CN113496552A - City model generating and processing method - Google Patents

Abstract

A city model generation and processing scheme is provided. The generation method comprises the following steps: acquiring building plane shape data and building height and/or type data of a plurality of buildings in a target range; generating a three-dimensional building model based on the building plane shape data for each of a plurality of buildings according to the building height and/or type data of the plurality of buildings; adding a top surface pattern to the three-dimensional building model; and adding a facade pattern to the three-dimensional building model. According to the scheme, the random detail addition following the rules is carried out on the building objects, so that the city can be more sensible, and a more intuitive visual scene is provided for a user in the application of data analysis and decision making processes.

Description

City model generating and processing method

Technical Field

The invention relates to the field of data visualization, in particular to a city model generating and processing method.

Background

In the process of visualizing urban scenes, the real world space to be expressed is a three-dimensional geometric space, and any object in the space contains three-dimensional spatial information. Conventional two-dimensional Geographic Information Systems (GIS) involve the representation of planar two-dimensional information only. Due to the lack of a corresponding solution, in the prior art, based on existing data, a three-dimensional scene can only be a white box which starts up in a field, and a building lacks details. Therefore, in the aspect of visual performance, an effective generation scheme needs to be established for urban scenes.

Disclosure of Invention

In order to solve at least one problem, the invention provides a city model generation and processing scheme. According to the scheme, the random detail addition following the rule is carried out on the building object, so that the city has more somatosensory feeling. Meanwhile, in applications such as data analysis and decision making processes, a more intuitive visual scene is provided for a user.

According to a first aspect of the present invention, a method for generating a city model is provided, including: acquiring building plane shape data and building height and/or type data of a plurality of buildings in a target range; generating a three-dimensional building model based on the building plane shape data for each of a plurality of buildings according to the building height and/or type data of the plurality of buildings; adding a top surface pattern to the three-dimensional building model; and adding a facade pattern to the three-dimensional building model.

According to a second aspect of the present invention, a city model processing method is provided, including: according to the selected range, obtaining city model information in the corresponding range, wherein the city model is generated according to the method; presenting the city model within the corresponding range.

According to a third aspect of the present invention, a city model generation method is provided, including: acquiring object plane shape data and object height and/or type data of a plurality of objects in a target range; generating a stereoscopic object model based on the object plane shape data for each of a plurality of objects according to the object height and/or type data of the plurality of objects; adding a top surface style to at least a portion of the stereoscopic object model; and adding a facade style to at least a portion of the stereoscopic object model.

According to a fourth aspect of the invention, there is provided a computing device comprising: a processor; and a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the model generation or processing method as described above.

According to a fifth aspect of the present invention, a non-transitory machine-readable storage medium is presented, having executable code stored thereon, which when executed by a processor of an electronic device, causes the processor to perform a model generation or processing method as described above.

By utilizing the method and the system, the buildings can be classified into high, medium and low (central business district, residential building and low layer of shop) based on the building height of the city, and the corresponding models and maps are matched for generation aiming at different building characteristics, so that a set of complete automatic city model generation scheme is provided, the automatic reduction can be carried out on the building group in the real world to the maximum extent, and the city can be seen as true as possible by matching different rules according to different building heights.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent by describing in greater detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.

FIG. 1 shows a schematic flow diagram of a city model generation method according to one embodiment of the invention.

Fig. 2 shows an example of display of a city block in a two-dimensional map.

Fig. 3 shows an example of dividing buildings according to the height of the house.

Fig. 4 shows examples of the top surface structure pattern and the top surface map pattern.

Fig. 5 shows some examples of the top surface decorations.

Fig. 6 shows an example showing a facade map.

Fig. 7 shows an example of a three-dimensional building model map.

Fig. 8 shows an example of a map of a three-dimensional building model completed by a plurality of buildings in a specific area.

FIG. 9 shows a schematic flow diagram of a city model processing method according to one embodiment of the invention.

FIG. 10 illustrates a schematic block diagram of a computing device that may be used to perform the above-described city model generation and processing method, according to one embodiment of the invention.

Detailed Description

Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

In the process of visualizing urban scenes, the real world space to be expressed is a three-dimensional geometric space, and any object in the space contains three-dimensional spatial information. Conventional two-dimensional Geographic Information Systems (GIS) involve the representation of planar two-dimensional information only. Due to the lack of a corresponding solution, in the prior art, based on existing data, a three-dimensional scene can only be a white box which starts up in a field, and a building lacks details.

In large-screen application scenarios such as smart cities, a city often needs to be manually modeled to be large in scope. The above presentation requires a large expenditure of manpower and material resources. Therefore, in the aspect of visual performance, an effective generation scheme needs to be established for urban scenes.

The invention provides a city model generation and processing scheme. According to the scheme, random details following rules are automatically added aiming at the building object, so that the city is more sensible while the modeling labor input is greatly reduced, and the built model can provide a more intuitive visual scene for a user in the application of data analysis and decision processes.

FIG. 1 shows a schematic flow diagram of a city model generation method according to one embodiment of the invention. Herein, a "city model" may refer to a model that characterizes a city scenario. Here, the "city" refers to a region with a dense population and a developed industrial and commercial property, and generally includes functional sections such as residential areas, industrial areas, and commercial areas. The city has the infrastructure of buildings, streets, parks and the like. In other words, an urban scene is typically a scene that contains a large number of buildings and road networks. In the present invention, "city model" may further refer to a large model of a city range or an approximate city range. In other words, the present invention is preferably applied to the establishment of a large model, for example, a model of a central urban area (inside a ring ) of Shanghai city, a model of a West lake area of Hangzhou city, or the like, rather than a small model having only a few or a few tens of buildings, for example, a certain garden or a cell.

In step S110, building plan shape data and building height and/or type data of a plurality of buildings within a target range are acquired.

As indicated previously, the present invention is a solution for building large models in urban scenarios. To this end, the target range may be a range of the large model itself that needs to be built, for example, a central urban area of Shanghai city. However, for reasons of computer processing power and editability, the model range may be divided into a plurality of sub-ranges according to certain rules (e.g., different zones and streets, specific roads, latitudes and longitudes, etc.), and the sub-range modeling may be performed for each sub-range (i.e., the currently processed sub-range is the target range).

After the target range to be processed is determined, building plan shape data and building height and/or type data of a plurality of buildings included in the range may be acquired. Fig. 2 shows an example of display of a city block in a two-dimensional map. As shown, buildings in an urban scene are displayed in a two-dimensional map as planar shape data (i.e., footprint) of the buildings as shown in box 1. In addition, in the two-dimensional map database, the height of a building (e.g., 15 meters) and/or the type of building, such as a low-rise dwelling, a high-rise business building, and the like, are also typically stored. The data may be obtained from the two-dimensional map database as described above, or may be obtained via other means, for example, a city planning database. The invention is not limited in this regard.

Subsequently, in step S120, a three-dimensional building model based on the building plane shape data may be generated for each of a plurality of buildings according to the building height and/or type data of the plurality of buildings. At this time, the three-dimensional building model may be generated by performing the raising based on the building height data (or building type data capable of representing the height, for example, a bungalow) according to the plane position where the building plane shape is located.

However, since the stereoscopic building model generated at this time lacks details (for example, only white boxes), a top surface pattern may be added to the generated stereoscopic building model at step S130, and a facade pattern may be added to the stereoscopic building model at step S140, thereby generating a three-dimensional city model having construction details.

The invention can automatically generate the three-dimensional building model by reading the existing building information of the database, and then automatically add the top surface style and the facade style, thereby obtaining the city model with the building details, greatly improving the visualization degree of the city model and expanding the application scene of the model.

Preferably, in the invention, the top surface patterns and the facade patterns can be randomly selected from the top surface and facade database according to the preset rules for adding, so that the automatic addition of the details of a large number of buildings (for example, thousands or even tens of thousands of buildings) in the target area is automatically realized, and the large-scale city model data suitable for large-screen display is quickly and efficiently obtained.

In one embodiment, the adding of the top surface style to the solid construction model at step S130 may include: and selecting a top surface pattern from the top surface database, and adding the selected top surface pattern to the three-dimensional building model. In particular, buildings are of varying importance or prominence, depending on height and type. Thus, a facade pattern may be randomly selected from a corresponding facade sub-database of heights and/or types based on the building height and/or type data for the building.

In one embodiment, the building may be divided into a low floor (civil house, business, etc.), a middle floor (mainly residential building), and a high floor (skyscraper). Fig. 3 shows an example of dividing buildings according to the height of the house. Buildings below 24m can be divided into low-rise buildings, buildings between 24m and 100m can be divided into middle-rise buildings, and buildings above 100m can be divided into high-rise buildings. In other cities, different heights may be used for division, for example, in small and medium cities lacking high-rise buildings, the division height threshold for the middle and high-rise buildings may be lowered.

Since the application scenario (e.g., large screen presentation scenario) of the urban model is usually concentrated in areas with more concentrated commercial activities, public opinions and traffic. The buildings in the area mainly comprise a middle layer and a high layer, wherein the high layer has the characteristics of easy identification, good visual effect and concentrated house arrangement. Therefore, rules defined by the high-rise model can be relatively complex, and conversely, the low-rise building is paved without complex rules.

To this end, three sub-databases, a lower level, a middle level and a higher level, may be provided in the top style database, and the three sub-databases may have the same, partially the same, and usually most different top style material stored therein. For example, the high-rise top-style sub-database may store more and more complex top-style materials and may be randomly selected by a certain rule for high-rise buildings (e.g., buildings larger than 100 m).

In one embodiment, the parameter-matching ceiling pattern may also be randomly selected from a ceiling database based on the parameter data of the building. The parameter data may be data for reflecting building attributes, for example, may include the building height or type as above, and may also include other attribute data, for example, the material of the outer wall (glass), the year of the building, and the like. Accordingly, the top surface style material in the top surface database may also have corresponding description parameters. Subsequently, when the random selection of the style is carried out, the addition of the constraint condition can ensure rich variability and avoid large deviation of detail addition. For example, a building includes parameters (mid-floor and 1990), for which purpose when selecting a roof pattern, a roof pattern may be selected that also includes the above-described parameters (or a roof pattern that rejects conflicting parameters), thereby allowing for efficient random generation of building details with little deviation from the actual building details.

In some embodiments, the top surface pattern may include a top surface structure pattern and a top surface map pattern. Since the ceiling structure pattern involves more details and more computations, a ceiling pattern may be added for certain non-important or inconspicuous buildings, and a ceiling pattern including the ceiling structure pattern (and the ceiling pattern) is selected for buildings above a threshold height and/or of a particular type. Fig. 4 shows examples of the top surface structure pattern and the top surface map pattern. The left side of the diagram shows two examples of the top surface structure pattern and the right side shows two examples of the top surface map pattern. As shown on the left side of the figure, the top surface design includes a specific three-dimensional structure including the illustrated lightning rod structure stacked in the forward direction (i.e., small area up), even as shown on the left. The overlay pattern may comprise a planar (or near-planar) pattern, such as a simple gray roof as shown in the right two, or a slightly undulating tile roof. In practical applications, for low-rise or unimportant building types, no top structure pattern or only a forward or reverse stacking pattern as a base can be added, and simple top mapping is performed, such as a pure color mapping shown in the right two. For higher or more important building types, the top structure pattern can be added first, and then the top map pattern can be added, and the higher the building is, the more complex the building can be selected for.

Preferably, a topping ornament may also be added according to the added topping style. After different main body houses and roofs are combined, in order to further enhance the details of the building, decorations can be added to be matched with the high-precision main body model, and the detail sense is enhanced. The added ornamentation can be a suite of different models within a randomly distributed ornamentation database on the roof. Fig. 5 shows some examples of the top surface decorations. As shown, the kit may include a water tank, a skylight, a beacon, a signal light, an air conditioner, various ventilation ducts, and the like. In other embodiments, the kit may also include an apron, a satellite dish, and the like. The random addition of the top surface decorations can be carried out according to different rules for buildings with different heights. For example, for low-rise buildings below 24m, the top decoration can be optionally not added. For a mid-level building of 24-100m, a top decoration may be added, for example, with a 30% probability. For high-rise buildings above 100m, it is possible to add the rooftop decoration with a higher probability, for example, 50%, i.e. half of the high-rise buildings are added with the rooftop decoration after the rooftop structure pattern is added, and then the application of the rooftop map pattern is performed. The top surface ornament may be added by randomly adding an ornament kit stored in an ornament database in consideration of the area and the structural shape of the top surface.

In addition, it is understood that, in the present invention, adding a top surface pattern to a three-dimensional building model may be determining a correlation addition of the top surface pattern of a certain three-dimensional building model based on the top surface patterns of neighboring buildings. The correlation additions may be the same or different. For example, for adjacent buildings having the same building plane shape, it can be determined that these buildings have the same configuration, and therefore the same ceiling pattern can be added to these adjacent buildings. For example, in a central business district where high buildings stand, the top surface pattern addition for each high-rise building ensures low repeatability between the high-rises, so that the model is reproduced as realistic as possible.

Since the addition of the top surface style also comprises the addition of the structure style, the addition of the facade style can be to add the facade style to the three-dimensional building model after the top surface style is added. Adding facade styles to the solid building model may include: and randomly selecting a facade pattern from the corresponding height and/or type facade sub-database based on the building height and/or type data of the building.

Similarly, the buildings may be classified into low floors (civil houses, shops, etc.), middle floors (mainly residential buildings), and high floors (skyscrapers), and for example, buildings lower than 24m may be classified into low floors, buildings of 24m to 100m may be classified into middle floors, and buildings of 100m or more may be classified into high floors. Since the application scenario (e.g., large screen presentation scenario) of the urban model is usually concentrated in areas with more concentrated commercial activities, public opinions and traffic. The buildings in the area mainly comprise a middle layer and a high layer, wherein the high layer has the characteristics of easy identification, good visual effect and concentrated house arrangement. Therefore, the facade rules defined by the high-rise model can be relatively complex, and conversely, the low-rise building is laid, and complex rules are not needed.

For this purpose, three sub-databases of a lower layer, a middle layer and a higher layer can be arranged in the facade pattern database, and the three sub-databases can store the same, partially same and usually most different facade pattern materials. For example, the high-rise facade pattern sub-database can store more and more complex facade pattern materials, and high-rise buildings (for example, buildings larger than 100 m) can be randomly selected according to certain rules.

Fig. 6 shows an example showing a facade map. The elevation map can also be called a wall map, and the wall map can be divided into three types of low type, high type and high type according to the height, and named by height-attribute + sequence number.

Low-rise buildings (shown in the pattern of Low-build050.JPG, the name corresponds to: Low-rise 050) usually mainly use wall maps with Low-rise building attributes, such as red bricks and tiles, and the window area is generally smaller than the wall surface, so that the general effect of a civil house shop is simulated.

The middle building (shown as Mid-building 035.JPG, the name corresponds to: middle-building 035), mainly comprises tiles for the middle building, and the proportion of window wall surfaces is approximately 1: 1, has certain life and office interest, and is a wall surface map mainly for residential buildings and middle office buildings.

The High-rise building (the pattern is High-build035.JPG, the name is corresponding to the High-rise building 035) mainly comprises bricks and tiles of the High-rise building, mainly comprises large-size French windows or more windows, and has strong commercial interest.

In one embodiment, the matched facade pattern of the parameters can be randomly selected from a facade database based on the parameter data of the building. The parameter data may be data for reflecting the building attribute, for example, may include the building height or type as above, and may also include other attribute data, for example, the exterior wall material (glass), the building year, and the like. Correspondingly, the facade style materials in the facade database can also have corresponding description parameters. Subsequently, when the random selection of the style is carried out, the addition of the constraint condition can ensure rich variability and avoid large deviation of detail addition. In addition, the corresponding facade pattern can be selected from the facade database based on the top surface pattern added to the three-dimensional building model. In other words, where there is some correlation between the top and facade patterns, the choice of facade pattern may depend in part on the top pattern that has been determined.

Similarly, adding a top surface pattern to a stereo building model may be determining a correlation addition of a facade pattern of a certain stereo building model based on facade patterns of neighboring buildings. The correlation additions may be the same or different. For example, for adjacent buildings having the same building plane shape, it can be determined that these buildings have the same configuration and appearance, and therefore the same facade pattern can be added to these adjacent buildings. For example, in a central business district of a high-rise building, the facade pattern addition for each high-rise building ensures low repeatability between the high-rise buildings, so that the model is reproduced as truly as possible.

In the invention, the addition of the facade pattern and the top pattern aiming at the three-dimensional building model can be completed by model mapping. The model map comprises a facade map and a top map. The elevation requires the X-axis and Y-axis tiling to be basically seamless, and the pattern of the map accords with the functional attributes of different building heights. For example, the attribute of the low-rise civil house needs to be matched with red bricks, tile bricks and the like to have the attribute of the low-rise building elevation and the top surface map. In one embodiment, the topmaps may be of type 2, with a common set of style databases at the lower level and the middle level. The high level uses a unique set of style databases. This is because high-rise buildings need to be fitted with high-rise decorations: parking apron, signal tower, water tank and other buildings.

Fig. 7 shows an example of a three-dimensional building model map. As shown, a left-side three-dimensional building model may be first generated based on the building plan shape and height. Then, based on the building height and its ceiling area, a ceiling structure is randomly selected from the ceiling structure pattern candidates in the database that fit the height and ceiling area. After combining the three-dimensional construction model with the roof structure, the construction model supplemented with construction details is completed from the roof and the three-dimensional map.

Fig. 8 shows an example of a map of a three-dimensional building model completed by a plurality of buildings in a specific area. The left side of fig. 8 shows the effect map of the addition of the ceiling structure and decorations within one block. The right side of fig. 8 shows an effect diagram in which a facade pattern and a top pattern are further added. It is apparent from fig. 8 that the architectural effect shown on the right side of fig. 8, after the addition of top and elevation details, is already highly realistic and more conducive to presenting a vivid urban landscape than, for example, the white box shown on the left side of fig. 7. In addition, as shown in fig. 8, various types of effects may be added to the model as needed, for example, a night mode with a light effect added as shown in fig. 8.

After the urban building group within the target range is automatically generated according to the invention, each building can be refined. For example, manual refinement may be made for signage (e.g., the eastern pearl television tower) or accented areas (e.g., the continental house mouth). In one embodiment, a satellite image and/or a street view image corresponding to geographic coordinates may be introduced to modify the top surface style and/or the facade style of the solid building model. Due to the problem of the shooting angle of the satellite image and/or the street view image, a certain angle correction operation is usually required when the satellite image and/or the street view image are suitable for the images. Finally, the colors, objects or materials in the images can be identified, and the generated building can be automatically refined according to the colors, the objects or the materials.

In addition, the road network plays a crucial role in creating urban scenes. To this end, the city model generation method of the present invention further includes: adding a road pattern to the road plan shape region. Adding the road pattern to the road plan shape region may include: determining a road style to be added according to the road grade and/or the region.

In one embodiment, road networks may be divided into two categories, one being precision roads within the target range and the other being low precision roads outside the non-emphasis range. The precision road modeling may include lane number, separator, road type, etc., which may then be composed of simple patches.

The precision roads may be classified into expressways, primary, secondary, and tertiary roads, etc., each having different lanes and form rules.

In addition, other elements, such as plants, rivers, lakes, or the like, may also be added to the city model. Since these objects are typically low in height, they can typically be rendered with low accuracy.

In a large-screen city scene, a large-scale model is often manually established for presentation in a city, and therefore, in the prior art, a large amount of manpower and material resources are consumed for presenting the effect of the plane. By using the method and the system, the buildings can be classified into high, medium and low (central business district, residential building and low layer of shop) based on the building height of the city, and the corresponding models and maps are matched for generation aiming at different building characteristics, so that a set of complete automatic city model generation scheme is provided, the automatic reduction of the building group in the real world can be maximally performed, and the city can be seen as real as possible by matching different rules according to different building heights.

After the city model is generated as above, the above model can also be applied. Therefore, the invention can also be realized as a city model processing method. FIG. 9 shows a schematic flow diagram of a city model processing method according to one embodiment of the invention.

In step S910, according to the selected range, city model information in the corresponding range is obtained. The city model is generated according to the city model generation method. Then, in step S920, the city model in the corresponding range is presented.

It should be understood that the main body executing the above city model processing method of the present invention may be, for example, a client on which the city model using software is installed, or may be an originating end for creating the city model. In either case, the city model generated above is retrieved from the database and presented at the user end according to a selected scope (e.g., currently actively selected or selected by default).

In one embodiment, the presenting of step S920 may be presenting a city model including a building stereo model of a plurality of buildings within a large screen. Here, the "large screen" may be a screen having a larger display area and capable of simultaneously displaying more contents with high precision, compared to a personal computer display screen or a mobile display screen. The large-screen application scene is often the places such as a monitoring center, a traffic guidance center or a smart city display center.

Thus, through the presentation of the stereoscopic city model, it is possible to: a good application tool is provided for the fields of traffic, geology, mines, surveying and mapping and the like; an effective tool for decision making and decision making participation is provided for managers and residents; more accurate 3D data and visual effect are provided for a traffic navigation system; and establishing a virtual reality model of the travel environment.

After rendering, various subsequent operations may also be performed on the city model. In one embodiment, the processing method may further include: adding a target test source to the city model; adding corresponding reaction parameters to the three-dimensional building model; and performing a target test in the city model. For example, the environmental protection department may perform diffusion analysis of noise, heat radiation, pollution, and the like of a city based on the above model, and in the communication field, the coverage of electric waves in the city environment and the like may be calculated using 3D data (for example, by adding a signal source, calculating reflection parameters of buildings to signal waves, and the like).

Further, in the case that the execution subject is a development end, or a client can store a copy of the model modification, the method may further include: selecting a three-dimensional building model from the presented city models; and modifying the selected three-dimensional building model. Here, the modifying the selected three-dimensional building model includes: and performing associated modification on the plurality of three-dimensional building models according to the building height and/or type data. Therefore, the method and the device can be conveniently refined by developers, and can be used for building planning conveniently by establishing a real building model of a construction area in civil engineering and architectural engineering.

As mentioned above, the city model generation and processing method of the invention can match corresponding models and map generation aiming at different building characteristics based on the building height of the city, thereby providing a set of complete automatic city model generation scheme. In a broader embodiment, the model generation and rendering method of the present invention may also be directed to a wider range of modeled objects, especially when the city building model skyline is not high, or there are other tall objects in addition to the building model. Therefore, the invention can also be realized as a city model generation method, comprising: acquiring object plane shape data and object height and/or type data of a plurality of objects in a target range; generating a stereoscopic object model based on the object plane shape data for each of a plurality of objects according to the object height and/or type data of the plurality of objects; adding a top surface style to at least a portion of the stereoscopic object model; and adding a facade style to at least a portion of the stereoscopic object model.

Here, the "object" may include, in addition to the "building" as described above, other landscape objects having a considerable height within a city, for example, a natural geographical landscape, or a plant such as a street tree, and the like. Thus, a stereo object model may also be generated for these objects. For the three-dimensional object models, the addition of a facade pattern or a top surface pattern can be performed for a part of the three-dimensional object models. For example, a hill may be reconstructed based on contour data and corresponding trees added as top and/or facade patterns. For example, mountain top portions as top surfaces, foot portions as elevation surfaces, and the like. And when the skyline of the urban model is not high, modeling can be performed on plant group objects such as shrubs and the like, and top surface patterns and facade patterns such as flowers and the like are added.

The city model thus generated, including other objects, may also be processed based on the embodiment described in fig. 9, for example, for rendering on a large screen.

FIG. 10 illustrates a schematic block diagram of a computing device that may be used to perform the above-described city model generation and processing method, according to one embodiment of the invention. The computing device may be a developer that participates in model generation or a client that invokes a model.

Referring to fig. 10, the computing device 1000 includes a memory 1010 and a processor 1020.

The processor 1020 may be a multi-core processor or may include multiple processors. In some embodiments, processor 1020 may include a general-purpose host processor and one or more special purpose coprocessors such as a Graphics Processor (GPU), Digital Signal Processor (DSP), or the like. In some embodiments, processor 1020 may be implemented using custom circuits, such as an Application Specific Integrated Circuit (ASIC) or a Field Programmable Gate Array (FPGA).

The memory 1010 may include various types of storage units, such as system memory, Read Only Memory (ROM), and permanent storage. Wherein the ROM may store static data or instructions that are needed by the processor 1020 or other modules of the computer. The persistent storage device may be a read-write storage device. The persistent storage may be a non-volatile storage device that does not lose stored instructions and data even after the computer is powered off. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the permanent storage may be a removable storage device (e.g., floppy disk, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as a dynamic random access memory. The system memory may store instructions and data that some or all of the processors require at runtime. Further, the memory 1010 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic and/or optical disks, among others. In some embodiments, memory 1010 may include a removable storage device that is readable and/or writable, such as a Compact Disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, dual layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, min SD card, Micro-SD card, etc.), a magnetic floppy disc, or the like. Computer-readable storage media do not contain carrier waves or transitory electronic signals transmitted by wireless or wired means.

The memory 1010 has stored thereon executable code that, when processed by the processor 1020, may cause the processor 1020 to perform the above-described city model generation and processing methods.

The city model generation and processing method according to the present invention has been described in detail hereinabove with reference to the drawings. In urban scenes, especially large-screen urban scenes, a large-scale model is often manually established for presentation in a city, and therefore, in the prior art, a large amount of manpower and material resources are consumed for presenting the effect of the city. By utilizing the method and the system, the buildings can be classified into high, medium and low (central business district, residential building and low layer of shop) based on the building height of the city, and the corresponding models and maps are matched for generation aiming at different building characteristics, so that a set of complete automatic city model generation scheme is provided, the automatic reduction can be carried out on the building group in the real world to the maximum extent, and the city can be seen as true as possible by matching different rules according to different building heights.

Furthermore, the method according to the invention may also be implemented as a computer program or computer program product comprising computer program code instructions for carrying out the above-mentioned steps defined in the above-mentioned method of the invention.

Alternatively, the invention may also be embodied as a non-transitory machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) having stored thereon executable code (or a computer program, or computer instruction code) which, when executed by a processor of an electronic device (or computing device, server, etc.), causes the processor to perform the steps of the above-described method according to the invention.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the disclosure herein may be implemented as electronic hardware, computer software, or combinations of both.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims (23)

1. A city model generation method, comprising:

acquiring building plane shape data and building height and/or type data of a plurality of buildings in a target range;

generating a three-dimensional building model based on the building plane shape data for each of a plurality of buildings according to the building height and/or type data of the plurality of buildings;

adding a top surface pattern to the three-dimensional building model; and

and adding a facade pattern to the three-dimensional building model.

2. The method of claim 1, wherein adding a roof style to the solid construction model comprises:

selecting a top surface style from a top surface database; and

and adding the selected top surface style to the three-dimensional building model.

3. The method of claim 2, wherein selecting the top surface style from the top surface database comprises:

and randomly selecting a top surface pattern from the corresponding height and/or type top surface sub-database based on the building height and/or type data of the building.

4. The method of claim 3, wherein the top surface pattern comprises at least one of:

a topmap style; and

the structural style of the top surface is the same as that of the top surface,

and selecting the top surface style from the top surface database comprises:

selecting a roof pattern comprising the roof construction pattern for a building above a threshold height and/or of a particular type.

5. The method of claim 1, wherein adding a roof style to the solid construction model comprises:

and determining the top surface pattern of a certain three-dimensional building model based on the top surface patterns of the adjacent buildings.

6. The method of claim 1, further comprising:

adding a top decoration according to the added top style.

7. The method of claim 6, wherein adding a top surface decoration comprises:

adding a roof pattern to a plurality of buildings within the target range with a predetermined probability.

8. The method of claim 1, wherein adding facade styles to the solid building model comprises:

and adding a facade pattern to the three-dimensional building model added with the top pattern.

9. The method of claim 8, wherein adding facade styles to the solid building model comprises:

and randomly selecting a facade pattern from the corresponding height and/or type facade sub-database based on the building height and/or type data of the building.

10. The method of claim 8, wherein adding facade styles to the solid building model comprises:

and selecting a corresponding facade pattern from a facade database based on the top surface pattern added by the three-dimensional building model.

11. The method of claim 1, wherein adding facade styles to the solid building model comprises:

and determining the vertical face pattern of a certain three-dimensional building model based on the vertical face patterns of the adjacent buildings.

12. The method of claim 1, further comprising:

and modifying the top surface style and/or the facade style of the three-dimensional building model according to the satellite image and/or the street view image.

13. The method of claim 1, further comprising:

adding a road pattern to the road plan shape region.

14. The method of claim 13, wherein adding a road pattern to a road plan shape region comprises:

determining a road style to be added according to the road grade and/or the region.

15. The method of claim 1, wherein adding a roof style to the solid construction model comprises:

randomly selecting a parameter-matched ceiling pattern from a ceiling database based on the building parameter data, and/or

Adding facade styles to the three-dimensional building model comprises:

and randomly selecting a parameter-matched facade pattern from a facade database based on the parameter data of the building.

16. A city model processing method comprises the following steps:

obtaining city model information in a corresponding range according to the selected range, wherein the city model is generated according to any one of claims 1-15;

presenting the city model within the corresponding range.

17. The method of claim 16, wherein presenting the city model within the corresponding range comprises:

an urban model comprising a three-dimensional model of a building of a plurality of buildings is presented within a large screen.

18. The method of claim 16, further comprising:

adding a target test source to the city model;

adding corresponding reaction parameters to the three-dimensional building model; and

and carrying out target test in the urban model.

19. The method of claim 16, further comprising:

selecting a three-dimensional building model from the presented city models;

and modifying the selected three-dimensional building model.

20. The method of claim 19, wherein modifying the selected three-dimensional building model comprises:

and performing associated modification on the plurality of three-dimensional building models according to the building height and/or type data.

21. A city model generation method, comprising:

acquiring object plane shape data and object height and/or type data of a plurality of objects in a target range;

generating a stereoscopic object model based on the object plane shape data for each of a plurality of objects according to the object height and/or type data of the plurality of objects;

adding a top surface style to at least a portion of the stereoscopic object model; and

a facade style is added to at least a portion of the stereoscopic object model.

22. A computing device, comprising:

a processor; and

a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method of any one of claims 1-21.

23. A non-transitory machine-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the method of any one of claims 1-21.

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