to scan the target oral cavity in a cycle to obtain multiple frames of images to be processed. The above two methods are only examples of obtaining multiple frames of images to be processed, and the embodiments of the present disclosure do not limit the specific methods of obtaining multiple frames of images to be processed.

[0053] Specifically, after the target oral cavity is connected to the scanning rod, the target oral cavity including the scanning rod is scanned to obtain multiple frames of images to be processed.

[0054] Step 102: Processing is performed based on multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system.

[0055] Among them, all three-dimensional coordinate points refer to the three-dimensional coordinate points corresponding to all auxiliary feature points in the target oral cavity.

[0056] In the embodiments of the present disclosure, there are many ways to obtain all three-dimensional coordinate points in the same coordinate system based on processing of multiple frames of images to be processed. In some implementations, the two-dimensional coordinate points of the auxiliary feature points in each frame of the image to be processed are obtained, and three-dimensional reconstruction is performed based on a preset intrinsic parameter matrix and the two-dimensional coordinate points to obtain the corresponding three-dimensional coordinate points of the auxiliary feature points of each frame of the image to be processed. The corresponding three-dimensional coordinate points of the auxiliary feature points of multiple frames of images to be processed are spliced ​​to obtain the three-dimensional coordinate points of the auxiliary feature points of multiple frames of images to be processed in the same coordinate system.

[0057] In other embodiments, the two-dimensional coordinate points of the auxiliary feature points in each frame of the image to be processed are obtained, and three-dimensional reconstruction is performed based on the relative position between the two cameras and the two-dimensional coordinate points to obtain the three-dimensional coordinate points corresponding to the auxiliary feature points of each frame of the image to be processed, and the three-dimensional coordinate points corresponding to the auxiliary feature points of multiple frames of images to be processed are spliced ​​to obtain the three-dimensional coordinate points of the auxiliary feature points of multiple frames of images to be processed in the same coordinate system. The above two methods are only examples of obtaining three-dimensional coordinate points in the same coordinate system by processing multiple frames of images to be processed. The embodiments of the present disclosure do not limit the specific method of obtaining three-dimensional coordinate points in the same coordinate system by processing multiple frames of images to be processed.

[0058] In the embodiment of the present disclosure, after acquiring multiple frames of images to be processed, processing can be performed based on the multiple frames of images to be processed to obtain three-dimensional coordinate points in the same coordinate system.

[0059] Step 103: measure and process the three-dimensional coordinate point to obtain the target three-dimensional coordinate point.

[0060] The target three-dimensional coordinate point refers to a three-dimensional coordinate point after the three-dimensional coordinate point is measured and processed, and can more accurately reflect the three-dimensional coordinate point of the auxiliary feature point.

[0061] In the embodiments of the present disclosure, all three-dimensional coordinate points are measured and processed to obtain target three-dimensional coordinate points in many ways. In some implementations, each three-dimensional coordinate point is projected onto an image coordinate system to obtain a two-dimensional pixel coordinate point. When the Euclidean distance between the two-dimensional pixel coordinate point and the two-dimensional coordinate point corresponding to the three-dimensional coordinate point is the smallest, the three-dimensional coordinate point is used as the target three-dimensional coordinate point.

[0062] In other embodiments, the Nth frame image in which the three-dimensional coordinate point appears is obtained, the two-dimensional pixel coordinate point of the Nth frame image is obtained, and the target three-dimensional coordinate point is determined based on the distance between the two-dimensional coordinate point projected by the three-dimensional coordinate point and the two-dimensional pixel coordinate point; wherein N is a positive integer. The above two methods are only examples of measuring and processing all three-dimensional coordinate points to obtain the target three-dimensional coordinate point. The embodiments of the present disclosure do not limit the specific method of measuring and processing all three-dimensional coordinate points to obtain the target three-dimensional coordinate point.

[0063] Specifically, after all three-dimensional coordinate points are acquired, all three-dimensional coordinate points may be measured and processed to obtain target three-dimensional coordinate points.

[0064] Step 104: Determine the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value.

[0065] The target position transformation relationship refers to a transformation matrix that converts the target three-dimensional coordinate points obtained by scanning into the corresponding designed distribution true value.

[0066] In the embodiments of the present disclosure, there are many ways to determine the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value. In some implementations, calculations are performed based on a preset scaling factor, the target three-dimensional coordinate point, and the distribution true value to obtain an initial position transformation relationship. The scaling factor, the target three-dimensional coordinate point, the distribution true value, and the initial position transformation relationship are optimized based on a preset optimization formula to obtain an optimized value. The scaling factor and the initial position transformation relationship are adjusted, and the initial position transformation relationship corresponding to the optimization value being less than a preset threshold is obtained as the target position transformation relationship.

[0067] In other embodiments, the position transformation relationship from each target three-dimensional coordinate point to the distribution true value is calculated, and the target position transformation relationship is obtained based on multiple position transformation relationships. The above two methods are only examples of determining the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value. The embodiments of the present disclosure do not limit the specific method of determining the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value.

[0068] The scanning data processing scheme provided by the embodiment of the present disclosure obtains multiple frames of images to be processed; wherein each frame of the images to be processed includes auxiliary feature points, and the auxiliary feature points have corresponding distribution true values. The multiple frames of images to be processed are processed to obtain all three-dimensional coordinate points, and all three-dimensional coordinate points are measured and processed to obtain target three-dimensional coordinate points. Based on the target three-dimensional coordinate points and the distribution true values, the target position transformation relationship is determined. The above technical scheme is adopted to determine the target position transformation relationship based on the distribution true values ​​pre-set by the auxiliary feature points and the three-dimensional coordinate points calculated by scanning, so that the relative positions between the scanning rods can be accurately located, thereby improving the data processing efficiency and accuracy in the oral scanning scenario.

[0069] Based on the description of the above embodiments, scanning can be performed by using a monocular camera and a binocular camera. Figure 3 and Figure 4 A detailed description is given for monocular camera and binocular camera respectively.

[0070] Specifically, Figure 3 This is a flow chart of another scan data processing method provided by an embodiment of the present disclosure. This embodiment further optimizes the scan data processing method based on the above embodiment. Figure 3 As shown, the method includes:

[0071] Step 201, control the scanning device to rotate in a preset direction and scan the target oral cavity including the scanning rod at a preset frequency to obtain multiple frames of images to be processed; wherein the auxiliary feature points have corresponding distribution true values.

[0072] Specifically, a monocular camera is controlled to rotate in a certain direction and scan the target oral cavity at a certain frequency to obtain multiple frames of images to be processed, or a binocular camera is controlled to scan the target oral cavity in a cycle to obtain multiple frames of images to be processed.

[0073] Step 202: obtain the two-dimensional coordinate points of the auxiliary feature points in each frame of the image to be processed, calculate based on the preset internal parameter matrix and the two-dimensional coordinate points to obtain the three-dimensional coordinate points of each frame of the image to be processed, and splice the three-dimensional coordinate points of each frame of the image to be processed to obtain all three-dimensional coordinate points in the same coordinate system.

[0074] Specifically, multiple frames of images to be processed are acquired through scanning (for example, by taking photos through hardware triggering, dozens of frames of images to be processed are acquired in one second, and the acquisition is cyclic), and based on the images to be processed, the two-dimensional coordinate points of the auxiliary feature points in each frame of the images to be processed are acquired (that is, the image recognition processing method is to extract the pixel coordinates of the auxiliary feature points on each frame of the images to be processed), and then according to the internal parameters of the camera (such as focal length, principal point, tilt factor and lens distortion) and the posture of texture tracking (for example, by acquiring the geometry and texture information of the surface of the scanning rod and splicing adjacent frames), the reconstruction of the auxiliary feature points of the current frame is completed, and the reconstructed three-dimensional coordinate points are based on the first frame camera coordinate system during scanning (the first frame camera coordinate system is determined by the first frame image, and each subsequent frame is spliced ​​with the first frame, so the coordinate system is the first frame camera coordinate system; the image recognizes the two-dimensional coordinate points, which need to be converted to the camera coordinate system to obtain the three-dimensional coordinate points).

[0075] The intrinsic parameter matrix refers to the matrix composed of the intrinsic parameters of the camera, so that the two-dimensional coordinate points are back-projected into the camera coordinate system based on the intrinsic parameter matrix to obtain the three-dimensional coordinate points.

[0076] Specifically, the three-dimensional coordinate points of each frame of the image to be processed are spliced ​​to obtain all the three-dimensional coordinate points. Based on the preset splicing algorithm, the two frames of different coordinate systems can be aligned through their common parts, so as to splice them together to obtain all the three-dimensional coordinate points. That is, the three-dimensional coordinate points reconstructed from all single frames are fused into the overall framework points, i.e., all the three-dimensional coordinate points, according to the distance constraint, and all the three-dimensional coordinate points are based on the overall tooth model coordinate system (world coordinate system).

[0077] Step 203: Project each 3D coordinate point onto the image coordinate system to obtain a 2D pixel coordinate point. When the Euclidean distance between the 2D pixel coordinate point and the 2D coordinate point corresponding to the 3D coordinate point is the smallest, use the 3D coordinate point as the target 3D coordinate point.

[0078] Specifically, assuming that the Kth auxiliary feature point p3D kAppearing in the i-th frame image, the texture map of the i-th frame (the acquisition of black and white images and texture maps with color information can be triggered at the same time) corresponds to the j-th two-dimensional coordinate point p2D j ,Photogrammetry optimization is based on bundle adjustment theory, based on the least squares theory, optimization target: all auxiliary feature points actually scanned, according to the number of image frames in which they appear and the camera posture T i The Euclidean distance between the two-dimensional pixel coordinates projected (projection function is defined as Π) onto each frame of the image and the corresponding two-dimensional coordinates of the auxiliary feature points is the smallest, and the calculation is shown in formula (1):

[0079]

[0080] Wherein, m represents the number of three-dimensional coordinate points, and n represents the number of images to be processed.

[0081] Step 204: Calculate based on the preset scaling factor, target three-dimensional coordinate point and distribution true value to obtain the initial position transformation relationship, and optimize the scaling factor, target three-dimensional coordinate point, distribution true value and initial position transformation relationship based on the preset optimization formula to obtain the optimized value.

[0082] Step 205: adjust the scaling factor and the initial position transformation relationship, and obtain the initial position transformation relationship corresponding to when the optimization value is less than a preset threshold as the target position transformation relationship.

[0083] Specifically, according to the distribution true value of the auxiliary feature points on the scanning rod or the auxiliary feature body connected to the scanning rod (for example, the distribution true value of the auxiliary feature points is obtained by a SLR photogrammetry system, a two-dimensional imager, etc.), denoted as q i , the target three-dimensional coordinate point P after the above photogrammetry optimization is spliced ​​with the distribution true value of the auxiliary feature points of each area (each scanning rod can be considered as a small area) with scaling (splicing is a rigid body and does not change the scale. When the scale changes, the Si scaling factor calculation is introduced to determine the target position transformation relationship of different scanning rods. minf() refers to the nonlinear least squares algorithm, as shown in formula (2):

[0084] minf(s i ,R i ,t i )=s i *R i *p+t i -q i (2)

[0085] Specifically, assuming Si = 1 (the actual value may be between 0.9 and 1.1), then through P and q i Calculate an initial (R i ,t i), and finally the assumed Si and initial (R i ,t i ), put them together for optimization, the optimization goal is to make point P scaled by Si and then pass the initial (R i ,t i ) can be combined with q i The whole optimization is a mathematical iterative process, which is to constantly adjust Si, (R i ,t i ), so that the spliced ​​P and q i The two points are infinitely close.

[0086] Therefore, by scanning the entire oral cavity, the relative positions between the scanning rods can be accurately located.

[0087] The scanning data processing scheme provided by the embodiment of the present disclosure obtains multiple frames of to-be-processed images including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values, obtains the two-dimensional coordinate points of the auxiliary feature points in each frame of the to-be-processed image, calculates based on a preset internal parameter matrix and the two-dimensional coordinate points to obtain the three-dimensional coordinate points of each frame of the to-be-processed image, splices the three-dimensional coordinate points of each frame of the to-be-processed image to obtain all three-dimensional coordinate points in the same coordinate system, projects each three-dimensional coordinate point onto the image coordinate system to obtain a two-dimensional pixel coordinate point, and when the Euclidean distance between the two-dimensional pixel coordinate point and the two-dimensional coordinate point corresponding to the three-dimensional coordinate point is minimum, uses the three-dimensional coordinate point as the target three-dimensional coordinate point, calculates based on a preset scaling factor, the target three-dimensional coordinate point and the distribution true value to obtain an initial position transformation relationship, optimizes and calculates the scaling factor, the target three-dimensional coordinate point, the distribution true value and the initial position transformation relationship based on a preset optimization formula to obtain an optimized value, adjusts the scaling factor and the initial position transformation relationship, and obtains the initial position transformation relationship corresponding to the optimization value being less than a preset threshold as the target position transformation relationship. Therefore, the target position transformation relationship is determined based on the pre-set distribution true value of the auxiliary feature point and the three-dimensional coordinate points calculated by scanning, so that the relative position between the scanning rods can be accurately located, thereby improving the data processing efficiency and accuracy in the oral scanning scenario.

[0088] Specifically, Figure 4 This is a flow chart of another scan data processing method provided by the embodiment of the present disclosure. This embodiment further optimizes the scan data processing method based on the above embodiment. Figure 4 As shown, the method includes:

[0089] Step 301, control the scanning device to rotate in a preset direction and scan the target oral cavity including the scanning rod at a preset frequency to obtain multiple frames of images to be processed; wherein the auxiliary feature points have corresponding distribution true values.

[0090] Specifically, a monocular camera is controlled to rotate in a certain direction and scan the target oral cavity at a certain frequency to obtain multiple frames of images to be processed, or a binocular camera is controlled to scan the target oral cavity in a cycle to obtain multiple frames of images to be processed.

[0091] Step 302, obtain the two-dimensional coordinate points of the auxiliary feature points in each frame of the image to be processed, calculate based on the relative position between the two cameras and the two-dimensional coordinate points, obtain the three-dimensional coordinate points of each frame of the image to be processed, and splice the three-dimensional coordinate points of each frame of the image to be processed to obtain all three-dimensional coordinate points in the same coordinate system.

[0092] Specifically, the image to be processed is acquired by scanning, and based on the image to be processed, the two-dimensional coordinate points of the auxiliary feature points in each frame of the image to be processed are acquired, and based on the relative position between the two cameras, the three-dimensional coordinate points of the auxiliary feature points of a single frame are reconstructed, and the reconstructed three-dimensional coordinate points are based on the left camera coordinate system of the current frame (usually the reconstructed depth information is based on the left camera coordinate system).

[0093] Specifically, according to the three-dimensional coordinate points of the auxiliary feature points reconstructed in each frame, based on the distance distribution information of the auxiliary feature points of adjacent frames (the distance between the coordinate points of two auxiliary feature points can be calculated), the same auxiliary feature point captured in adjacent frames is searched, and the auxiliary feature points are spliced ​​to obtain all three-dimensional coordinate points. That is, the three-dimensional coordinate points reconstructed from all single frames are fused into the overall framework points, i.e., all three-dimensional coordinate points, according to the distance constraints, and all the three-dimensional coordinate points are based on the overall tooth model coordinate system (world coordinate system).

[0094] Step 303: Project each 3D coordinate point onto the image coordinate system to obtain a 2D pixel coordinate point. When the Euclidean distance between the 2D pixel coordinate point and the 2D coordinate point corresponding to the 3D coordinate point is the smallest, use the 3D coordinate point as the target 3D coordinate point.

[0095] Specifically, assuming that the Kth auxiliary feature point p3D k Appears in the i-th frame, and corresponds to the j-th two-dimensional point p2DL on the texture map of the i-th frame j ,p2DR j , the rigid body transformation between the two eyes is T RL Photogrammetry optimization is based on bundle adjustment theory. The optimization goal is to find all auxiliary feature points actually scanned according to the number of image frames in which they appear and the camera posture T. i The Euclidean distance between the two-dimensional pixel coordinates projected (projection function is defined as Π) onto each frame of the image and the corresponding two-dimensional coordinates of the auxiliary feature points is the smallest, and the calculation is shown in formula (3):

[0096]

[0097] Wherein, m represents the number of three-dimensional coordinate points, and n represents the number of images to be processed.

[0098] Step 304: Calculate based on the preset scaling factor, target three-dimensional coordinate point and distribution true value to obtain the initial position transformation relationship, and optimize the scaling factor, target three-dimensional coordinate point, distribution true value and initial position transformation relationship based on the preset optimization formula to obtain the optimized value.

[0099] Step 305: adjust the scaling factor and the initial position transformation relationship, and obtain the initial position transformation relationship corresponding to when the optimization value is less than a preset threshold as the target position transformation relationship.

[0100] Specifically, according to the distribution true value of the auxiliary feature points on the scanning rod or the auxiliary feature body connected to the scanning rod (for example, the distribution true value of the auxiliary feature points is obtained by a SLR photogrammetry system, a two-dimensional imager, etc.), denoted as q i , the target three-dimensional coordinate point P after the above photogrammetry optimization is spliced ​​with the distribution true value of the auxiliary feature points of each area (each scanning rod can be considered as a small area) with scaling (splicing is a rigid body and does not change the scale. When the scale changes, the Si scaling factor calculation is introduced to determine the target position transformation relationship of different scanning rods. minf() refers to the nonlinear least squares algorithm, as shown in formula (2):

[0101] minf(s i ,R i ,t i )=s i *R i *p+t i -q i (2)

[0102] Specifically, assuming Si = 1 (the actual value may be between 0.9 and 1.1), then through P and q i Calculate an initial (R i ,t i ), and finally the assumed Si and initial (R i ,t i ), put them together for optimization, the optimization goal is to make point P scaled by Si and then pass the initial (R i ,t i ) can be combined with q i The whole optimization is a mathematical iterative process, which is to constantly adjust Si, (R i ,t i ), so that the spliced ​​P and q i The two points are infinitely close.

[0103] Therefore, by scanning the entire oral cavity, the relative positions between the scanning rods can be accurately located.

[0104] The scanning data processing scheme provided by the embodiment of the present disclosure obtains multiple frames of to-be-processed images including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values, obtains two-dimensional coordinate points of the auxiliary feature points in each frame of the to-be-processed image, calculates based on the relative position between two cameras and the two-dimensional coordinate points to obtain three-dimensional coordinate points of each frame of the to-be-processed image, splices the three-dimensional coordinate points of each frame of the to-be-processed image to obtain all three-dimensional coordinate points in the same coordinate system, projects each three-dimensional coordinate point onto the image coordinate system to obtain a two-dimensional pixel coordinate point, and when the Euclidean distance between the two-dimensional pixel coordinate point and the two-dimensional coordinate point corresponding to the three-dimensional coordinate point is minimum, uses the three-dimensional coordinate point as the target three-dimensional coordinate point, calculates based on a preset scaling factor, the target three-dimensional coordinate point and the distribution true value to obtain an initial position transformation relationship, optimizes and calculates the scaling factor, the target three-dimensional coordinate point, the distribution true value and the initial position transformation relationship based on a preset optimization formula to obtain an optimized value, adjusts the scaling factor and the initial position transformation relationship, and obtains the initial position transformation relationship corresponding to the optimization value being less than a preset threshold as the target position transformation relationship. Therefore, the target position transformation relationship is determined based on the pre-set distribution true value of the auxiliary feature point and the three-dimensional coordinate points calculated by scanning, so that the relative position between the scanning rods can be accurately located, thereby improving the data processing efficiency and accuracy in the oral scanning scenario.

[0105] Figure 5 This is a schematic diagram of the structure of a scanning data processing device provided by an embodiment of the present disclosure. The device can be implemented by software and / or hardware and can generally be integrated into an electronic device. Figure 5 As shown, the device comprises:

[0106] The image acquisition module 401 is used to acquire multiple frames of to-be-processed images including auxiliary feature points; wherein the auxiliary feature points have corresponding distribution true values;

[0107] An image processing module 402 is used to process the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system;

[0108] The measurement processing module 403 is used to perform measurement processing on all the three-dimensional coordinate points to obtain the target three-dimensional coordinate point;

[0109] The determination module 404 is used to determine the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value.

[0110] Optionally, the image processing module 402 is specifically used for:

[0111] Obtaining two-dimensional coordinate points of auxiliary feature points in each frame of the image to be processed;

[0112] Calculating based on a preset internal parameter matrix and the two-dimensional coordinate points to obtain the three-dimensional coordinate points of each frame of the image to be processed;

[0113] The three-dimensional coordinate points of each frame of the image to be processed are spliced ​​to obtain all the three-dimensional coordinate points in the same coordinate system.

[0114] Optionally, the image processing module 402 is specifically used for:

[0115] Obtaining two-dimensional coordinate points of auxiliary feature points in each frame of the image to be processed;

[0116] Calculate based on the relative position between the two cameras and the two-dimensional coordinate points to obtain the three-dimensional coordinate points of each frame of the image to be processed;

[0117] The three-dimensional coordinate points of each frame of the image to be processed are spliced ​​to obtain all the three-dimensional coordinate points in the same coordinate system.

[0118] Optionally, the measurement processing module 403 is specifically used to:

[0119] Projecting each of the three-dimensional coordinate points onto the image coordinate system to obtain a two-dimensional pixel coordinate point;

[0120] When the Euclidean distance between the two-dimensional pixel coordinate point and the two-dimensional coordinate point corresponding to the three-dimensional coordinate point is the smallest, the three-dimensional coordinate point is used as the target three-dimensional coordinate point.

[0121] Optionally, the determining module 404 is specifically configured to:

[0122] Calculating based on a preset scaling factor, the target three-dimensional coordinate point and the distribution true value to obtain an initial position transformation relationship;

[0123] Based on a preset optimization formula, the scaling factor, the target three-dimensional coordinate point, the distribution true value and the initial position transformation relationship are optimized and calculated to obtain an optimized value;

[0124] The scaling factor and the initial position transformation relationship are adjusted, and the initial position transformation relationship corresponding to when the optimization value is less than a preset threshold is obtained as the target position transformation relationship.

[0125] Optionally, the image acquisition module 401 is specifically used for:

[0126] The scanning device is controlled to rotate in a preset direction and scan the target oral cavity including the scanning rod at a preset frequency to obtain the multiple frames of images to be processed.

[0127] The scan data processing device provided in the embodiments of the present disclosure can execute the scan data processing method provided in any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects of the execution method.

[0128] The embodiments of the present disclosure also provide a computer program product, including a computer program / instruction, which implements the scan data processing method provided by any embodiment of the present disclosure when the computer program / instruction is executed by a processor.

[0129] Figure 6 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Figure 6 , which shows a schematic diagram of the structure of an electronic device 500 suitable for implementing the embodiment of the present disclosure. The electronic device 500 in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0130] like Figure 6 As shown, the electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0131] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0132] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the scan data processing method of the embodiment of the present disclosure are executed.

[0133] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0134] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0135] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0136] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: receives an information display trigger operation from a user during video playback; obtains at least two target information associated with the video; displays a first target information among the at least two target information in an information display area on a playback page of the video, wherein the size of the information display area is smaller than the size of the playback page; receives a first switching trigger operation from a user, and switches the first target information displayed in the information display area to the second target information among the at least two target information.

[0137] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0138] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0139] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0140] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0141] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0142] According to one or more embodiments of the present disclosure, the present disclosure provides an electronic device, including:

[0143] processor;

[0144] a memory for storing instructions executable by the processor;

[0145] The processor is used to read the executable instructions from the memory and execute the instructions to implement any scan data processing method provided in the present disclosure.

[0146] According to one or more embodiments of the present disclosure, the present disclosure provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program is used to execute any scan data processing method provided by the present disclosure.

[0147] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0148] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0149] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A scanning data processing method, applied to a scanning scenario where a plurality of scanning rods are installed in a target oral cavity, comprising: Acquire multiple frames of to-be-processed images including multiple auxiliary feature points on the surface of the scanning rod; wherein the multiple auxiliary feature points on the surface of the scanning rod respectively have corresponding distribution true values; Processing is performed based on the multiple frames of images to be processed to obtain three-dimensional coordinate points of multiple auxiliary feature points on the surface of the scanning rod in the same coordinate system; Measuring and processing the three-dimensional coordinate points of the auxiliary feature points on the surface of the plurality of scanning rods to obtain the target three-dimensional coordinate points; Determine the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value of the plurality of scanning rod surface auxiliary feature points; The relative positions of the plurality of scanning rods are located based on the target position transformation relationship.

2. The scanning data processing method according to claim 1, characterized in that: The processing based on the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system includes: Obtaining two-dimensional coordinate points of auxiliary feature points in each frame of the image to be processed; Calculating based on a preset internal parameter matrix and the two-dimensional coordinate points to obtain the three-dimensional coordinate points of each frame of the image to be processed; The three-dimensional coordinate points of each frame of the image to be processed are spliced ​​to obtain all the three-dimensional coordinate points in the same coordinate system.

3. The scanning data processing method according to claim 1, characterized in that: The processing based on the multiple frames of images to be processed to obtain all three-dimensional coordinate points in the same coordinate system includes: Obtaining two-dimensional coordinate points of auxiliary feature points in each frame of the image to be processed; Calculate based on the relative position between the two cameras and the two-dimensional coordinate points to obtain the three-dimensional coordinate points of each frame of the image to be processed; The three-dimensional coordinate points of each frame of the image to be processed are spliced ​​to obtain all the three-dimensional coordinate points in the same coordinate system.

4. The scanning data processing method according to claim 1, characterized in that: The process of measuring and processing all three-dimensional coordinate points to obtain the target three-dimensional coordinate points includes: Projecting each of the three-dimensional coordinate points onto the image coordinate system to obtain a two-dimensional pixel coordinate point; When the Euclidean distance between the two-dimensional pixel coordinate point and the two-dimensional coordinate point corresponding to the three-dimensional coordinate point is the smallest, the three-dimensional coordinate point is used as the target three-dimensional coordinate point.

5. The scanning data processing method according to claim 1, characterized in that: Based on the target three-dimensional coordinate point and the distribution true value, determining the target position transformation relationship includes: Calculating based on a preset scaling factor, the target three-dimensional coordinate point and the distribution true value to obtain an initial position transformation relationship; Based on a preset optimization formula, the scaling factor, the target three-dimensional coordinate point, the distribution true value and the initial position transformation relationship are optimized and calculated to obtain an optimized value; The scaling factor and the initial position transformation relationship are adjusted, and the initial position transformation relationship corresponding to when the optimization value is less than a preset threshold is obtained as the target position transformation relationship.

6. The scanning data processing method according to claim 1, characterized in that: The step of acquiring multiple frames of images to be processed including auxiliary feature points comprises: The scanning device is controlled to rotate in a preset direction and scan the target oral cavity including the scanning rod at a preset frequency to obtain the multiple frames of images to be processed.

7. A scanning data processing device, characterized in that: Applicable to scanning scenarios where multiple scanning rods are installed in the target oral cavity, including: An image acquisition module is used to acquire multiple frames of to-be-processed images including multiple auxiliary feature points on the surface of the scanning rod; wherein the auxiliary feature points on the surface of the multiple scanning rods respectively have corresponding distribution true values; An image processing module, used for processing the multiple frames of images to be processed to obtain three-dimensional coordinate points of multiple auxiliary feature points on the surface of the scanning rod in the same coordinate system; A measurement processing module, used for measuring and processing the three-dimensional coordinate points of the auxiliary feature points on the surface of the plurality of scanning rods to obtain the target three-dimensional coordinate points; A determination module, used to determine the target position transformation relationship based on the target three-dimensional coordinate point and the distribution true value of the plurality of scanning rod surface auxiliary feature points; The relative positions of the plurality of scanning rods are located based on the target position transformation relationship.

8. The scanning data processing device according to claim 7, characterized in that: The image processing module is specifically used for: Obtaining two-dimensional coordinate points of auxiliary feature points in each frame of the image to be processed; Based on a preset internal parameter matrix, the current frame camera posture and the two-dimensional coordinate points are calculated to obtain the three-dimensional coordinate points of each frame of the image to be processed; The three-dimensional coordinate points of each frame of the image to be processed are spliced ​​to obtain all the three-dimensional coordinate points.

9. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the scan data processing method described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the scanning data processing method described in any one of claims 1 to 6.

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