KR20220069541A - Map making Platform apparatus and map making method using the platform - Google Patents

Abstract

A map making platform apparatus and a map making method using the same are disclosed. The map making platform apparatus calculates a drone shooting cost for a certain area based on a certain area, provides an image of the certain area taken by a drone, determines an external facial expression element including the shooting position and attitude information of the image based on a tie point included in a plurality of images obtained by photographing the certain area doubly, performs relative facial expressions on at least two or more images based on the external facial expression elements to remove disparity, identifies spatial coordinates, generates 3D object data and outputs them.

Description

Map making platform apparatus and map making method using the platform

An embodiment of the present invention relates to a platform for map production, and more particularly, to a platform device for producing a three-dimensional map using a two-dimensional image captured using a drone, and a map production method using the same .

The importance of 3D map information such as smart city, navigation, and portal map service is emerging. Existing three-dimensional map production consists of a method of obtaining three-dimensional coordinates of the terrain by photographing an image of the terrain using an aircraft, and obtaining the projection position of each image and the photographing posture information of the image. Aircraft for 3D map production are equipped with expensive equipment that can acquire precise projected position and attitude information, which has the advantage of obtaining accurate 3D coordinates for the terrain, but it is expensive when shooting once. In addition to the disadvantages, it is practically impossible for a general individual or a general company to produce a 3D map using a dedicated aircraft for 3D map production. Another way to get aerial photos at low cost is to use drones. However, since aerial photos obtained through drones are simple two-dimensional images, a separate method is required to generate a three-dimensional image based on them.

The technical problem to be achieved by the embodiment of the present invention is to provide a platform apparatus capable of producing a three-dimensional map using a two-dimensional image captured using a drone, and a map production method using the same.

In order to achieve the above technical problem, an example of a mapping platform apparatus according to an embodiment of the present invention is to calculate the drone shooting cost for a certain area based on the area, and provide an image photographed by a drone in the predetermined area the drone photography service department; a bundle adjustment unit for determining an external expression element including a photographing position and posture information of an image based on a tie point included in a plurality of images overlapping a predetermined area; and removing parallax by performing relative expressions on at least two or more images based on external expression elements, identifying spatial coordinates of at least one or more points of an object from at least two or more images from which parallax has been removed, and based on the spatial coordinates and a cartography unit that generates and outputs three-dimensional object data in the form of points, lines, or surfaces.

An example of a map production method using a map production platform according to an embodiment of the present invention for achieving the above technical task is to calculate the drone shooting cost for a certain area based on the area, and photograph the predetermined area with a drone providing an image; determining an external expression element including a photographing position and posture information of an image based on a tie point included in a plurality of images overlapping a predetermined area; and removing parallax by performing relative expressions on at least two or more images based on external expression elements, identifying spatial coordinates of at least one or more points of an object from at least two or more images from which parallax has been removed, and based on the spatial coordinates and generating and outputting three-dimensional object data in the form of points, lines, or surfaces.

According to an embodiment of the present invention, it is possible to provide not only a drone-captured image for a certain area, but also to determine an exact 3D shooting position and an exterior orientation parameter such as posture information from a 2D image, so that drone shooting is possible. Images can be precisely aligned. In addition, it is possible to generate a 3D object for 3D map production by obtaining 3D coordinates from a 2D image through a general computer without a stereoscopic method that requires equipment such as an expensive stereo monitor.

1 is a diagram showing an overall system overview for a mapping platform according to an embodiment of the present invention;
2 is a diagram showing the configuration of an example of a mapping platform apparatus according to an embodiment of the present invention;
3 is a view showing an example of a screen interface for bundle adjustment according to an embodiment of the present invention;
4 is a view showing an example of a screen interface for 3D map production according to an embodiment of the present invention;
5 is a view showing an example of the detailed configuration of the bundle adjustment unit according to an embodiment of the present invention;
6 to 8 are views illustrating a process of aligning images through a bundle adjustment process using tine points;
9 is a view showing an example of a detailed configuration of a map making unit according to an embodiment of the present invention;
10 is a view showing two images after performing an initial relative expression according to an embodiment of the present invention;
11 is a view showing an example of a change in image coordinates with respect to a change in height value of spatial coordinates according to an embodiment of the present invention;
12 is a diagram illustrating an example of generating a 3D object from a 2D image according to an embodiment of the present invention;
13 is a flowchart illustrating an example of a mapping method using a mapping platform according to an embodiment of the present invention.

Hereinafter, a map making platform apparatus and a map making method using the same according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram illustrating an overall system overview for a mapping platform according to an embodiment of the present invention.

Referring to FIG. 1 , the mapping platform apparatus 100 is connected to at least one user terminal 120 through a wired or wireless communication network. The user terminal 120 is a terminal of a person using the mapping platform of the present embodiment, and may be various types of terminals capable of communication, such as a general computer, a smart phone, and a tablet PC.

The drone 110 provides a camera capable of capturing an image, a device capable of determining a three-dimensional spatial location (eg, GNSS (Global Navigation Satellite System) equipment, etc.), and photographing posture information (such as a photographing direction or inclination). It may include various sensors that can be grasped (eg, a geomagnetic sensor, a gyro sensor, an acceleration sensor, etc.).

The mapping platform apparatus 100 may receive an image captured by the drone 110 or receive an image from the user terminal 120 . Although this embodiment shows an example in which the mapping platform apparatus 100 and the drone 110 directly communicate for better understanding, the image captured by the drone 110 is stored on a separate storage medium (eg, After being transferred to a USB (Universal Servial Bus), etc.), the drone shot image can be delivered to the mapping platform apparatus 100 using the storage medium.

The mapping platform apparatus 100 provides various functions for producing a three-dimensional map. For example, the mapping platform device 100 determines external expression factors such as a function to estimate and present a shooting cost using a drone, a shooting position and posture information of a drone shot image or an image received from the user terminal 120 . It may include a bundle adjustment function that is provided by doing this, and a function of creating a 3D map using a 2D image. Each function will be described below in FIG. 2 .

2 is a diagram showing the configuration of an example of a mapping platform apparatus according to an embodiment of the present invention.

Referring to FIG. 2 , the mapping platform apparatus 100 includes a drone photographing service unit 200 , a bundle adjustment unit 210 , and a map production unit 220 . The mapping platform apparatus 100 may be implemented in various forms, such as a computer, a server, and a cloud system. For example, each configuration of the present embodiment may be implemented by software, loaded in a memory, and then performed by a processor.

The drone photographing service unit 200 calculates the drone photographing cost for a certain area based on the photographing area, and provides an image captured by the drone in the predetermined area. The drone photographing service unit 200 may provide a map screen for receiving a selection of a photographing area from the user. The user can select a shooting area on the map screen. For example, the drone photographing service unit 200 may provide a polygon object creation tool, and the user may display a desired photographing area on the map in the form of a polygon.

The drone shooting service unit 200 may determine the coordinates (eg, latitude and longitude, etc.) of the shooting area marked by the user on the map, and then obtain the actual area of the shooting area based on this, and calculate the shooting cost based on the area. have. In drone shooting, an administrator can directly control the drone to shoot video while checking the coordinates of the shooting area. The drone photographing service unit 200 may provide the original drone photographed image and an external expression element for each image to the user as a result of the drone photographing service.

The drone superimposes the shooting area. For example, when a drone continuously takes pictures while moving in a certain direction, portions of the continuously shot images may overlap each other. However, in the case of drones, since GNSS or IMU (Inertial Measurement Unit) is used, the accuracy of measurement values such as shooting location and shooting posture may be reduced. When a 3D map is produced using posture information, etc. as it is, the accuracy may be lowered. This may be adjusted through the bundle adjustment unit 210 .

The bundle adjustment unit 210 determines and provides external expression elements such as a photographing position and posture information of a two-dimensional image. For example, the bundle adjustment unit 210 may determine an external expression element (ie, photographing location and posture information of each image) for a plurality of images captured by the drone or a plurality of images received from the user terminal 120 . . The bundle adjustment unit 210 may obtain a bundle adjustment value by designating a Ground Control Point (GCP), which is an absolute coordinate value of each image, in each image, and then provide the result to the user terminal. An example of a user interface screen for adjusting bundles of each image is shown in FIG. 3 .

The bundle adjustment unit 210 may be downloaded and driven by a user terminal that has purchased a license. When the license contract period ends, the bundle adjustment unit 210 may no longer operate in the user terminal 120 . As another example, the function of the bundle adjustment unit 210 may be provided by the mapping platform apparatus 100 . That is, the user can use the bundle adjustment function provided by the mapping platform apparatus 100 after accessing the mapping platform apparatus 100 through a login process.

Users can use either one of the drone photography service and the bundle adjustment service, or both services at the same time, as needed. For example, the user may request to take an image of a certain area and adjust the bundle of the image through the drone.

The bundle adjustment unit 210 may use various conventional bundle adjustment methods. However, in order to determine a more accurate external expression element, the bundle adjustment unit 210 acquires an external expression element such as an accurate photographing position and posture information of an image based on a common feature point included in a plurality of images overlapped with a certain area can do. A specific method of bundle adjustment using common feature points will be described again with reference to FIGS. 5 to 8 .

The cartography unit 220 removes the parallax by performing relative expressions on at least two or more images based on the external expression element of the image, and spatial coordinates of at least one or more points of the object from the at least two or more images from which the parallax has been removed (that is, , the absolute coordinate value of 3D space), and using the identified spatial coordinates, generates and outputs 3D object data in the form of points, lines, or surfaces. For example, when the cartography unit 220 displays a 2D image on the screen and receives a selection from the user of a point of an object for which 3D coordinates are to be obtained, the 3D coordinates of each point may be obtained after the parallax is removed. An example of a user interface screen for 3D map production is illustrated in FIG. 4 .

The map making unit 220 may be downloaded and driven by a user terminal that has purchased a license. When the license contract period ends, the mapping unit 220 may no longer operate. As another example, the functions of the mapping unit 220 may be provided by the mapping platform apparatus 100 . That is, after the user accesses the mapping platform apparatus 100 through a login process, the user can use the mapping function as shown in FIG. 4 provided by the mapping platform apparatus 100 .

As an example of a method for removing parallax for 3D map production, there is a stereoscopic vision method. The stereoscopic method is a method of removing the Y disparity between two images by specifying a point from which three-dimensional coordinates are to be obtained from two images and then aligning the specific points of the two images to match three-dimensionally using a stereo stereoscopic monitor or the like. In addition to this, various conventional relative expression methods for removing parallax may be applied to the present embodiment.

In another embodiment, the cartography unit 220 of this embodiment proposes a method of obtaining three-dimensional coordinates by performing a relative expression using a general computer without expensive stereo stereoscopic vision equipment. For example, the cartography unit 220 may display the two images on the screen and change the height value of the spatial coordinates to remove the parallax and obtain the three-dimensional coordinates through the process of matching the two points displayed on the two images. A detailed method for this will be looked at again with reference to FIGS. 9 to 12 .

3 is a diagram illustrating an example of a screen interface for bundle adjustment according to an embodiment of the present invention.

Referring to FIG. 3 , the bundle adjustment screen interface 300 includes an image list display window 310 on the left side of the screen, and a plurality of image viewer windows 320 that display images selected from the image list display window 310 on the right side of the screen. This includes When the user selects an image displayed on the viewer window 320 and selects GCP from the image, the bundle adjustment unit 210 of the mapping platform apparatus 100 provides an external expression including the shooting location and posture information of the image. determine the elements.

For example, when the user selects an image, the bundle adjustment unit 210 additionally selects two different images overlapping the image, and based on a total of three images including the user selected image and the additionally selected two images. As a result, bundle adjustment may be performed according to the method described in FIGS. 5 to 8 . The bundle adjustment unit 210 may select the additional images in the order in which the ratio of the overlapping portion to the image selected by the user is high or in the order in which the number of common feature points (ie, tie points) is large. As another example, the user may directly select three images to be used for bundle adjustment on the interface screen 300 .

4 is a diagram illustrating an example of a screen interface for 3D map production according to an embodiment of the present invention.

Referring to FIG. 4 , the mapping screen interface 400 includes a video risk display window 410 on the left side of the screen, and a plurality of image viewer windows 420 that display images selected from the image list display window 410 on the right side of the screen. ) is included. When the user selects a first image in which an object for which three-dimensional coordinates are to be obtained exists among the images displayed on the viewer window 420, the cartography unit 220 of the mapping platform apparatus 100 is displayed with the first image selected by the user. A second image overlapping a predetermined portion is selected and displayed. For example, the map making unit 220 may automatically determine the second image having the largest overlap between the first image and the image and display it on the screen. In another embodiment, the user may directly select both the first image and the second image through the interface screen 400 .

When the user selects a point at which to obtain three-dimensional coordinates in the first image, the map making unit 220 fixes the first image and displays the point of the image coordinates that change according to the height value of the spatial coordinates on the second image . The map making unit 220 may change the height value of the spatial coordinates to adjust the points displayed on the second image to coincide with the points fixedly displayed on the first image, and when the points on the first image and the second image coincide with each other, the user 3D coordinates of the selected point can be grasped. Examples of displaying the first image and the second image on a screen and matching two points displayed on the two images are shown in FIGS. 10 and 11 . Also, FIG. 12 shows an example in which three-dimensional coordinates of at least one or more points of an object displayed on the first image are identified in this way and the corresponding object is output as a three-dimensional object for producing a three-dimensional map.

The screen interfaces 300 and 400 of FIGS. 3 and 4 are only examples for helping the understanding of the present invention, and the screen interfaces 300 and 400 for bundle adjustment and map production can be used with various modifications depending on the embodiment.

5 is a diagram illustrating an example of a detailed configuration of a bundle adjustment unit according to an embodiment of the present invention. 6 to 8 are diagrams illustrating a process of aligning images through a bundle adjustment process using tine points. Hereinafter, it will be described with reference to FIGS. 6 to 8 together.

First, referring to FIG. 5 , the bundle adjustment unit 210 includes a feature point extraction unit 500 , a feature point calculation unit 510 , and an expression determination unit 520 .

The feature point extraction unit 500 extracts a common feature point from at least three or more images having overlapping portions. For extracting feature points from each image, various conventional methods such as Scale-Invariant Feature Transform (SIFT) and Speeded Up Roubst Features (SURF) may be used. Since extracting feature points of an image itself is a well-known technique, a detailed description thereof will be omitted. It is assumed that the three-dimensional spatial coordinates of image feature points are known in advance.

Among the feature points extracted from a plurality of images, the same feature point is called a tie point. For example, the same feature point extracted from two images is called a double tie point, and the same feature point extracted from three images is called a triple tie point. For convenience of description, the present embodiment is limited to a case in which the feature point extraction unit 500 extracts triple tie points. For example, the feature point extraction unit 500 may extract a plurality of triple tie points 602 , 612 , and 622 from three images 600 , 610 , and 620 as shown in FIG. 6 .

The feature point calculating unit 510 calculates the number of suitable tie points corresponding to the estimated position and the estimated posture among the plurality of triple tie points based on the estimated positions and the estimated postures of the three images, respectively. For example, when the triple tie points are the same as in FIG. 6 , the feature point calculating unit 510 may align the three images 600 , 610 , and 620 based on the triple tie points 602 , 612 and 622 as shown in FIG. 7 . However, all of the triple tie points 602 , 612 , and 622 of the three images 600 , 610 , and 620 do not completely overlap, and some non-overlapping triple tie points may exist. However, at this time, it is not known which triple tie point is the error point.

The feature point calculating unit 510 may first randomly select a triple tie point from among a plurality of triple tie points, and then derive a three-dimensional estimated position and an estimated posture of each image therefrom. For example, given the three-dimensional spatial coordinates of the triple tie point and the image coordinates of the triple tie point displayed on the image, the projection center (ie, estimated position) of the image and the photographing posture information (ie, estimation) according to collinear conditions, etc. behavior) can be identified. A method of determining the projection center and posture information of an image using collinear conditions, three-dimensional spatial coordinates, and image coordinates is a well-known technique in the field of photogrammetry, so a detailed description thereof will be omitted.

The feature point calculating unit 510 calculates the number of fit points corresponding to the estimated position and the estimated posture obtained from each image among the plurality of triple points. For example, if there are six triple tie points, and the estimated position and the estimated posture of each image (600, 610, 620)) are obtained using any one of the triple tie points, the feature point calculating unit 510 performs the remaining Obtain the projection image coordinates in the first image for the triple tie point, compare the projected image coordinates with the image coordinates of the triple tie point existing in the first image, and if the distance is less than a certain amount, the triple tie point is selected as a suitable tie points can be determined.

The expression determining unit 520 obtains the estimated position and the estimated posture of each image based on the randomly selected triple typography, and repeats the process of finding the number of suitable tie points in each estimated position and the estimated posture to find the suitable tie points. The estimated position and the estimated posture when the number of is the largest may be determined as the final position and final posture of each image. An example of aligning three images 600 , 610 , and 620 using the largest number of suitable tie points is shown in FIG. 8 .

9 is a diagram illustrating an example of a detailed configuration of a map making unit according to an embodiment of the present invention.

Referring to FIG. 9 , the map making unit 220 includes a relative expression unit 900 , an image display unit 910 , a position adjustment unit 920 , and a coordinate finding unit 930 .

The relative expression unit 900 performs a relative orientation based on an external expression element including photographing positions and posture information of the first image and the second image in which a predetermined region is overlapped (S210). The relative expression unit 900 performs a relative expression using a relative expression relational expression widely known in the field of photogrammetry. In order to grasp accurate three-dimensional spatial coordinates through the relative expression, a process of matching specific points of the first image and the second image with each other is required. Conventionally, a process of matching specific points of two images is performed using a stereoscopic method, but in this embodiment, a relative expression is performed without such a process.

More specifically, the relative expression unit 900 includes an arbitrary initial image coordinate (eg, each central coordinate of the two images) and an arbitrary spatial coordinate height value (ie, Z-axis coordinate) in the first image and the second image. After setting the value), the initial spatial coordinates satisfying the epipolar geometry are identified using the collinear condition. In other words, since the initial image coordinates of the two images are given and the height value among the spatial coordinates is given, the relative representation unit 900 uses the collinear condition and the epipolar geometric condition to determine the X-axis coordinate value and the Y-axis, which are unknown among the spatial coordinates. Coordinate values can be calculated.

In other words, the relative expression unit 900 inputs the initial image coordinates and the initial spatial coordinates to the relative expression relational expression widely known in the field of photogrammetry, and then converts the two unknowns (X-axis coordinate value and Y-axis coordinate value) to least squares method, etc. can be obtained using Since a method of determining a spatial coordinate value using a relative expression relational expression is already well known, a detailed description thereof will be omitted.

The spatial coordinates obtained by the relative expression unit 900 are values obtained by using arbitrary initial image coordinates and arbitrary spatial coordinate height values, and not values obtained by precisely matching specific points of two images. The image display unit 910 and the position adjustment unit 920 are required as a configuration for accurately adjusting the spatial coordinates obtained by the relative expression unit 900 initially.

The image display unit 910 displays the first image and the second image on the screen, respectively. For example, two images 1000 and 1010 may be displayed on the screen as shown in FIG. 10 . Hereinafter, it will be described with reference to FIG. 10 together.

The position adjusting unit 920 receives a point from which a three-dimensional coordinate is to be obtained from the user and displays the corresponding point (ie, the first point) 1002 on the first image 1000 . The position adjusting unit 920 obtains the image coordinates (ie, the second point) 1012 of the second image 1010 that is changed according to the change of the height value in the initial spatial coordinates obtained by the relative expression unit 900 to obtain the second image. displayed on For example, the image display unit 910 may obtain and display the image coordinates 1012 of the second image 1010 corresponding to the spatial coordinates using the collinear condition. In this case, the second point may be identified by fixing the height value of the spatial coordinates of the first image 1000 and changing the height value of the spatial coordinates of the second image 1010 .

When the height value of the initial spatial coordinates is changed by the position adjusting unit 920 , the relative expression unit 900 performs a relative expression for recognizing the spatial coordinates satisfying the epipolar geometry based on the changed height value. The position adjustment unit 920 determines the spatial coordinates newly obtained according to the change in the height value (that is, the changed height value (Z-axis coordinate value) of the spatial coordinates) and the X-axis and Y-axis coordinates of the spatial coordinates newly obtained through the relative expression relational expression based on this value (Z-axis coordinate value). The image coordinate of the second image corresponding to the value) is obtained through the collinear condition, and an 'X' character 1012 is displayed on the image coordinate of the second image 1010 .

The position adjusting unit 920 controls the height value of the spatial coordinates of the second image 1010 until the second point 1012 of the second image 1010 coincides with the first point 1002 of the first image 1000 . change the For example, as shown in FIG. 11 , the second point 1110 of the second image 1010 may move to coincide with the first point 1002 of the first image 1000 according to a change in the height value of the spatial coordinates. . Whether the first point 1002 and the second point 1012 match can be determined by the user checking whether the 'X' mark respectively displayed on the two images points to the same point in the images. In another embodiment, the position adjusting unit 920 determines whether the first point 1002 and the second point 1012 in the two images 1000 and 1010 are the same location using various conventional image recognition methods or artificial intelligence such as deep learning. It can be identified through the model, and in this case, the height value of the spatial coordinates where the first point 1002 and the second point 1012 coincide with the position adjusting unit 920 automatically changing the height value without user input. have.

When the first point 1002 of the first image 1000 matches the second point 1100 of the second image 1010 , the coordinate determiner 930 controls the second point 1110 of the second image 1010 . ) to determine the spatial coordinates corresponding to the image coordinates. Since the height value when the first point and the second point coincide with each other is known, the coordinate grasping unit 930 uses the collinear condition on the basis of the height value of the image coordinate and the spatial coordinate of the second point 1110 to obtain the second 3D spatial coordinates corresponding to the image coordinates of the point 1110 may be identified.

For example, if the height value of the initial spatial coordinate obtained through the initial relative expression is 5, and the height value is changed by '+2' to match the first point 1002 and the second point 1012, the coordinates are identified The unit 930 may determine '7' by adding or subtracting the adjusted height value to the height value of the initial spatial coordinates as the height value of the spatial coordinates of the point for which the three-dimensional coordinates are to be obtained. The coordinate determiner 930 determines a collinear condition based on a height value when the first point 1002 and the second point 1100 coincide and the image coordinate of the second point 1100 of the second image 1010. The coordinates of the X-axis and Y-axis of the spatial coordinates that are satisfied can be obtained.

In this way, three-dimensional coordinates for various points in the image can be obtained. In this case, the three-dimensional coordinates are relative coordinate values between each point in the image. If an actual height value (ie, GCP) for a specific point in the image exists, the absolute coordinate value of each point 1002 in the image can be obtained based on this.

10 is a view showing two images after performing an initial relative expression according to an embodiment of the present invention.

Referring to FIG. 10 , the mapping platform apparatus 100 sets initial image coordinates (eg, central coordinates of images) of two images, and uses external expression elements and collinear conditions of the two images to generate epipolar geometry. An initial relative expression to obtain a satisfactory spatial coordinate can be performed.

After performing the initial relative expression, the mapping platform apparatus 100 displays two images, respectively, and displays a first point 1002 from which three-dimensional coordinates are to be obtained on the first image 1000 . The mapping platform apparatus 100 displays the second point 10122 on the image coordinates of the second image 1010 corresponding to the spatial coordinates obtained through the initial relative expression.

11 is a diagram illustrating an example of a change in image coordinates with respect to a change in height value of spatial coordinates according to an embodiment of the present invention.

Referring to FIG. 11 , the mapping platform apparatus 100 changes the height value of the initial spatial coordinate obtained through the initial relative expression, and identifies and displays the image coordinate 1100 of the second image corresponding thereto.

More specifically, the mapping platform apparatus 100 fixes the first point 1002 of the first image 1000 . That is, the mapping platform apparatus 100 fixes the height value of the first image to the initial height value obtained through the initial relative expression, and changes the height value of the spatial coordinates only for the second image 1010 . The mapping platform apparatus 100 obtains new spatial coordinates by performing relative expressions based on the changed height value, and displays the second point 1110 of the image coordinates corresponding to the new spatial coordinates on the second image 1010. . The height value until the second point 1100 of the second image 1010 points to the same location as the first point 1002 of 1000 of the first image (eg, the same location of the same object in the image) Changes are repeated.

12 is a diagram illustrating an example of generating a 3D object from a 2D image according to an embodiment of the present invention.

Referring to FIG. 12 , a user selects at least one point of an object for which three-dimensional coordinates are to be obtained from an image. For example, the user may select each point in the image 1200 selected through the screen interface of FIG. 4 and obtain 3D coordinates to generate the 3D object 1210 . If you want to generate 3D object data for the building roof 1210 as shown in FIG. 12 , the user selects each corner point of the building roof, and the 3D coordinates for each corner point in FIGS. 9 to 11 . can be obtained through

When the three-dimensional coordinates for at least one point of the object 1210 are obtained, the cartography platform apparatus 100 uses the three-dimensional coordinate values of each point of the object 1210 to form a point, a line, or a plane 3 Creates and outputs dimension object data.

In this way, each object 1210 present in the 2D image 1200 may be generated as a 3D object. The cartography platform apparatus 100 may generate a 3D map by combining 3D objects.

13 is a flowchart illustrating an example of a mapping method using a mapping platform according to an embodiment of the present invention.

Referring to FIG. 13 , the mapping platform apparatus 100 may obtain and provide a two-dimensional image captured by a drone in a predetermined area according to a user's request (S1300). The map making platform device 100 provides a map screen, and through the map screen, a user may receive a desired shooting area. In addition, the mapping platform apparatus 100 may calculate the cost according to the area selected by the user.

The mapping platform apparatus 100 may perform bundle adjustment on the drone-captured image or the image received from the user terminal (S1310). In another embodiment, in the case of using the photographing position and posture information of the drone photographed image as it is, the bundle adjustment process may be omitted. Various conventional bundle adjustment methods can be applied to this embodiment, and another embodiment of bundle adjustment is shown in FIGS. 5 to 8 .

The mapping platform apparatus 100 obtains three-dimensional spatial coordinates for a point selected by the user in the two-dimensional image (S1320). The mapping platform apparatus 100 displays two images of the first image and the second image as shown in FIG. 10 and then reflects the height change of the spatial coordinates in the second image to match the points of the two images. dimensional coordinates can be obtained. Examples of a specific method for obtaining three-dimensional coordinates are shown in FIGS. 9 to 11 .

The cartography platform apparatus 100 generates and outputs 3D object data expressed in the form of points, lines, or surfaces by using 3D coordinates of at least one or more points of the object (S1330).

The present invention can also be implemented as computer-readable codes on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices in which data readable by a computer system is stored. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage device. In addition, the computer-readable recording medium is distributed in a network-connected computer system so that the computer-readable code can be stored and executed in a distributed manner.

So far, the present invention has been looked at with respect to preferred embodiments thereof. Those of ordinary skill in the art to which the present invention pertains will understand that the present invention can be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments are to be considered in an illustrative rather than a restrictive sense. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

Claims (9)

a drone photographing service unit that calculates a drone photographing cost for a certain area based on the area and provides an image captured by a drone in the predetermined area;
a bundle adjustment unit for determining an external expression element including a photographing position and posture information of an image based on a tie point included in a plurality of images overlapping a predetermined area; and
Removes parallax by performing relative expressions on at least two or more images based on external expression elements, finds spatial coordinates of at least one or more points of an object from at least two or more images from which parallax is removed, and points based on spatial coordinates , a cartography unit for generating and outputting three-dimensional object data in the form of a line or plane; Cartography platform device comprising a. According to claim 1, wherein the drone photography service unit,
Map production platform device, characterized in that it provides a map screen for receiving a selection of a shooting area According to claim 1, wherein the bundle adjustment unit,
a feature point extraction unit for extracting a plurality of triple tie points from three images among a plurality of images;
a feature point calculation unit configured to calculate the number of fit points matching the estimated position and the estimated posture among the plurality of triple tie points based on the estimated positions and the estimated postures of the three images; and
and an expression determining unit that determines the estimated positions and the estimated postures of the three images as final positions and final postures of the three images based on the number of the fit points. According to claim 1, wherein the cartography unit,
An image of performing a relative expression for recognizing spatial coordinates of image coordinates of a predetermined position of the first image and the second image based on an external expression element including the photographing position and posture information of the first image and the second image representative government;
an image display unit for displaying the first image and the second image, respectively;
a position adjusting unit for displaying a first point of an object in the first image and displaying a second point of image coordinates that change according to a change in a height value of spatial coordinates on the second image; and
When the first point displayed on the first image matches the second point displayed on the second image, the spatial coordinates of the first point of the object are identified and output based on the image coordinates of the second point displayed on the second image A map making platform device comprising a; a coordinate grasping unit. In the mapping method performed by the mapping platform device,
estimating a drone photographing cost for a predetermined area based on the area, and providing an image captured by a drone in the predetermined area;
determining an external expression element including a photographing position and posture information of an image based on a tie point included in a plurality of images overlapping a predetermined area; and
Removes parallax by performing relative expressions on at least two or more images based on external expression elements, finds spatial coordinates of at least one or more points of an object from at least two or more images from which parallax is removed, and points based on spatial coordinates , generating and outputting three-dimensional object data in the form of a line or plane; The method of claim 5, wherein the providing of the drone-captured image comprises:
providing a map screen;
receiving a selection of a shooting area on the map screen; and
Calculating the cost according to the area of the photographing area; a method for making a map using a map making platform, comprising: a. The method of claim 5, wherein the step of determining the spatial coordinates,
Performing a relative expression for recognizing spatial coordinates of image coordinates of predetermined positions of the first image and the second image based on an external expression element including the photographing position and posture information of the first image and the second image ;
displaying the first image and the second image, respectively;
displaying a first point of an object in the first image, and displaying a second point of image coordinates that change according to a change in a height value of spatial coordinates on the second image; and
When the first point displayed on the first image matches the second point displayed on the second image, the spatial coordinates of the first point of the object are identified and output based on the image coordinates of the second point displayed on the second image A method of making a map using a map making platform, comprising the steps of: 6. The method of claim 5,
extracting a plurality of triple tie points from three images among a plurality of images;
calculating the number of fit points matching the estimated position and the estimated posture among the plurality of triple tie points based on the estimated positions and the estimated postures of the three images; and
determining the estimated positions and the estimated postures of the three images as the final positions and final postures of the three images based on the number of the fit points; A method of making a map using a map making platform. A computer-readable recording medium in which a program for performing the method according to any one of claims 5 to 8 is recorded.

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