Drone based architectural modeling video producing method

Abstract

The present invention relates to a method for producing architectural modeling images using a drone, comprising the steps of: producing a three-dimensional orthophoto using first drone image data in which an entire bird's-eye view area is captured using a drone; flying the drone based on the three-dimensional orthophoto to obtain second drone image data that captures the surroundings of an architectural object within the entire bird's-eye view area; mapping the obtained second drone image data to the three-dimensional orthophoto to obtain an image of the surroundings of the architectural object resulting from the flight of the drone; performing three-dimensional modeling according to the architectural information of the architectural object to generate an image of the architectural object; and mapping the image of the architectural object to the image of the surroundings of the architectural object to generate an overall bird's-eye view image; thereby effectively providing an overall bird's-eye view of an architectural object.

Description

Technology Field

[0001] The present invention relates to a method for producing architectural modeling images using a drone, which can effectively provide an overall bird's-eye view of a target building by constructing a three-dimensional orthophoto of the surroundings using a drone, photographing the surroundings of a target building, and then modeling the building in three dimensions, and then mapping the surroundings of the target building and the three-dimensional modeling image onto the produced three-dimensional orthophoto. Background Technology

[0002] As is well known, a model house refers to a home built to look exactly like the actual interior before construction begins, intended to be shown to prospective buyers. Since it is created by replicating the planned housing exactly, its production is costly, and because the model house must be dismantled once the housing sales are complete, significant costs are also incurred for its demolition.

[0003] In addition, since the constructed model house is located at a specific site near where the actual house is being built, consumers face the inconvenience of having to travel to the location where the model house was built.

[0004] Meanwhile, as non-face-to-face business is increasing due to the impact of COVID-19 that has continued for several years, making it difficult or undesirable to visit model houses, and consequently, visits to model houses are gradually decreasing, such as by operating them on a reservation system. As a result, there is an increasing demand for the production of 3D videos of model houses to show the model house in video form as an alternative.

[0005] In particular, for buildings undergoing reconstruction or redevelopment, there is an increasing demand from consumers who wish to view an overall bird's-eye view of the area where the building will be constructed.

[0006] In response to these needs, if one intends to produce a 3D image of the entire bird's-eye view, while it is easy to produce a 3D image of the building itself through 3D modeling, there is a problem in that one must meticulously photograph the surrounding houses, parks, trees, and roads located in the area and perform the work of 3D modeling each of them individually.

[0007] In other words, in the case of conventional technology that presents the exterior image of a building and surrounding images from various angles as a 3D image, there is a problem in that in order to produce the 3D image, the exterior of the target building itself must be 3D modeled, and objects such as trees, roads, buildings, and parks located around the building must also be 3D modeled one by one.

[0008] Accordingly, there is a need to develop an architectural modeling video production technique that can effectively provide an overall bird's-eye view of a target building by using a drone to construct a 3D orthophoto of the surroundings, photographing the surroundings of the target building, and 3D modeling the building, and then mapping the surroundings of the target building and the 3D modeling image onto the produced 3D orthophoto. Prior art literature

[0009] Korean Patent Publication No. 10-2023-0091084 (Published June 22, 2023) The problem to be solved

[0010] The present invention aims to provide a method for producing architectural modeling images using a drone, which can effectively provide an overall bird's-eye view of a target building by constructing a three-dimensional orthophoto of the surroundings using a drone, photographing the surroundings of a target building, and then modeling the building in three dimensions, and finally mapping the surroundings of the target building and the three-dimensional modeling image onto the produced three-dimensional orthophoto.

[0011] The purposes of the embodiments of the present invention are not limited to those mentioned above, and other unmentioned purposes will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0012] According to an embodiment of the present invention, a method for producing a building modeling image using a drone may be provided, comprising: a step of producing a three-dimensional orthophoto using first drone image data in which an entire bird's-eye view area is captured using a drone; a step of obtaining second drone image data by flying the drone based on the three-dimensional orthophoto to capture the surroundings of a building object within the entire bird's-eye view area; a step of obtaining an image of the surroundings of a building object based on the flight of the drone by mapping the obtained second drone image data to the three-dimensional orthophoto; a step of generating an image of a building object by performing three-dimensional modeling according to the building information of the building object; and a step of generating an overall bird's-eye view image by mapping the image of the building object to the image of the surroundings of the building object.

[0013] In addition, according to an embodiment of the present invention, the step of acquiring the second drone image data may be provided as a method for producing architectural modeling images using a drone, wherein the drone is controlled to fly according to the coordinate information and height information of the building object to photograph the surroundings of the building object.

[0014] In addition, according to an embodiment of the present invention, the step of acquiring an image of the surroundings of the building object may be mapped using each bird's-eye reference point of the 3D orthophoto and the second drone image data, and a method for producing an architectural modeling image using a drone may be provided, wherein the drone is acquired as a 3D flight image that moves to the location of the building object according to the drone flight path of the second drone image data.

[0015] In addition, according to an embodiment of the present invention, the step of generating the image of the building object may be provided as a method for producing an architectural modeling image using a drone that is modeled according to site information, specification information, floor plan design drawings for each floor, and construction information regarding the building object.

[0016] In addition, according to an embodiment of the present invention, a method for producing architectural modeling images using a drone may be provided, wherein the step of generating the overall bird's-eye view image involves mapping the image of the building object onto the surrounding image of the building object, and synthesizing the image according to the coordinate information where the building object is to be constructed to generate the overall bird's-eye view image.

[0017] In addition, according to an embodiment of the present invention, the method for producing an architectural modeling video using a drone may further include the step of extracting the overall bird's-eye view image and transmitting it to the communication terminal when a model house image of the architectural object is requested from the communication terminal. Effects of the invention

[0018] The present invention can effectively provide an overall bird's-eye view of a target building by using a drone to construct a three-dimensional orthophoto of the surroundings, photographing the surroundings of the target building, and then three-dimensionally modeling the building, and then mapping the surroundings of the target building and the three-dimensional modeling image onto the produced three-dimensional orthophoto. Brief explanation of the drawing

[0019] FIG. 1 is a flowchart illustrating the process of producing architectural modeling videos using a drone according to an embodiment of the present invention, and FIG. 2 is a block diagram of an architectural modeling video production system to which a method according to an embodiment of the present invention is applied, and FIGS. 3 to 13 are drawings for explaining the detailed process of a method for producing architectural modeling images using a drone according to an embodiment of the present invention. Specific details for implementing the invention

[0020] The advantages and features of the embodiments of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined only by the scope of the claims. Throughout the specification, the same reference numerals refer to the same components.

[0021] In describing the embodiments of the present invention, specific descriptions of known functions or configurations will be omitted if it is determined that such detailed descriptions could unnecessarily obscure the essence of the invention. Furthermore, the terms described below are defined in consideration of their functions in the embodiments of the present invention, and these definitions may vary depending on the intentions or practices of the user or operator. Therefore, such definitions should be based on the content throughout this specification.

[0022] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings.

[0023] FIG. 1 is a flowchart showing the process of producing an architectural modeling video using a drone according to an embodiment of the present invention, FIG. 2 is a block diagram of an architectural modeling video production system to which a method according to an embodiment of the present invention is applied, and FIG. 3 to 13 are drawings for explaining the detailed process of a method for producing an architectural modeling video using a drone according to an embodiment of the present invention.

[0024] Referring to FIGS. 1 to 13, a three-dimensional orthophoto can be produced using first drone image data in which the entire bird's-eye view area is captured using a drone (20) (step 110).

[0025] For example, drone image data of a map-making area can be collected using a drone (20), and the drone (20) can be flown according to the coordinates of ground reference points surveyed in the entire bird's-eye view area to collect the data.

[0026] Here, the drone (20) may be equipped with a flight means, a shooting means (e.g., an RGB camera, a multispectral camera, etc.), a wireless communication module, a GPS receiver, a pressure sensor, a gyroscope sensor, etc. in the drone body, and may fly unmanned to a desired area according to wireless control of the image production device (10) through the communication network (40), photograph the area, and wirelessly transmit drone image data to the image production device (10) for map production. Such an image production device (10) may be provided in a control center that performs wireless control of the drone (20), or may be provided including the control center.

[0027] Here, the drone body may be equipped with various components for operation and control of the drone (20), and can fly in an area to be flown unmanned along a pre-set path or a wirelessly controlled path using a flight means including a propulsion motor, a propeller, etc., and can acquire first drone image data for producing a three-dimensional orthophoto using a shooting means capable of shooting in all directions of 360 degrees.

[0028] In addition, the drone (20) can receive coordinate signals transmitted from the control center using a wireless communication module, receive GPS signals from the satellite navigation system (GPS) equipped in the satellite image collection device using a GPS receiver, measure ambient pressure in real time to detect the altitude of the drone body using a pressure sensor, and be equipped to detect the up-and-down inversion of the drone body using a gyroscope sensor.

[0029] Here, the drone (20) can acquire various satellite information related to location information through the satellite navigation system (GPS: global positioning system) and inertial navigation system (INS: inertial navigation system) of the satellite image collection device equipped in the image production device (10).

[0030] A drone (20) having the configuration described above can obtain the coordinates of ground reference points by surveying ground reference points to fly unmanned over the entire bird's-eye view area, determine a flight path according to the coordinates of the ground reference points surveyed in the entire bird's-eye view area, fly the drone (20) by referring to the coordinates of the ground reference points surveyed according to the determined flight path to photograph the area, and then collect the photographed drone video data.

[0031] Next, the satellite image collection device (city omitted) can collect satellite image data in which the map production area is captured, and can collect using the satellite navigation system (GPS) and inertial navigation system (INS) provided in the image production device (10).

[0032] For example, the satellite navigation system (GPS) consists of at least 24 GPS satellites, and the precise position of each GPS satellite can be calculated using the unique signal and orbit parameters of each GPS satellite, and the accurate position of the drone (20) or the image production device (10) can be calculated through trilateration using the position information of each GPS satellite calculated using the GPS receiver equipped in the drone (20) or the image production device (10).

[0033] In addition, the inertial navigation system (INS) is a system that includes a gyroscope and an accelerometer acting as inertial sensors to calculate and control the rotation and positional movement of the drone (20) to help it fly to a desired location, and can receive and collect high-resolution satellite image data captured through the satellite navigation system (GPS) and the inertial navigation system (INS).

[0034] The satellite navigation system (GPS) and inertial navigation system (INS) described above can be integrated into an image production device (10), and various satellite information provided therefrom can be provided to a drone (20) and an image production device (10).

[0035] Next, the image production device (10) can perform image matching for the entire bird's-eye view area using drone image data and satellite image data based on ground reference points of the map production area, by detecting a first ground reference point corresponding to a ground reference point in the drone image data and detecting a second ground reference point corresponding to a ground reference point in the satellite image data, and can perform image matching using the first ground reference point and the second ground reference point.

[0036] In addition, when performing image matching for the entire bird's-eye view area, the first ground control point and the second ground control point can be detected using the image size, and SIFT (scale invariant feature transform) can be used to match the drone image data and the satellite image data by detecting the first ground control point and the second ground control point, respectively.

[0037] For example, a first ground control point is detected in drone image data according to image size, and a second ground control point is detected in satellite image data according to image size. Then, a first descriptive vector and a second descriptive vector are generated to identify the first ground control point and the second ground control point, respectively, and image matching can be performed by measuring the similarity between the generated first descriptive vector and the second descriptive vector. Here, the first ground control point and the second ground control point can be designated and detected by considering ground control points surveyed in the entire bird's-eye view area.

[0038] Specifically, a plurality of Gaussian images corresponding to a drone image and a difference image of the plurality of Gaussian images can be used, and a first ground reference point can be detected by considering the image size. As shown in FIG. 3, a plurality of Gaussian images with a Gaussian filter of a certain multiple applied to the drone image are obtained, and a difference operation is performed on each of the adjacent images in the obtained plurality of Gaussian images to obtain a plurality of difference images.

[0039] In addition, to find the first ground reference point in a plurality of difference calculation images obtained as shown in FIG. 4, the points of 8 pixels surrounding a specific point (X) in the current image and the points of 9 pixels in both adjacent images (i.e., 18 points) are compared, and the point having the smallest or largest value is selected based on the result of comparing a total of 26 pixel points based on the specific point, and the maximum and minimum points can be detected by repeating this process, and the points selected according to the detection result are post-processed according to the image size to select the most stable points, thereby detecting the first ground reference point.

[0040] Meanwhile, in satellite image data, the second ground control point can also be detected in a manner similar to the detection method of the first ground control point as described above.

[0041] Next, a first ground reference point detected in drone image data is described as a first descriptive vector, and a second ground reference point detected in satellite image data is described as a second descriptive vector. Then, image matching can be performed by matching the first ground reference point and the second ground reference point using the first descriptive vector and the second descriptive vector, and image gradients and directions can be obtained for pixels surrounding a specific point.

[0042] And, for the rotation-invariant property, the keypoint descriptor and image gradients can be rotated relative to the point direction, and gradients of all levels can be calculated and represented by small arrows as shown in Fig. 5.

[0043] Here, the descriptor is formed in the form of a vector containing the values ​​of all directional histogram entries, and the lengths of each right arrow as illustrated in FIG. 5 may correspond to the values ​​of the histogram entries.

[0044] As described above, after the detection of the first ground reference point and the second ground reference point according to FIGS. 3 and 4 and the description of the first ground reference point and the second ground reference point according to FIG. 5 are completed, image matching between the drone image data and the satellite image data can be performed.

[0045] For example, when performing image matching using a comparison of similarity between a first ground control point and a second ground control point, if the number of first ground control points in the drone image is N and the number of second ground control points extracted from satellite image data is M, a total of N*M keypoint matching may occur, which has the advantage of requiring fewer operations compared to the existing template matching method based on pixel-to-pixel comparison.

[0046] Here, for image matching judgment, as shown in Fig. 5, weights are assigned using a Gaussian model to the light blue line portion, which is the matching point, and for the final matching judgment, the total score for each point can be summed. That is, image matching can be performed by obtaining a high score where the light blue line portion is concentrated.

[0047] Next, the image production device (10) can produce an orthophoto by modeling the matched image obtained through image matching, and the matched image can be modeled in the form of a point cloud or a mesh, and when modeled in the form of a point cloud, as shown in FIG. 6, it can be modeled using at least one selected from a digital surface model (DSM), a digital elevation model (DEM), and a digital terrain model (DTM).

[0048] Here, the Digital Surface Model (DSM) is surface information that includes all artificial features such as trees and buildings, and can derive a collection of point clouds filled with varying elevation values ​​using an aerial LiDAR (light detection and ranging) system. Here, building roofs, tree tops, power lines, and other shape elevations may also be included.

[0049] Furthermore, a Digital Elevation Model (DEM) is surface data that does not include natural features such as trees or artificial features such as buildings; it represents the uncovered surface as a function of X and Y. It includes the raster method, which divides the terrain into a grid of a fixed size to represent elevation values, and the TIN (triangular irregular network) method, which represents the surface by dividing it into an irregular triangular network. By removing non-surface points such as bridges and roads, a smooth Digital Elevation Model can be obtained.

[0050] In addition, the Digital Terrain Model (DTM) is numerical information regarding the location and elevation of points distributed at a proper density, includes linear features of the uncovered surface terrain, can be obtained through stereophotogrammetry, and can derive a digital elevation model through interpolation from a point distribution at regular intervals and contour lines.

[0051] In addition, the image production device (10) can rearrange the modeled matching image according to the image coordinates to produce an orthophoto as shown in FIG. 7.

[0052] Meanwhile, when the registration image is modeled in the form of a mesh, depth information can be calculated from the image of the registration image, and a mesh image of the mapping area can be formed based on the calculated depth information. Additionally, an orthophoto can be produced by rearranging textures generated based on drone image data according to image coordinates and mapping them onto the mesh image of the entire bird's-eye view area.

[0053] Then, a drone (20) can be flown based on a 3D orthophoto to obtain second drone image data that captures the surroundings of the building object within the entire bird's-eye view area (step 120).

[0054] In the step (120) of acquiring the second drone image data, the drone (20) can be controlled to fly according to the coordinate information and height information of the building object to photograph the surroundings of the building object, and to acquire surrounding images in the up-down direction and left-right direction.

[0055] In addition, in the step (120) of acquiring the second drone image data, a point of interest (POI) located around the building object is further photographed, and the point of interest may include at least one of a public institution, a large mall, a traffic point, and an educational institution.

[0056] For example, in the video production device (10), starting from the edge position of the entire bird's-eye view area (e.g., the boundary position, corner position, etc. in the entire bird's-eye view area of ​​a rectangle) in the 3D orthophoto produced in step 110 as shown in FIG. 8, the drone (20) can be controlled to fly around the building object along the boundary surface of the building object as shown in FIG. 11, after approaching the location of the building object as shown in FIG. 9 and FIG. 10 by referring to the coordinate information and height information of the building object.

[0057] In this way, the drone (20) can fly along a first flight path moving from the bird's-eye view reference point to the location of the building object and a second flight path moving along the boundary surface of the building object, and can take pictures at various angles through a shooting means to obtain second drone image data.

[0058] At this time, the video production device (10) can control the drone (20) to fly along a first flight path so that when it approaches the location of the building object and reaches the boundary surface, it can reflect the entire location of the building object according to the height information of the building object on a second flight path so that it can rotate and move at a position higher than the upper surface of the building object to be built.

[0059] Meanwhile, the video production device (10) extracts a point of interest (POI) including at least one of a public institution, a large mall, a transportation point, and an educational institution located around the building object from a three-dimensional orthophoto of the entire bird's-eye view area, and then controls the drone (20) to fly according to the location information of the extracted point of interest and perform video shooting. The drone (20) may be controlled to fly from a relatively far point of interest to a relatively close point of interest based on the distance from the building object by reflecting it in the first flight path, or divided into the east, west, north, and south directions of the building object by reflecting it in the first flight path and controlled to fly from one area to another, or after flying along the second flight path, the drone (20) may be controlled to fly by generating a third flight path based on distance or direction as described above. Of course, if no point of interest (POI) is extracted, the drone may be controlled not to perform shooting of the point of interest.

[0060] Images captured along the boundary surface of the building object as described above (i.e., surrounding images) can be provided as 3D flight images, and images captured of the region of interest (POI) (i.e., region of interest images) can be provided as 3D flight images or as 360-degree panoramic images.

[0061] Next, the acquired second drone image data can be mapped with a three-dimensional orthophoto to obtain an image of the surroundings of the building object following the flight of the drone (20) as shown in FIG. 12 (step 130).

[0062] In the step (130) of acquiring the surrounding image of the building object, mapping is performed using each bird's-eye reference point of the 3D orthophoto and the second drone image data, and the image may be acquired as a 3D flight image that moves to the location of the building object according to the drone flight path of the second drone image data.

[0063] In addition, in the step (130) of acquiring the surrounding image of the building object, in the case of a region of interest (POI), a region of interest indicator label may be labeled on the surrounding image of the building object.

[0064] For example, the video production device (10) can map the 3D orthophoto image and the 2nd drone video data using a bird's-eye reference point set in the 3D orthophoto image and a bird's-eye reference point that is the flight starting point in the 2nd drone video data, and can be obtained as a flight video moving to the location of the building object according to the drone flight path of the 2nd drone video data (i.e., 1st flight path, 2nd flight path, 3rd flight path, etc.).

[0065] To specifically explain the mapping between the 3D orthophoto and the second drone image data as described above, the second drone image data can be mapped according to the shooting angle of the 3D orthophoto. This is done by using a bird's-eye reference point set in the 3D orthophoto and a bird's-eye reference point that is the flight start point in the second drone image data as references. For each of the multiple frame images extracted from the 3D orthophoto, shooting angles for the x-axis, y-axis, and z-axis can be extracted, and correspondingly, mapping angles for the x-axis, y-axis, and z-axis can be set for each of the multiple frame images extracted from the second drone image data. After setting each tracking point for each frame image (i.e., multiple frame images extracted from the 3D orthophoto and multiple frame images extracted from the second drone image data) with each bird's-eye reference point as the drone flight start point, images with the same shooting angle and mapping angle are respectively matched and composited (mapped) so that the tracking points are connected to each other, thereby generating an image of the surroundings of the building object as a single flight image.

[0066] In addition, the video production device (10) may include a point of interest indicator label labeled on the surrounding image of the building object to provide a general video or a 360-degree panoramic video when an additional image of the point of interest (POI) (i.e., point of interest image) is provided, as shown in FIG. 12, and such point of interest indicator label may include the name of the point of interest, etc.

[0067] To specifically explain the labeling of the region of interest indicator label as described above, after generating a region of interest indicator label containing the region of interest name (e.g., 00 Dong Community Center, 0 Plus, 00 Subway Station, 00 Station, 00 Elementary School, etc.) for the region of interest (POI) extracted from the surrounding image of the building object, the region of interest indicator label can be added to the upper part of the building according to the location coordinates of the region of interest (POI) in the surrounding image of the building object and composited.

[0068] Here, the surrounding image of the building object may include a general video or a 360-degree panoramic video of the point of interest (POI) as a sub-image, and an area of ​​interest indicator label may be used as an input means to display such sub-images. That is, when the area of ​​interest indicator label is selected, the general video or the 360-degree panoramic video of the area of ​​interest (POI), which is the sub-image, may be displayed.

[0069] To explain in detail the various methods of providing 360-degree panoramic images as described above with reference to FIGS. 13a to 13h, when an area of ​​interest display label is selected, a sub-image can be generated so that a panoramic image as shown in FIG. 13a is displayed. A viewing angle screen (red box area) showing the viewing angle area of ​​each site corresponding to each area of ​​interest corresponding to the entire image can be displayed at the upper left corner, and a control panel (blue box area) for providing various panoramic images can be displayed at the lower center.

[0070] In addition, as shown in the upper part of FIG. 13b, when a viewing angle screen (red box area) is selected in the left panoramic image, a sub-image can be generated so that the corresponding viewing angle screen is enlarged by a preset ratio (e.g., 50%) in the right panoramic image, and as shown in the lower part of FIG. 13b, when a thumbnail switching button (red arrow) among the control panels in the left panoramic image is selected, a sub-image can be generated so that the control panel in the right panoramic image is expanded upward and thumbnail images corresponding to each site are displayed sequentially in the expanded space.

[0071] In addition, as illustrated in FIG. 13c, when the backward switching button (red arrow) on the control panel is selected in the central panoramic image representing the second site, the image can be switched to the image representing the first site as in the upper panoramic image, and when the forward switching button (blue arrow) on the control panel is selected in the central panoramic image, a sub-image can be generated so that the image can be switched to the image representing the third site as in the lower panoramic image. Here, when each image is switched, a sub-image can be generated so that the site and the viewing angle can also be switched in the viewing angle screen.

[0072] Meanwhile, as illustrated in FIG. 13d, when the left arrow toggle button (red arrow) on the control panel is selected in the central panoramic image representing the second site, the image can be switched to an image that is rotated to the left by a preset angle, as in the upper panoramic image; and when the right arrow toggle button (blue arrow) on the control panel is selected in the central panoramic image, a sub-image can be generated so that the image can be switched to an image that is rotated to the right by a preset angle, as in the lower panoramic image. Here, when each image is rotated, a sub-image can be generated so that the angle of the viewing angle arc in the viewing angle screen can also be switched.

[0073] In addition, as illustrated in FIG. 13e, when the upward arrow switching button (red arrow) on the control panel is selected in the central panoramic image representing the second site, the image can be switched to an image showing a relatively wider field of view area at that site, similar to the upper panoramic image; and when the downward arrow switching button (blue arrow) on the control panel is selected in the central panoramic image, a sub-image can be generated so that the image can be switched to an image showing a relatively narrower field of view area at that site, similar to the lower panoramic image. Here, when each field of view area is switched, a sub-image can be generated so that the field of view area is also switched in the field of view screen.

[0074] Additionally, as illustrated in FIG. 13f, when the plus (+) toggle button (red arrow) on the control panel is selected in the central panoramic image representing the second site, the image can be converted to a relatively more magnified image of that site, similar to the upper panoramic image; and when the minus (-) toggle button (blue arrow) on the control panel is selected in the central panoramic image, the image can be converted to a relatively more reduced image of that site, similar to the lower panoramic image, so that a sub-image can be generated. Here, when the image is magnified or reduced, the sub-image can be generated so that the arc of the field of view in the field of view screen can be converted to narrow or widen.

[0075] Meanwhile, as illustrated in FIG. 13g, when the VR environment switching button (red arrow) on the control panel is selected in the central panoramic image representing the second site, a sub-image can be generated so that it can be switched to a VR image corresponding to the site, such as the upper panoramic image. In the case of such a VR image, when the communication terminal (30) receives the corresponding model house image and displays the VR image corresponding to the sub-image panoramic image, the sub-image can be generated so that various types of panoramic images can be provided according to the operation using the input means (e.g., keyboard, mouse, keypad, touchscreen, etc.) of the communication terminal (30).

[0076] In addition, as shown in FIG. 13h, when the full-screen switching button (red arrow) among the control panels in the central panoramic image representing the second site is selected, the image can be switched to the full-screen image of the corresponding site as in the upper panoramic image, and when the downward switching button (blue arrow) among the control panels in the central panoramic image is selected, the image can be switched to the lower panoramic image where the control panel is hidden, and when the upward switching button (yellow arrow) is selected in the lower panoramic image, a sub-image can be generated so that it can return to the central panoramic image.

[0077] Meanwhile, a 3D model can be performed based on the building information of the building object to generate an image of the building object (step 140).

[0078] In the step (140) of generating the above-mentioned building object image, the building object may be modeled according to site information, specification information, floor plan design drawings for each floor, and construction information, and the building object image may be provided as an overall exterior image or as a stacked image in which each floor is sequentially stacked.

[0079] For example, the image production device (10) can receive site information (i.e., GPS coordinate information where the building object is scheduled to be built), specification information (i.e., size, area, height, etc. of the building object), floor plan drawings for each floor, and construction information (e.g., temporary construction, reinforced concrete construction, masonry construction, stonework, tile construction, interior construction, waterproofing construction, roof and gutter construction, metalwork, plastering construction, window and door construction, glass construction, painting construction, interior finishing construction, panel construction, furniture construction, etc.) from a design office terminal (city omitted) and model the image of the entire structure of the building object into a 3D model.

[0080] This overall structure image can be produced as an overall exterior image, which is a 3D model of the entire structure, or as a stacked image, which is a 3D model showing the building status of each floor, utilizing specification information and floor plan drawings for each floor so that it can be displayed sequentially from the lowest floor (i.e., 1st floor) to the highest floor (i.e., the top floor of the building object) on the planned construction site (i.e., the location of the building object).

[0081] In addition, an image of the building object can be mapped onto an image of the surroundings of the building object to generate an overall bird's-eye view image as illustrated in FIGS. 14 and 15 (step 150).

[0082] In the step (150) of generating the above overall bird's-eye view image, the image of the building object is mapped onto the surrounding image of the building object, and the overall bird's-eye view image can be generated by synthesizing it according to the coordinate information where the building object will be built.

[0083] For example, the image production device (10) can generate an overall bird's-eye view image by extracting coordinate information of the building object from an image of the building object's surroundings and mapping the image of the building object to a corresponding location according to the extracted coordinate information of the building object, and such an overall bird's-eye view image can be generated for each building object and stored and managed as a model house image for each building object.

[0084] To specifically explain the mapping of the surrounding image of the building object and the building object image as described above, the building object image, which is a 3D model, can be mapped according to the shooting angle of the surrounding image of the building object, which is a 3D flight image. For each of the multiple frame images extracted from the surrounding image of the building object, shooting angles for the x-axis, y-axis, and z-axis can be extracted, and corresponding mapping angles for the x-axis, y-axis, and z-axis can be set for each of the multiple frame images extracted from the building object image. After setting each tracking point for each frame image (i.e., multiple frame images extracted from the surrounding image of the building object and multiple frame images extracted from the building object image), images with the same shooting angle and mapping angle can be matched to each other and composited (mapped) so that the tracking points are connected to each other, thereby generating a single overall bird's-eye view image.

[0085] Meanwhile, when a model house image of a building object is requested from a communication terminal (30), an overall bird's-eye view image can be extracted and transmitted to the communication terminal (30) (step 160).

[0086] Here, the communication terminal (30) is a terminal registered in response to a client who wishes to view a model house video of a building object, and may include, for example, a smartphone, a mobile phone, a navigation system, a computer, a laptop, a digital broadcasting terminal, a PDA (Personal Digital Assistants), a PMP (Portable Multimedia Player), a tablet PC, a game console, a wearable device, an IoT (Internet of Things) device, a VR (Virtual Reality) device, an AR (Augmented Reality) device, etc.

[0087] The communication terminal (30) can connect to a web server, etc. operated by the video production device (10), select a building object that wishes to view the model house video, and request the transmission of the model house video. The video production device (10) can extract the model house video of the requested building object and transmit it to the communication terminal (30) through the web server. Accordingly, the communication terminal (30) can display the transmitted model house video through a video display application installed therein.

[0088] Here, the communication network (40) may include, for example, a mobile communication network, a wired internet communication network, a wireless internet communication network, a broadcasting network, an administrative network (closed network), and specifically, may include one or more networks such as a PAN (personal area network), LAN (local area network), CAN (campus area network), MAN (metropolitan area network), WAN (wide area network), BBN (broadband network), the Internet, LoRaWAN, and may include one or more network topologies such as a bus network, a star network, a ring network, a mesh network, a star-bus network, a tree network, a hierarchical network.

[0089] Through this communication network (40), a communication environment for transmitting and receiving wired and wireless data between each of the video production device (10), drone (20), and communication terminal (30) can be provided.

[0090] Accordingly, according to an embodiment of the present invention, a drone is used to construct a three-dimensional orthophoto of the surroundings, photograph the surroundings of the target building, and then three-dimensionally model the building. Afterward, the image of the surroundings of the target building and the three-dimensional modeling image are mapped onto the produced three-dimensional orthophoto to effectively provide an overall bird's-eye view of the target building.

[0091] Meanwhile, embodiments of the present invention may also be implemented in the form of a recording medium containing instructions executable by a computer, such as a program module executed by a computer, wherein the computer-readable medium may be any available medium accessible by a computer, may include both volatile and non-volatile media, and both removable and non-removable media, and the computer-readable medium may include all computer storage media.

[0092] Here, computer storage media may include all volatile and non-volatile, removable and non-removable media implemented by any method or technique for storing information such as computer-readable instructions, data structures, program modules or other data.

[0093] Although the method of the present invention has been described in relation to specific embodiments, it is obvious that some or all of its components or operations may be implemented using a computer system having a general-purpose hardware architecture.

[0094] Although various embodiments of the present invention have been presented and described in the above description, the present invention is not necessarily limited thereto, and those skilled in the art will readily understand that various substitutions, modifications, and changes are possible within the scope of the technical concept of the present invention. Explanation of the symbols

[0095] 10 : Video production device 20 : Drone 30 : Communication terminal 40 : Communication network

Claims

Claim 1 A step of producing a 3D orthophoto using first drone image data in which the entire bird's-eye view area is captured using a drone; a step of acquiring second drone image data by flying the drone based on the 3D orthophoto to capture the surroundings of the building object within the entire bird's-eye view area; a step of acquiring an image of the surroundings of the building object resulting from the flight of the drone by mapping the acquired second drone image data with the 3D orthophoto; and a step of generating an image of the building object by performing 3D modeling according to the building information of the building object. and a step of generating an overall bird's-eye view image by mapping the image of the building object onto the image of the surroundings of the building object; wherein the step of acquiring the second drone image data comprises controlling the drone to fly according to the coordinate information and height information of the building object to photograph the surroundings of the building object, wherein the drone is controlled to fly around the building object along the boundary surface of the building object after approaching the location of the building object by referring to the coordinate information and height information, starting from a bird's-eye view reference point which is the edge position of the overall bird's-eye view area in the 3D orthophoto, and then controlling the drone to fly around the building object by flying the drone according to a first flight path moving from the bird's-eye view reference point to the location of the building object, and when the drone approaches the location of the building object and reaches the boundary surface, the drone is controlled to rotate at a position higher than the top surface of the building object to be constructed by reflecting the second flight path moving along the boundary surface of the building object in order to view the entire location of the building object according to the height information, thereby acquiring the second drone image data; and the step of acquiring the second drone image data comprises the After extracting a region of interest (POI) from a 3D orthophoto that includes at least one of a public institution, a large mall, a transportation point, and an educational institution located around the building object, the drone is controlled to fly and perform video recording according to the location information of the extracted region of interest.Controlling the drone to fly from a relatively distant area of ​​interest to a relatively close area of ​​interest based on the distance from the building target object by reflecting it in the first flight path, or controlling it to fly from one area to another by dividing the building target object into east, west, north, and south directions based on the first flight path, or controlling the drone to fly by generating a third flight path based on distance or orientation after flying along the second flight path; the step of acquiring images of the surroundings of the building target object involves mapping using each bird's-eye reference point of the 3D orthophoto and the second drone image data, wherein the images are acquired as 3D flight images moving to the location of the building target object according to the drone flight path of the second drone image data, wherein shooting angles of the x-axis, y-axis, and z-axis are extracted for each of the multiple frame images extracted from the 3D orthophoto, and mapping angles of the x-axis, y-axis, and z-axis are set for each of the multiple frame images extracted from the second drone image data, and wherein each bird's-eye reference point is used as the drone flight starting point for each frame image A method for producing architectural modeling images using a drone, wherein, after setting tracking points, images having the same shooting angle and mapping angle are respectively matched to create a composite image of the surroundings of the architectural object so that the tracking points are connected to each other, and the step of acquiring the image of the surroundings of the architectural object includes, in the case of the region of interest (POI), a region of interest indicator label being labeled on the image of the surroundings of the architectural object. Claim 2 delete Claim 3 delete Claim 4 In claim 1, the step of generating the image of the building object comprises a method for producing a building modeling image using a drone, which is modeled according to site information, specification information, floor plan design drawings of each floor, and construction information regarding the building object. Claim 5 In claim 4, the step of generating the overall bird's-eye view image comprises mapping the image of the building object onto the surrounding image of the building object, and synthesizing the image according to the coordinate information where the building object is to be constructed to generate the overall bird's-eye view image, a method for producing an architectural modeling image using a drone. Claim 6 A method for producing an architectural modeling image using a drone, wherein, in any one of claims 1, 4, and 5, the method further comprises the step of extracting the overall bird's-eye view image and transmitting it to the communication terminal when a model house image of the architectural object is requested from the communication terminal.

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