Method, device, equipment, system and medium for visualizing point cloud alignment quality

Abstract

The embodiments of the present disclosure relate to a method, apparatus, device, medium and product for visualizing the alignment quality of a point cloud. The method obtains aligned homonymous point data, converts the three-dimensional coordinates of the homonymous points contained in the homonymous point data into two-dimensional pixel coordinates, determines the color of the homonymous points according to the position offset of the homonymous points relative to the position before alignment, determines the offset direction arrow of the homonymous points according to the offset direction of the homonymous points relative to the position before alignment, and draws homonymous points of corresponding colors and offset direction arrows of the homonymous points in a two-dimensional coordinate system based on the two-dimensional pixel coordinates of the homonymous points. Thus, based on the colors of the homonymous points and the offset direction arrows, the alignment quality of the point cloud can be intuitively and accurately displayed, thereby improving the detection efficiency of the point cloud alignment quality.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of high-precision map technology, and in particular to a method, apparatus, device, system, and medium for visualizing point cloud alignment quality. Background Art

[0002] Point cloud data collection involves multiple passes of point cloud data, and the resulting point cloud data may have coordinate deviations. Therefore, related technologies require alignment of the point cloud data after collection. However, the inventors of this application have discovered that existing technologies are unable to intuitively, accurately, and efficiently detect the alignment quality of point cloud data, resulting in low efficiency in alignment quality testing. Therefore, there is an urgent need to improve the efficiency of point cloud alignment quality testing. Summary of the Invention

[0003] In order to solve the above technical problems, the embodiments of the present disclosure provide a method, apparatus, device, system and medium for visualizing point cloud alignment quality.

[0004] A first aspect of an embodiment of the present disclosure provides a method for visualizing the quality of point cloud alignment, the method comprising: acquiring aligned homonymous point data; converting the three-dimensional coordinates of the homonymous points contained in the homonymous point data into two-dimensional pixel coordinates; determining the color of the homonymous points based on the position offset of the homonymous points relative to before alignment, and determining the offset direction arrow of the homonymous points based on the offset direction of the homonymous points relative to before alignment; and drawing the homonymous points of the color and the offset direction arrows of the homonymous points in a two-dimensional coordinate system based on the two-dimensional pixel coordinates of the homonymous points.

[0005] A second aspect of an embodiment of the present disclosure provides a method for visualizing the quality of point cloud alignment, the method comprising: obtaining visualization data of the aligned point cloud, the visualization data including data on the two-dimensional pixel coordinates, colors, and offset direction arrows of the aligned homonymous points in a two-dimensional coordinate system; displaying the homonymous points of the color and the offset direction arrows of the homonymous points on a display interface based on the two-dimensional pixel coordinates of the homonymous points; wherein the color of the homonymous points is related to the position offset of the homonymous points, and the offset direction arrows of the homonymous points are related to the offset direction of the homonymous points.

[0006] A third aspect of the embodiments of the present disclosure provides a point cloud alignment quality visualization device, the device comprising:

[0007] The first acquisition module is used to obtain the aligned homonymous point data;

[0008] A first conversion module, configured to convert the three-dimensional coordinates of the same-name points contained in the same-name point data into two-dimensional pixel coordinates;

[0009] a first determining module, configured to determine the color of the homonymous point according to the position offset of the homonymous point relative to the position before alignment, and to determine the offset direction arrow of the homonymous point according to the offset direction of the homonymous point relative to the position before alignment;

[0010] The first drawing module is configured to draw the same-name points of the color and the offset direction arrows of the same-name points in a two-dimensional coordinate system based on the two-dimensional pixel coordinates of the same-name points.

[0011] A fourth aspect of the embodiments of the present disclosure provides a point cloud alignment quality visualization device, including:

[0012] An acquisition module is used to acquire visualization data of the aligned point cloud, wherein the visualization data includes the two-dimensional pixel coordinates, colors, and offset direction arrows of the aligned points of the same name in the two-dimensional coordinate system;

[0013] A display module, configured to display the same-name points of the color and the offset direction arrows of the same-name points on a display interface based on the two-dimensional pixel coordinates of the same-name points;

[0014] The color of the same-name point is related to the position offset of the same-name point, and the offset direction arrow of the same-name point is related to the offset direction of the same-name point. A fifth aspect of the embodiments of the present disclosure provides a computer device, which includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor can perform the method of the first aspect above.

[0015] A sixth aspect of an embodiment of the present disclosure provides a terminal device, which includes a memory and a processor, wherein a computer program is stored in the memory. When the computer program is executed by the processor, the processor can execute the method of the above-mentioned second aspect.

[0016] The seventh aspect of the embodiment of the present disclosure provides a point cloud alignment quality visualization system, which includes the computer device referred to in the fifth aspect above and the terminal device referred to in the sixth aspect above, and the terminal device obtains visualization data from the computer device and displays it.

[0017] An eighth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a computer device, the computer device can execute the method of the first or second aspect above.

[0018] A ninth aspect of the embodiments of the present disclosure provides a computer program product, which is stored in a storage medium. When the computer program product is executed by a computer device, the computer device can execute the method of the first or second aspect above.

[0019] Compared with related technologies, the technical solution provided by the embodiments of the present disclosure has the following advantages:

[0020] The disclosed embodiment obtains the data of homonymous points after alignment, converts the three-dimensional coordinates of the homonymous points contained in the homonymous point data into two-dimensional pixel coordinates, determines the color of the homonymous points according to the position offset of the homonymous points relative to the position before alignment, determines the offset direction arrow of the homonymous points according to the offset direction of the homonymous points relative to the position before alignment, and draws homonymous points of corresponding colors and offset direction arrows of the homonymous points in the two-dimensional coordinate system based on the two-dimensional pixel coordinates of the homonymous points. Therefore, based on the color of the homonymous points and the offset direction arrows, the alignment quality of the point cloud can be displayed intuitively and accurately, thereby improving the detection efficiency of the point cloud alignment quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0022] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0023] Figure 1 is a schematic diagram of a point cloud alignment quality visualization scene provided by an embodiment of the present disclosure;

[0024] Figure 2 is a flow chart of a method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure;

[0025] Figure 3 is a schematic diagram of a coordinate conversion method provided by an embodiment of the present disclosure;

[0026] Figure 4 is a schematic diagram of another coordinate conversion method provided by an embodiment of the present disclosure;

[0027] Figure 5 is a flow chart of a method for determining the color of points of the same name provided by an embodiment of the present disclosure;

[0028] Figure 6 is a flowchart of another method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure;

[0029] Figure 7 is a flowchart of another method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure;

[0030] Figure 8 is a flowchart of another method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure;

[0031] Figure 9 Schematic diagram of a point cloud alignment quality visualization device provided by an embodiment of the present disclosure;

[0032] Figure 10 It is a structural diagram of a computer device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0033] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features therein can be combined with each other in the absence of conflict.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0035] In order to better understand the technical solutions of the embodiments of the present disclosure, some of the terms involved in the embodiments of the present disclosure are first explained.

[0036] A point cloud refers to a collection of three-dimensional points with attributes such as three-dimensional coordinates and reflectivity collected by collection equipment such as laser collection vehicles.

[0037] Point cloud alignment refers to the process of correcting the coordinate deviations of two collected point cloud data (hereinafter referred to as two passes of point cloud data) to form a single pass of point cloud data.

[0038] Alignment quality refers to the degree of deviation of parameters such as the position offset and offset direction of a 3D point from the corresponding reference threshold during the alignment process. The smaller the deviation, the better the alignment quality, and the larger the deviation, the worse the alignment quality.

[0039] Homologous points refer to three-dimensional points whose feature similarity is higher than a preset threshold after feature matching of two or more point cloud data.

[0040] For example, Figure 1 This is a schematic diagram of a point cloud alignment quality visualization scene provided by an embodiment of the present disclosure. Figure 1 The collection device 10, the server 11 and the terminal device 12 are shown as an example.

[0041] exist Figure 1In the figure, the acquisition device 10 can be exemplarily understood as a device such as a point cloud acquisition vehicle or an unmanned aerial vehicle that has point cloud data acquisition and data transmission capabilities. The server 11 can be exemplarily understood as a device that has data transmission and reception capabilities and data processing capabilities. The server 11 is used to perform point cloud data alignment processing, identify points of the same name, and visualize the alignment quality of the point cloud data. The terminal device 12 can be, for example, a desktop computer, a laptop computer, or other device that has data transmission and reception capabilities and data rendering capabilities. The terminal device 12 is used to obtain visualization data of the point cloud data alignment quality from the server 11 and to visualize the alignment quality of the point cloud data based on the visualization data.

[0042] In actual scenarios, there can be one or more collection devices 10. When there are multiple collection devices 10, the multiple collection devices 10 can be configured to perform one or more point cloud data collection tasks along the same route and in the same area. When there is only one collection device 10, the collection device 10 is configured to perform multiple point cloud data collection tasks along the same route. The point cloud data collected by the collection device 10 is uploaded to the server 11 in real time or periodically.

[0043] The server 11 performs alignment processing and homonymous point identification processing on the multiple passes of point cloud data collected by the above-mentioned multiple acquisition devices, or the multiple passes of point cloud data collected by a single acquisition device, to obtain aligned homonymous point data. The alignment quality is then visualized based on the aligned homonymous point data. The terminal device 12 can obtain the visualization data from the server 11 via a wired or wireless link and render and display it. The method for aligning the point cloud data and identifying homonymous points by the server 11 can be found in related art and will not be elaborated on here.

[0044] It should be noted that in a scenario involving multiple acquisition devices 10, before the server 11 performs alignment processing and same-name point recognition processing on the point cloud data, it is also necessary to perform format conversion processing on the received point cloud data so that the formats of the point cloud data of multiple acquisition devices are converted into the same format, thereby facilitating data processing.

[0045] Of course, the above scenario is only an exemplary scenario, not the only scenario. For example, in other implementations, the server 11 may also perform alignment processing and homonymous point recognition processing on the point cloud data, while other pre-configured devices may perform visualization processing of the alignment quality.

[0046] The following describes a method for visualizing alignment quality with reference to exemplary embodiments.

[0047] For example, Figure 2is a flow chart of a method for visualizing the quality of point cloud alignment provided by an embodiment of the present disclosure. This method can be exemplarily executed by the server 11 in the above scenario. Figure 2 , the visualization method provided by the embodiment of the present disclosure includes:

[0048] Step 201: Acquire aligned homonymous point data.

[0049] In some implementations of the disclosed embodiments, the homonymous point data may include the 3D coordinates of the homonymous points after alignment and the 3D coordinates before alignment. In this case, by calculating the difference in coordinates before and after alignment, the positional offset and offset direction of the homonymous points relative to the pre-alignment position can be obtained.

[0050] In other implementations of the disclosed embodiments, the homonymous point data may include data such as the three-dimensional coordinates of the homonymous points after alignment, the position offset and offset direction of the homonymous points after alignment relative to the position before alignment, and other data.

[0051] In yet other implementations of the disclosed embodiments, in addition to either of the two aforementioned implementations, the homonymous point data may further include information about the acquisition locations corresponding to the homonymous points. In practice, the movement trajectory of a capture device consists of a series of trajectory points. During movement, the capture device collects point cloud data at the locations of at least some of these trajectory points. These point cloud data include homonymous points. Therefore, the locations of the trajectory points that capture the homonymous points can be determined as the acquisition locations corresponding to the homonymous points.

[0052] Step 202: Convert the three-dimensional coordinates of the same-name points contained in the same-name point data into two-dimensional pixel coordinates.

[0053] In the embodiment of the present disclosure, the three-dimensional coordinates of the homonymous points included in the homonymous point data may be understood as the three-dimensional coordinates after the homonymous points are aligned.

[0054] In one implementation of the embodiment of the present disclosure, all the same-name points in the same-name point data may be converted into the same two-dimensional pixel coordinate system, or may be converted into different two-dimensional pixel coordinate systems.

[0055] In the case of converting all the same-name points into the same two-dimensional pixel coordinate system, the three-dimensional coordinates of all the same-name points contained in the same-name point data can be converted into the preset two-dimensional pixel coordinate system based on the conversion relationship between the preset three-dimensional coordinate system and the preset two-dimensional pixel coordinate system to obtain the two-dimensional pixel coordinates of the same-name points. For example, Figure 3 is a schematic diagram of a coordinate conversion method provided by an embodiment of the present disclosure, such as Figure 3As shown, in an exemplary embodiment, the three-dimensional coordinates of the same-name points can be understood as coordinates in the world coordinate system, which can be composed of longitude, latitude and elevation. In this case, the longitude and latitude data in the three-dimensional coordinates can be first extracted to obtain two-dimensional longitude and latitude coordinates, and then the longitude and latitude coordinates can be converted into two-dimensional pixel coordinates in the two-dimensional pixel coordinate system according to the conversion relationship between the pre-set longitude and latitude coordinates and the preset two-dimensional pixel coordinate system. Of course, Figure 3 This is only an example of the coordinate conversion method and is not the only limitation.

[0056] In another case, the acquisition area of ​​the acquisition device can be divided into multiple area blocks, each area block corresponds to a two-dimensional pixel coordinate system. When executing the step of converting the three-dimensional coordinates of the same-name points contained in the same-name point data into two-dimensional pixel coordinates, the area block where the same-name points are located can be determined based on the three-dimensional coordinates of the same-name points or the coordinates of the acquisition positions corresponding to the same-name points. Then, based on the conversion relationship between the pre-set three-dimensional coordinate system and the two-dimensional pixel coordinate system corresponding to the area block, the three-dimensional coordinates of the same-name points can be converted into two-dimensional pixel coordinates under the corresponding two-dimensional pixel coordinate system. For example, Figure 4 This is a schematic diagram of another coordinate conversion method provided by the embodiment of the present disclosure. Figure 4 The acquisition area of ​​the acquisition device is exemplarily divided into 6 area blocks, each area block corresponds to a three-dimensional coordinate range. Assuming that the three-dimensional coordinates of the same-name point A or the three-dimensional coordinates of the acquisition position corresponding to the same-name point A belong to the three-dimensional coordinate range corresponding to area block 1, then according to the preset conversion relationship, the three-dimensional coordinates of the same-name point A are converted into the two-dimensional pixel coordinate system corresponding to area block 1 to obtain the two-dimensional pixel coordinates of the same-name point A. If the three-dimensional coordinates of the same-name point B or the three-dimensional coordinates of the acquisition position corresponding to the same-name point B belong to the three-dimensional coordinate range corresponding to area block 2, then according to the preset conversion relationship, the three-dimensional coordinates of the same-name point B are converted into the two-dimensional pixel coordinate system corresponding to area block 2 to obtain the two-dimensional pixel coordinates of the same-name point B. This process is repeated until the three-dimensional coordinates of all the same-name points in the same-name point data are converted into corresponding two-dimensional pixel coordinates.

[0057] Of course, the above two coordinate conversion situations are only examples and are not limited to the following. In practice, corresponding coordinate conversion strategies can be set as needed.

[0058] Step 203: Determine the color of the homonymous points according to the positional offset of the homonymous points relative to the position before alignment, and determine the offset direction arrow of the homonymous points according to the offset direction of the homonymous points relative to the position before alignment.

[0059] The embodiment of the present disclosure uses color to represent the degree of offset of the position of the homonymous points after alignment relative to the position before alignment. Different colors represent different degrees of offset. The degree of offset of the homonymous points can be represented by the position offset after alignment relative to the position before alignment. For example, in some implementations of the embodiment of the present disclosure, the position offset can be divided into multiple ranges based on the size of the position offset of the homonymous points. Different ranges correspond to different color gradient intervals. Within each color gradient interval, a specific value of the position offset corresponds to a unique specific color. In order to more clearly understand the color determination method of this implementation method, an example is given below to illustrate.

[0060] For example, Figure 5 This is a flow chart of a method for determining the color of points with the same name provided by an embodiment of the present disclosure. Figure 5 As shown, the method includes:

[0061] Step 501: Determine the component of the position offset of the same-name point in at least one preset direction.

[0062] In step 501, the preset direction may be one or more, and the number and orientation of the preset directions may be set as needed. For example, when the preset directions include the vehicle's moving direction, the vehicle's left-right direction, and the vehicle's up-down direction, the position offset components of the same-name point in the vehicle's moving direction, the vehicle's left-right direction, and the vehicle's up-down direction need to be determined separately. Of course, this is merely an example and does not specifically limit the preset directions.

[0063] Step 502: In response to at least one component exceeding a preset error range, determine the color of the same-name point based on a first association relationship between the position offset and the color.

[0064] In the disclosed embodiment, a corresponding error range can be set for each specific preset direction, and the error ranges corresponding to different preset directions can be the same or different. For example, in the example of step 501, corresponding error ranges can be set for the vehicle movement direction, the vehicle left-right direction, and the vehicle up-down direction, respectively. Assuming that the position offset of the same-name point has a component a1 in the vehicle movement direction, a component a2 in the vehicle left-right direction, and a component a3 in the vehicle up-down direction, and at least one of a1, a2, and a3 exceeds its corresponding error range, the color of the same-name point is determined based on a first association between the position offset and the color, where the first association can be, for example, a correspondence between the position offset and a color within a gradient range from green to red.

[0065] Step 503 : In response to the fact that the components in at least one preset direction do not exceed a preset error range, the color of the same-name point is determined based on a second association relationship between the position offset and the color.

[0066] Still taking the example in step 502 as an example, assuming that the position offset of the same-name point has a component a1 in the vehicle moving direction, a component a2 in the vehicle left-right direction, and a component a3 in the vehicle up-down direction, all exceeding their corresponding error ranges, then the color of the same-name point is determined based on a second association between the position offset and the color, wherein the first association and the second association correspond to different color ranges. For example, the second association may be a correspondence between the position offset and a color within a gradient range from blue to green.

[0067] certainly Figure 5 The embodiment of the present disclosure only provides an exemplary color determination method, not the only method. In fact, Figure 5 Two color ranges are established, and a corresponding relationship between position offset and color is established for each color range. In other embodiments, only one color range may be established, or three or more color ranges may be established, and a corresponding corresponding relationship between position offset and color may be established for each color range.

[0068] For example, in step 203 of the present embodiment, the direction of the arrow can also be used to indicate the offset direction of the position of the homonymous points after alignment relative to the position before alignment. The length of the arrow can be determined based on a pre-established correspondence between the arrow length and the position offset. The greater the position offset, the longer the arrow length, and the smaller the position offset, the smaller the arrow length.

[0069] Step 204 : Based on the two-dimensional pixel coordinates of the same-name points, draw the same-name points of corresponding colors and the offset direction arrows of the same-name points in the two-dimensional coordinate system.

[0070] For example, assuming the 2D pixel coordinates of a homonymous point are (x1, y1), then a homonymous point of a preset size is drawn at the position (x1, y1) and filled with the color determined by the above method. The starting point of the offset direction arrow for the homonymous point can be drawn at the homonymous point, pointing in the same direction as the offset of the homonymous point, and with a preset fixed length or a length determined by the size of the position offset.

[0071] The disclosed embodiment obtains the data of homonymous points after alignment, converts the three-dimensional coordinates of the homonymous points contained in the homonymous point data into two-dimensional pixel coordinates, determines the color and offset direction arrow of the homonymous points according to the position offset and offset direction of the homonymous points relative to before alignment, and draws homonymous points of corresponding colors and offset direction arrows of the homonymous points in the two-dimensional coordinate system based on the two-dimensional pixel coordinates of the homonymous points. Therefore, based on the color and offset direction arrows of the homonymous points, the alignment quality of the point cloud can be displayed intuitively and accurately, thereby improving the detection efficiency of the point cloud alignment quality.

[0072] Figure 6 This is a flowchart of another method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure. Figure 6 As shown in the above Figure 2 Based on the embodiment, the method for visualizing point cloud alignment quality provided by the embodiment of the present disclosure may further include the following steps:

[0073] Step 601: Cluster the points of the same name based on their two-dimensional pixel coordinates to obtain multiple sub-clustering clusters.

[0074] In step 601, points with the same name whose coordinate distance is less than a preset distance can be grouped into a pile to form a pile cluster. The number of points with the same name included in different pile clusters can be the same or different. The color and offset direction arrows of the points with the same name in the pile cluster are shown by Figure 2 The embodiment is confirmed.

[0075] Step 602: Determine the position offset and offset direction of the center of gravity of each sub-cluster based on the position offset and offset direction corresponding to each point of the same name contained in each sub-cluster.

[0076] In the embodiment of the present disclosure, for each stacking cluster, the position of the center of gravity of the stacking cluster can be determined based on the position of each point of the same name in the stacking cluster; the position offset of the center of gravity can be obtained by averaging the position offsets of each point of the same name in the stacking cluster, and using the average position offset as the position offset of the center of gravity. Alternatively, in order to improve the accuracy, after averaging to obtain the average position offset, the average position offset is summed with a preset first tolerance parameter, and the sum is used as the position offset of the center of gravity. The offset direction of the center of gravity can be obtained by averaging the offset directions of each point of the same name in the stacking cluster, and using the average offset direction as the offset direction of the center of gravity. Alternatively, in order to improve the accuracy, after calculating the average offset direction of each point of the same name in the stacking cluster, the average offset direction is summed with a preset second tolerance parameter, and the sum is used as the offset direction of the center of gravity.

[0077] Step 603: based on the position offset and offset direction of the center of gravity point and the number of points with the same name contained in the stacking cluster corresponding to the center of gravity point, draw an offset direction arrow of the center of gravity point at the position of the center of gravity point.

[0078] For example, in one implementation of step 603, the length of the offset direction arrow of the center of gravity point can be determined based on the correspondence between the position offset and the arrow length; the thickness of the offset direction arrow of the center of gravity point can be determined based on the number of points of the same name contained in the stacked clusters, and the correspondence between the pre-set number of points of the same name and the thickness of the arrow; the offset direction of the center of gravity point is used as the direction of the arrow, and then the offset direction arrow of the center of gravity point is drawn using the length, direction and thickness determined above.

[0079] Of course, the above is only an example and not the only limitation on the arrow drawing method. In fact, in other implementations, the length of the arrow can also be a preset fixed length, and the thickness of the arrow can also be a fixed thickness.

[0080] In the embodiment of the present disclosure, by clustering the data of points with the same name, a corresponding offset direction arrow is drawn for the center point of each cluster, and the average alignment quality of the points with the same name in the cluster is reflected by the offset direction arrow of the center point, thereby improving the efficiency of alignment quality detection.

[0081] Figure 7 This is a flowchart of another method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure. Figure 7 As shown, after drawing the offset direction arrows of the centroids of the various sub-clustering clusters, the visualization method provided by the embodiment of the present disclosure may further include the following steps:

[0082] Step 701: Perform multiple thinning processes on the centroids of multiple sub-heap clusters according to different thinning degrees to generate multiple images, which include the centroids obtained by thinning and the offset direction arrows of the centroids.

[0083] Step 702: Generate an image pyramid based on the multiple images obtained through thinning.

[0084] In the embodiment of the present disclosure, the degree of thinning corresponds to the scale of the display range of the visualization interface. The larger the scale, the higher the degree of thinning and the more severe the thinning. The smaller the scale, the lower the degree of thinning and the less severe the thinning. In practical applications, corresponding degrees of thinning can be set for different scales. Then, the centroids of all the obtained stacked clusters are thinned out with different degrees of thinning. One or more pictures are generated based on the centroids obtained by thinning out at each degree of thinning. The picture also includes the centroid obtained by thinning out and the offset direction arrow of the centroid.

[0085] After obtaining the corresponding images based on thinning at different scales, you can refer to related technologies to construct an image pyramid in order of scale from large to small or from small to large. The higher the part on the image pyramid, the larger the scale.

[0086] During the visualization display process of the disclosed embodiment, images at corresponding levels (also understood as heights) on the image pyramid can be obtained according to the scale of the target display and displayed on a display interface (such as a web page). The average alignment quality around the center of gravity point can be quickly obtained through the offset direction arrow of the center of gravity point displayed on the image, such as the length, thickness, and direction of the arrow.

[0087] For example, in some implementations provided by the embodiments of the present disclosure, a user interactive experience can also be provided. For example, when a user selects a certain center of gravity point or an offset direction arrow of a center of gravity point on a picture, the color, offset direction arrow and other information of all the same-name points in the sub-stack clustering cluster corresponding to the center of gravity point can be displayed on the display interface according to the pre-established correspondence between the center of gravity point and the sub-stack clustering cluster, so that the user can know the alignment quality around a certain position more intuitively and in detail. Furthermore, in another implementation provided by the embodiments of the present disclosure, the visualization method provided by the embodiments of the present disclosure can also provide users with a function of viewing three-dimensional coordinate information. When a user selects a certain point of the same name or an offset direction arrow of a point of the same name on the display interface, the three-dimensional coordinates of the point of the same name can also be displayed to the user. This allows users to grasp more detailed information and meet the needs of users to varying degrees.

[0088] The disclosed embodiment establishes an image pyramid and uses a hierarchical approach to display alignment quality at different scales with varying levels of detail, meeting the varying viewing needs of users and improving user experience. When a user discovers a location with low alignment quality, they can view the alignment details of the surrounding area. The correspondence between two-dimensional pixel coordinates and three-dimensional coordinates also allows users to view specific three-dimensional coordinate information, improving alignment quality viewing efficiency.

[0089] Figure 8 This is a flowchart of another method for visualizing point cloud alignment quality provided by an embodiment of the present disclosure. Figure 8 As shown, based on any of the above embodiments, the visualization method provided by the embodiment of the present disclosure may further include the following steps:

[0090] Step 801: Acquire aligned trajectory points, where the point cloud data collected at the positions of the trajectory points include points with the same name.

[0091] Step 802: Convert the three-dimensional coordinates of the trajectory points into corresponding two-dimensional pixel coordinates.

[0092] Step 803: determine the color of the track point according to the position offset of the track point relative to the position before alignment, and determine the offset direction arrow of the track point according to the offset direction of the track point relative to the position before alignment.

[0093] Step 804: Based on the two-dimensional pixel coordinates of the trajectory point, draw the trajectory point of the color and the offset direction arrow of the trajectory point in the two-dimensional coordinate system.

[0094] The execution method of the above steps 801-804 is the same as Figure 2 The embodiments are similar and will not be described again here.

[0095] The present disclosure also provides a method for visualizing the quality of point cloud alignment. The method can be executed by a terminal device, which can be exemplarily understood as Figure 1 The terminal device 12 in the illustrated scenario can, for example, obtain and display visualization data from the server in the above embodiment. Specific details are as follows:

[0096] S1. Obtain visualization data of the aligned point cloud, where the visualization data includes the two-dimensional pixel coordinates, colors, and offset direction arrows of the aligned points of the same name in the two-dimensional coordinate system.

[0097] S2. Based on the two-dimensional pixel coordinates of the homonymous points, display the homonymous points of the color and the offset direction arrows of the homonymous points on the display interface.

[0098] The color of the same-name point is related to the position offset of the same-name point, and the offset direction arrow of the same-name point is related to the offset direction of the same-name point.

[0099] The specific method for determining the two-dimensional pixel coordinates, color and offset direction arrow of the same-name point can refer to the above Figure 2-Figure 8 The embodiments in the embodiment will not be repeated in this embodiment. Figure 9 This is a schematic diagram of a point cloud alignment quality visualization device provided by an embodiment of the present disclosure. The device can be exemplarily understood as Figure 1 The server or some functional modules in the server in the embodiment, such as Figure 9 As shown, the point cloud alignment quality visualization device 90 includes:

[0100] A first acquisition module 91 is used to acquire aligned homonymous point data;

[0101] A first conversion module 92 is configured to convert the three-dimensional coordinates of the same-name points contained in the same-name point data into two-dimensional pixel coordinates;

[0102] A first determining module 93 is configured to determine the color of the homonymous point according to the position offset of the homonymous point relative to the position before alignment, and to determine the offset direction arrow of the homonymous point according to the offset direction of the homonymous point relative to the position before alignment;

[0103] The first drawing module 94 is configured to draw the same-name points of the colors and the offset direction arrows of the same-name points in a two-dimensional coordinate system based on the two-dimensional pixel coordinates of the same-name points.

[0104] In a feasible implementation, the first conversion module 92 is configured to:

[0105] The three-dimensional coordinates of the same-name points contained in the same-name point data are converted into two-dimensional longitude and latitude coordinates; and the longitude and latitude coordinates are converted into two-dimensional pixel coordinates.

[0106] In a feasible implementation manner, the first determining module 93 is configured to:

[0107] determining a component of the position offset in at least one preset direction;

[0108] In response to at least one component exceeding a preset error range, determining the color of the same-name point based on a first association relationship between the position offset and the color;

[0109] In response to the components in the at least one preset direction not exceeding a preset error range, determining the color of the same-name point based on a second association relationship between the position offset and the color;

[0110] The first association relationship and the second association relationship correspond to different color ranges.

[0111] In a feasible implementation manner, the point cloud alignment quality visualization device 90 may further include:

[0112] A clustering module, configured to cluster the points of the same name based on their two-dimensional pixel coordinates to obtain a plurality of sub-heap clusters;

[0113] A second determining module is configured to determine a position offset and an offset direction of a centroid of each of the stacking clusters based on the position offset and the offset direction corresponding to each of the points with the same name contained in each of the stacking clusters;

[0114] The second drawing module is used to draw an offset direction arrow of the center of gravity point at the position of the center of gravity point based on the position offset amount and offset direction of the center of gravity point and the number of points with the same name contained in the stacking cluster corresponding to the center of gravity point.

[0115] In a feasible implementation manner, the second determining module is configured to:

[0116] For each cluster, averaging the position offsets of the points with the same name in the cluster to obtain the position offset of the center of gravity of the cluster;

[0117] The offset directions of the points with the same name in the stacking clusters are averaged to obtain the offset direction of the center of gravity of the stacking clusters.

[0118] In a feasible implementation, the second drawing module is configured to:

[0119] Determining the length of the arrow based on the position offset of the center of gravity point;

[0120] Determine the thickness of the arrow based on the number of points with the same name contained in the stacking cluster corresponding to the center of gravity point;

[0121] An arrow indicating the offset direction of the center of gravity is drawn based on the offset direction of the center of gravity, the arrow length, and the arrow thickness.

[0122] In a feasible implementation manner, the point cloud alignment quality visualization device 90 may further include:

[0123] a thinning module, configured to perform multiple thinning processes on the centroids of the plurality of stacked clusters according to different thinning degrees, to generate a plurality of images, wherein the images include the centroids obtained by thinning and arrows indicating the offset directions of the centroids;

[0124] A generating module is configured to generate an image pyramid based on the multiple images.

[0125] In a feasible implementation manner, the point cloud alignment quality visualization device 90 may further include:

[0126] A first display module, configured to display a corresponding image based on the image pyramid and a target display scale;

[0127] A second display module is configured to, in response to detecting a selection operation on a centroid point in the image, display the points of the same name in the stacking cluster corresponding to the centroid point, as well as the colors and offset direction arrows corresponding to the points of the same name;

[0128] The third display module is configured to display the three-dimensional coordinates of the same-name point in response to detecting a selection operation on the same-name point.

[0129] In a feasible implementation manner, the point cloud alignment quality visualization device 90 may further include:

[0130] a second acquisition module, configured to acquire aligned trajectory points, wherein the point cloud data collected at the positions of the trajectory points include points with the same name;

[0131] A second conversion module, configured to convert the three-dimensional coordinates of the trajectory points into corresponding two-dimensional pixel coordinates;

[0132] a third determining module, configured to determine a color of the track point according to an offset of the track point relative to a position before alignment, and to determine an offset direction arrow of the track point according to an offset direction of the track point relative to a position before alignment;

[0133] The third drawing module is configured to draw the trajectory point of the color and the offset direction arrow of the trajectory point in the two-dimensional coordinate system based on the two-dimensional pixel coordinates of the trajectory point.

[0134] The execution method and beneficial effects of the device provided in the embodiment of the present disclosure are similar to those of the above-mentioned method embodiment and will not be repeated here.

[0135] The present disclosure also provides a point cloud alignment quality visualization device, which includes:

[0136] An acquisition module is used to acquire visualization data of the aligned point cloud, wherein the visualization data includes the two-dimensional pixel coordinates, colors, and offset direction arrows of the aligned points of the same name in the two-dimensional coordinate system;

[0137] A display module, configured to display the same-name points of the color and the offset direction arrows of the same-name points on a display interface based on the two-dimensional pixel coordinates of the same-name points;

[0138] The color of the same-name point is related to the position offset of the same-name point, and the offset direction arrow of the same-name point is related to the offset direction of the same-name point.

[0139] The device provided in the embodiment of the present disclosure can be understood as Figure 1 The execution method and beneficial effects of the terminal device 12 or some functional modules in the terminal device 12 in the scenario shown are similar to those of the method embodiment of the above-mentioned terminal device and are not repeated here.

[0140] The present disclosure also provides a computer device, which can be exemplarily understood as Figure 2 The server referred to in the embodiment. The computer device includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the above Figure 2-Figure 8 The method of any embodiment.

[0141] For example, Figure 10 This is a schematic diagram of the structure of a computer device provided by an embodiment of the present disclosure. Figure 10 , which shows a schematic diagram of the structure of a computer device 1000 suitable for implementing the embodiment of the present disclosure. The computer device 1000 in the embodiment of the present disclosure may include but is not limited to devices with computing and processing capabilities such as servers, cloud computing nodes, etc. Figure 10The computer 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.

[0142] like Figure 10 As shown, computer device 1000 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1009 into a random access memory (RAM) 1003. Various programs and data required for the operation of computer device 1000 are also stored in RAM 1003. Processing device 1001, ROM 1002, and RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to bus 1004.

[0143] Typically, the following devices may be connected to the I / O interface 1005: an input device 1006 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 1007 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1009 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the computer device 1000 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 10 The computer device 1000 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0144] 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 includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 1009, or installed from the storage device 1009, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment of the present disclosure are performed.

[0145] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, 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 that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component. In the present disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport 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 thereof.

[0146] The computer-readable medium may be included in the computer device, or may exist independently without being incorporated into the computer device.

[0147] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the computer device, the computer device is caused to: obtain the aligned homonymous point data; convert the three-dimensional coordinates of the homonymous points contained in the homonymous point data into two-dimensional pixel coordinates; determine the color of the homonymous point based on the position offset of the homonymous point relative to the position before alignment, and determine the offset direction arrow of the homonymous point based on the offset direction of the homonymous point relative to the position before alignment; and draw the homonymous point of the color and the offset direction arrow of the homonymous point in the two-dimensional coordinate system based on the two-dimensional pixel coordinates of the homonymous point.

[0148] 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 stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on the 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).

[0149] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two 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 box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0150] The units involved in the embodiments described in this disclosure may be implemented in software or hardware, wherein the name of a unit does not necessarily limit the unit itself.

[0151] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and 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 chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0152] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can 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 can 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.

[0153] An embodiment of the present disclosure further provides a terminal device, which includes a memory and a processor, wherein a computer program is stored in the memory. When the computer program is executed by the processor, the processor can execute the method executed by the terminal device in the above method embodiment.

[0154] An embodiment of the present disclosure further provides a point cloud alignment quality visualization system, which includes the computer device and terminal device provided in the embodiment of the present disclosure, and the terminal device obtains visualization data from the computer device and displays it.

[0155] The embodiment of the present disclosure also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a computer device, it can implement the method of any of the above method embodiments. Its execution method and beneficial effects are similar and will not be repeated here.

[0156] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0157] The foregoing description is intended only to provide specific embodiments of the present disclosure, intended to enable those skilled in the art to understand and implement the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the embodiments described herein, but rather to be construed in the broadest manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for visualizing the quality of point cloud alignment, wherein: The method comprises: Get the aligned homonymous point data; Converting the three-dimensional coordinates of the same-name points contained in the same-name point data into two-dimensional pixel coordinates; determining the color of the homonymous points according to the positional offset of the homonymous points relative to the position before alignment, and determining the offset direction arrow of the homonymous points according to the offset direction of the homonymous points relative to the position before alignment; Based on the two-dimensional pixel coordinates of the same-name points, the same-name points, the colors of the same-name points, and the offset direction arrows of the same-name points are drawn in a two-dimensional coordinate system.

2. The method according to claim 1, wherein The determining the color of the homonymous points according to the position offset of the homonymous points relative to the position before alignment includes: determining a component of the position offset in at least one preset direction; In response to at least one component exceeding a preset error range, determining the color of the same-name point based on a first association relationship between the position offset and the color; In response to the components in the at least one preset direction not exceeding a preset error range, determining the color of the same-name point based on a second association relationship between the position offset and the color; The first association relationship and the second association relationship correspond to different color ranges.

3. The method according to claim 1 or 2, wherein: After drawing the color homonymous points and the offset direction arrows of the homonymous points in a two-dimensional coordinate system based on the two-dimensional pixel coordinates of the homonymous points, the method further includes: Clustering the points of the same name based on their two-dimensional pixel coordinates to obtain a plurality of sub-heap clusters; Determining the position offset and offset direction of the center point of each of the stacking clusters based on the position offset and offset direction of each of the points with the same name contained in each of the stacking clusters; Based on the position offset and offset direction of the center of gravity point and the number of points with the same name contained in the stacking cluster corresponding to the center of gravity point, an offset direction arrow of the center of gravity point is drawn at the position of the center of gravity point.

4. The method according to claim 3, wherein: Determining the position offset and offset direction of the center of gravity of each of the stacking clusters based on the position offset and offset direction of each of the points with the same name contained in each of the stacking clusters includes: For each stacking cluster, averaging the position offsets of the points with the same name contained in the stacking cluster to obtain the position offset of the center of gravity of the stacking cluster; The offset directions of the points with the same name contained in the stacking clusters are averaged to obtain the offset direction of the center point of the stacking clusters.

5. The method according to claim 3, wherein Drawing an arrow in the offset direction of the center of gravity point at the position of the center of gravity point based on the position offset amount and offset direction of the center of gravity point and the number of points with the same name contained in the stacking cluster corresponding to the center of gravity point includes: Determining the length of the arrow based on the position offset of the center of gravity point; Determine the thickness of the arrow based on the number of points with the same name contained in the stacking cluster corresponding to the center of gravity point; An arrow indicating the offset direction of the center of gravity is drawn based on the offset direction of the center of gravity, the arrow length, and the arrow thickness.

6. The method according to claim 3, wherein: After drawing an offset direction arrow of the center of gravity at the position of the center of gravity, the method further includes: Performing multiple thinning processes on the centroids of the plurality of stacked clusters according to different thinning degrees to generate a plurality of images, wherein the images include the centroids obtained by thinning and arrows indicating the offset direction of the centroids, wherein the thinning degree corresponds to the scale of the display range of the visualization interface, i.e., a larger scale indicates a higher thinning degree, and a smaller scale indicates a lower thinning degree; A picture pyramid is generated based on the multiple pictures, wherein a higher part of the picture pyramid corresponds to a larger scale.

7. The method according to claim 6, wherein: After generating the picture pyramid based on the multiple pictures, the method further includes: Displaying a corresponding image based on the image pyramid and the target display scale; In response to detecting a selection operation on a centroid point in the image, displaying the same-named points in the stacking cluster corresponding to the centroid point and the colors and offset direction arrows corresponding to the same-named points; In response to detecting a selection operation on the same-name point, the three-dimensional coordinates of the same-name point are displayed.

8. The method according to claim 1, wherein The method further comprises: Acquire the aligned trajectory points, wherein the point cloud data collected at the positions of the trajectory points include points with the same name; Converting the three-dimensional coordinates of the trajectory points into corresponding two-dimensional pixel coordinates; determining a color of the track point according to an offset amount of the track point relative to a position before alignment, and determining an offset direction arrow of the track point according to an offset direction of the track point relative to a position before alignment; Based on the two-dimensional pixel coordinates of the trajectory point, the trajectory point of the color and the offset direction arrow of the trajectory point are drawn in the two-dimensional coordinate system.

9. A method for visualizing the quality of point cloud alignment, wherein: The method comprises: Obtaining visualization data of the aligned point cloud, wherein the visualization data includes two-dimensional pixel coordinates of the aligned homonymous points in a two-dimensional coordinate system, colors of the homonymous points, and data of offset direction arrows of the homonymous points; Based on the two-dimensional pixel coordinates of the same-name points, displaying the same-name points in the color and the offset direction arrows of the same-name points on a display interface; The color of the same-name point is related to the position offset of the same-name point, and the offset direction arrow of the same-name point is related to the offset direction of the same-name point.

10. A computer device, wherein: include: A memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor performs the method according to any one of claims 1 to 8.

11. A terminal device, wherein: include: A memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor performs the method according to claim 9.

12. A point cloud alignment quality visualization system, wherein: The system comprises the computer device according to claim 10 and the terminal device according to claim 11, wherein the terminal device acquires and displays visualization data from the computer device.

13. A computer-readable storage medium, wherein: The storage medium stores a computer program, and when the computer program is executed by a computer device, the computer device executes the method according to any one of claims 1 to 9.

Images