Method of estimating spatial disparity between three-dimensional objects

Abstract

The present invention relates to a method of estimating a spatial disparity between three-dimensional objects and, more specifically, to a method of estimating a spatial disparity between three-dimensional objects, wherein design data for three-dimensional objects configuring a structure disposed in a three-dimensional space is compared with scan data for actually built or constructed three-dimensional objects so as to identify whether there is a disparity between a design and a construction. The method of estimating a spatial disparity between three-dimensional objects according to the present invention enables accurate and efficient identification of a spatial disparity for an individual object by effectively comparing design data of a three-dimensional structure with scan data of an actual construction site.

Description

Method for calculating spatial differences between 3D objects

[0001] The present invention relates to a method for calculating spatial differences between three-dimensional objects, and more specifically, to a method for calculating spatial differences between three-dimensional objects by comparing design data for three-dimensional objects constituting a structure placed in a three-dimensional space with scan data for a three-dimensional object that has actually been built or constructed to determine whether there is a difference between the design and the construction.

[0002] There is demand in various technology fields for identifying changes in shape or color over time in a specific space.

[0003] For example, in the field of architecture, various such tasks are required to monitor the progress of construction work. It is necessary to frequently check whether a construction project is proceeding according to the design and to what extent actual construction has been completed relative to the design.

[0004] Monitoring the progress of construction is a key management measure for architectural projects. It is an essential procedure for billing and settling payments to subcontractors and verifying construction results, and it is a frequently occurring task. Traditionally, this work was handled by human operators visiting the construction site to visually compare the actual site with design drawings, as well as by comparing actual measurements or surveys. Performing these tasks manually requires significant time, effort, and cost. Therefore, if the task of assessing construction progress by comparing design drawings with the actual state of construction can be automated, it would save a considerable amount of time, effort, and costs.

[0005] Recently, as the design, construction, and management of buildings are all centered around 3D BIM (Building Information Model), productivity and efficiency are being dramatically improved. As a result, the adoption rate of 3D BIM from the design stage for new buildings is gradually increasing. Furthermore, BIM is utilized as a fundamental building representation database in systems designed to enhance urban operational efficiency based on digital models of the entire city, such as smart cities.

[0006] As such, there is a need for a method to effectively identify differences from the design shape by scanning the shape of a 3D structure that has been actually constructed or built, based on 3D design data obtained through BIM. In other words, there is a need for a method to obtain scan data by photographing the actual structure and comparing it with design data (BIM) to effectively determine whether the shape, position, and orientation of the individual constituent objects that make up the structure differ from the design.

[0007] The present invention was devised to satisfy the aforementioned needs and aims to provide a method for calculating spatial differences between three-dimensional objects that can accurately and quickly identify differences between individual constituent objects by comparing design data by BIM with scan data of the actual construction site constructed accordingly.

[0008] A method for calculating spatial differences between three-dimensional objects by comparing design data of a three-dimensional structure with scan data of the structure to identify spatial differences between the design data and the scan data, comprising: (a) a step in which a design data receiving module receives and stores the design data classified into constituent objects constituting the structure; (b) a step in which a scan data receiving module receives the scan data that scanned the structure and stores it in the form of point cloud data; (c) a step in which an alignment module aligns the scan data overall so as to be close to the position and direction of the design data; (d) a step in which a registration module classifies each point of the scan data in the form of point cloud data to correspond to each constituent object of the design data based on spatial proximity; and (e) a step in which a comparison module performs an ICP algorithm on at least some of the constituent objects of the design data and the points of the scan data classified as corresponding to those constituent objects to generate the difference in position and direction between the corresponding constituent objects and the points of the scan data as error information.

[0009] The method for calculating spatial differences between three-dimensional objects according to the present invention has the effect of accurately and efficiently identifying spatial differences between individual objects by effectively comparing design data of a three-dimensional structure with scan data of an actual construction site.

[0010] FIG. 1 is a block diagram of an apparatus for implementing an example of a method for calculating spatial differences between three-dimensional objects according to the present invention.

[0011] FIG. 2 is a flowchart illustrating an example of a method for calculating spatial differences between three-dimensional objects according to the present invention.

[0012] FIGS. 3 and 4 are drawings for explaining the process of implementing a method for calculating spatial differences between three-dimensional objects according to the present invention.

[0013] Hereinafter, a method for calculating spatial differences between three-dimensional objects according to an embodiment of the present invention will be described with reference to the attached drawings.

[0014] FIG. 1 is a block diagram of an apparatus for implementing an example of a method for calculating spatial differences between three-dimensional objects according to the present invention, and FIG. 2 is a flowchart for implementing an example of a method for calculating spatial differences between three-dimensional objects according to the present invention.

[0015] Referring to FIG. 1, an apparatus for implementing a method for calculating spatial differences between three-dimensional objects according to the present invention comprises a design data receiving module (100), a scan data receiving module (200), an alignment module (300), a registration module (400), a comparison module (500), and a display module (600).

[0016] The design data receiving module (100) receives and stores design data classified into constituent objects that constitute a structure. That is, the design data corresponds to BIM data of a structure corresponding to a building or architectural structure. The design data receiving module (100) receives and stores design data that includes shape and spatial information of individual constituent objects that constitute a structure. The individual constituent objects included in the design data include three-dimensional objects such as walls, floors, ceilings, and columns of a building. The design data includes information such as the shape, location, and orientation of such individual constituent objects.

[0017] The scan data receiving module (200) receives scan data of a structure that is actually manufactured or is in the process of being manufactured based on design data and stores it in the form of point cloud data. The scan data may be data scanned using a laser or a set of two-dimensional photographic images taken using a 360 camera, etc. The scan data receiving module (200) may receive the camera's unique parameters of the camera that took the two-dimensional photographic images along with the two-dimensional photographic images, place the two-dimensional photographic images in a three-dimensional space, and convert the space captured by recognizing commonalities between the photos into the form of point cloud data and store it, or it may receive and store only the point cloud data generated by performing such processing on a separate device as scan data.

[0018] As described above, the alignment module (300) aligns the design data and scan data, which are received and stored by the design data receiving module (100) and the scan data receiving module (200) respectively, so that they align with each other. In this embodiment, the design data and scan data are aligned with each other using an Iterative Closest Point (ICP) algorithm. Even if there are some differences between the design data and the scan data, if the design data and scan data relate to a common structure, there are many commonalities. Therefore, the scan data is aligned with the design data by applying the ICP algorithm as a method to recognize such commonalities. By aligning the scan data with the design data in this way, the shape of the scan data is adjusted overall in position and direction so that it approaches the position and direction of the design data in virtual space. Fig. 3 illustrates an example of the state before the design data and scan data are aligned with each other. In Fig. 3, the three-dimensional space formed by the design data and scan data is superimposed and displayed on a display device. It can be seen that the design data and scan data are displayed with an overall offset. In this state, when the design data and scan data are aligned with each other by the alignment module (300), the state is as shown in FIG. 4. In FIG. 4, it can be seen that the design data and scan data are aligned with each other and superimposed.

[0019] As described above, the registration module (400) classifies and registers points of scan data aligned with the design data to correspond to each constituent object. As described above, the design data includes three-dimensional shape and location information of individual constituent objects constituting the target structure. When the scan data is aligned with the design data, the point groups included in the scan data are recognized as corresponding to individual constituent objects that overlap or are close in space, and are classified as belonging to each constituent object. At this time, the registration module (400) classifies and registers the point groups of the scan data to correspond to individual constituent objects based on spatial proximity. That is, the point groups of data that scanned a wall are classified and registered as corresponding to the constituent object corresponding to that wall. Since the shape of the actual manufactured or constructed structure may differ from the design data, if a constituent object exists within a predetermined standard distance (e.g., 50 cm), the registration module (400) can register each point as belonging to the closest constituent object.

[0020] If the scan data received by the scan data receiving module (200) includes normal vectors for each point, the registration module (400) may also consider the direction of such points and correspond them to the constituent objects. As described above, the scan data stored by the scan data receiving module (200) may include a normal vector that is perpendicular to the surface of the object where each point is located. In this case, the registration module (400) may perform a registration operation for the constituent objects of the point group by considering the surface direction of the corresponding constituent object and the direction of the normal vectors of the points together. For example, if the reference angle range is set to 30 degrees, the registration module (400) classifies the points as corresponding to the constituent object only when the points are close to a certain constituent object and the difference between the direction of the surface of the constituent object at the close point and the direction of the normal vectors of the points is within 30 degrees.

[0021] The comparison module (500) performs an ICP algorithm on the design data's constituent objects and the corresponding set of points (hereinafter referred to as "constituent point group") to generate error information regarding the difference in position and direction between the corresponding constituent object and the constituent point group die. As described above, when the design data and scan data are aligned by the alignment module (300), the difference in position and direction can be calculated by comparing the corresponding constituent object and the constituent point group using the ICP algorithm. The comparison module (500) generates and stores such a difference in position and direction as error information. In some cases, the comparison module (500) may additionally identify and store not only the difference in position and direction but also the difference in shape between the constituent object and the constituent point group as error information. For example, if a certain column at a construction site is only partially constructed, there may be a difference between the constituent point group and the constituent object for that column; therefore, the comparison module (500) may identify such a difference as well to identify information regarding the constituent object for which construction has not been completed.

[0022] Meanwhile, the comparison module (500) can perform the ICP algorithm with the constituent point group in various ways depending on the form of the data regarding the constituent object of the scan data. The comparison module (500) may apply a method of directly performing the ICP algorithm on the constituent object in the form of a mesh and the corresponding constituent point group. In some cases, the comparison module (500) may perform the ICP algorithm by sampling an appropriate number of points from the surface of the constituent object and comparing the extracted points with the constituent point group. At this time, the comparison module (500) may perform the ICP algorithm by extracting points from the surface of the constituent object at a density similar to that of the constituent point group, taking into consideration the density of points (number of points existing in a unit space) of the constituent point group corresponding to the constituent object.

[0023] The display module (600) displays error information calculated by the comparison module (500) on the display device. The display device may display error information on the display device in various ways. For example, only the configuration object with an error may be displayed on the display device. Alternatively, the configuration object with error information and the configuration object without an error may be displayed on the display device in different colors. In some cases, the three-dimensional shape of the configuration object or the configuration point group may be displayed in a virtual space displayed on the display device so as to be distinguished by a color that is more emphasized depending on the degree of error between the configuration object and the configuration point group.

[0024] Hereinafter, the process of implementing the method for calculating spatial differences between three-dimensional objects according to the present invention using a device configured as described above will be explained with reference to FIG. 2.

[0025] First, a design data receiving module (100) receives and stores design data for a target structure (step (a); S100). As described above, the design data is divided into units of constituent objects that make up the target structure and includes position, direction, and shape information for a three-dimensional shape.

[0026] Additionally, the scan data receiving module (200) receives scan data that scans a target structure and stores it in the form of point cloud data (step (b); S200). The scan data may be in the form of point cloud data from the beginning, or it may be received in the form of 2D photographic images and camera intrinsic parameters and converted into the form of point cloud data by additional processing. Additionally, as described above, the point cloud data may additionally include normal vectors of each point.

[0027] When design data and scan data are received in this manner, the alignment module (300) aligns the scan data and design data to each other and joins them (step (c); S300). Even if there is some error between the design data and the scan data, since they are three-dimensional shape information for the same target structure (target space) overall, the design data and the scan data are aligned to roughly match each other. As described above, the alignment module (300) can align the design data and the scan data to each other using an ICP algorithm. FIGS. 3 and 4 show the design data and the scan data before and after alignment, respectively, displayed on a display device.

[0028] With the design data and scan data aligned in this manner, the registration module (400) classifies the point clouds of the scan data into constituent point cloud units corresponding to individual constituent objects of the design data (step (d); S400). At this time, the registration module (400) classifies the point cloud data to correspond to the closest constituent object based on the distance between the individual points of the point cloud data and the constituent objects. At this time, the registration module (400) may classify the point cloud data by applying a criterion of whether it is within the standard distance range as described above, or may classify the point cloud data by additionally considering a standard angle range. In places such as construction sites where work is in progress, there may be tools, materials, waste, etc., that cannot correspond to the constituent objects of the design data. Such items may also be included in the scan data by methods such as photography, and point cloud data for such items may be excluded from the work of the registration module (400) because there are no corresponding constituent objects. This step (d) can be performed by the registration module (400) storing the serial number of the corresponding points for each corresponding configuration object, or conversely, storing the serial number of the corresponding configuration object for each point of the point cloud data.

[0029] When step (d) as described above is completed, the comparison module (500) performs an ICP algorithm on the corresponding configuration object and configuration point cloud to generate the difference in position and direction between the configuration object and the configuration point cloud as error information (step (e); S500). This step (e) may be performed for all configuration objects or only for some of the configuration objects in the design data. The ICP algorithm for the configuration object and configuration point cloud may be performed on points sampled from the configuration object and on the configuration point cloud. As described above, the ICP algorithm may be performed by sampling points from the configuration objects at a similar density, taking into account the density of the configuration point cloud.

[0030] The display module (600) displays the result of step (e) on a display device (step (f); S600). Various methods may be used for the display module (600) to display the difference between the configuration object and the configuration point cloud.

[0031] By the method described above, it is easy to determine whether the actual constructed structure was built accurately in accordance with the design data. The position and orientation of structural elements such as columns, walls, and windows can be quickly and accurately identified, and the extent of deviation from the design can be easily determined. Furthermore, it is possible to easily identify cases where only a portion of a constituent object has been constructed.

[0032] Although preferred examples of the present invention have been described above, the scope of the present invention is not limited to the embodiments described above.

[0033] For example, the method for calculating spatial differences between three-dimensional objects in the embodiment described above was explained as having a step in which a display module (600) displays error information on a display device; however, depending on the case, it is also possible to implement a method for calculating spatial differences between three-dimensional objects that does not include such a step (f). In this case, the method for calculating spatial differences between three-dimensional objects may be completed simply by calculating the error information generated in step (e) as a result value. If the error information generated in this way is transmitted to a separate device, it can be used in different ways depending on various purposes.

[0034] In addition, although the process of aligning design data and scan data in step (c) was described above as being performed using the ICP algorithm, it is also possible to perform step (c) using a different method or algorithm.

Claims

1. A method for calculating spatial differences between three-dimensional objects by comparing design data of a three-dimensional structure with scan data of said structure to identify the spatial difference between said design data and said scan data, wherein (a) A step in which a design data receiving module receives and stores the design data classified into constituent objects constituting the structure; (b) A step in which a scan data receiving module receives the scan data that scans the structure and stores it in the form of point cloud data; (c) A step in which the alignment module aligns the scan data overall so as to be close to the position and orientation of the design data; (d) a step in which a registration module classifies each point of the scan data in the form of the point cloud data based on spatial proximity to correspond to each constituent object of the design data; and (e) a step in which a comparison module performs an ICP algorithm on at least some of the constituent objects of the design data and on points of the scan data classified as corresponding to those constituent objects to generate the difference in position and direction between the corresponding constituent objects and the points of the scan data as error information; a method for calculating spatial differences between three-dimensional objects.

2. In Paragraph 1, The above step (c) is a method for calculating the spatial difference between three-dimensional objects aligned with each other by performing an ICP algorithm between the design data and the scan data.

3. In Paragraph 1, The above step (d) is, A method for calculating spatial differences between three-dimensional objects, wherein the distance between each point of the scan data and the object of the design data that is close to it is within a predetermined standard distance range and is classified as a point corresponding to the object.

4. In Paragraph 1, The scan data received in step (b) above further includes information on normal vectors for at least some of the points of the point cloud data, and The above step (d) is, A method for calculating the spatial difference between three-dimensional objects, wherein the direction of the constituent object of the design data adjacent to each point of the scan data and the direction of the normal vector of the points of the point cloud data are within a predetermined reference angle range.

5. In Paragraph 1, (f) a step in which a display module displays error information calculated by the comparison module in step (e) on a display device; further comprising a method for calculating spatial differences between three-dimensional objects.

6. In Paragraph 1, The above step (e) is, A method for calculating spatial differences between three-dimensional objects, wherein the comparison module calculates error information by performing an ICP algorithm on points sampled from the surface of the constituent object of the design data and points of the scan data classified as corresponding to the constituent object.

7. In Paragraph 6, The above step (e) is, A method for calculating spatial differences between three-dimensional objects, wherein the comparison module considers the density of points in the scan data and samples points corresponding to that density from the surface of the constituent object to perform the ICP algorithm.

8. In Paragraph 1, The above step (e) is, A method for calculating spatial differences between three-dimensional objects, wherein the comparison module performs an ICP algorithm on the points of the constituent object and the corresponding scan data to calculate the error information as to whether only a part of the corresponding constituent object exists.

9. In Paragraph 1, The above step (b) is, A method for calculating spatial differences between three-dimensional objects, wherein the above-described scan data receiving module receives a set of multiple two-dimensional photographic images and camera intrinsic parameters of the camera that captured the two-dimensional photographic images as the scan data, and extracts point cloud data from them.

Images