A building vector graphics multi-scene intelligent simplification method and system

Abstract

The application discloses a building vector graphics multi-scene intelligent simplification method and system, and belongs to the technical field of geographic information systems. The method comprises the following steps: establishing a four-level data system comprising an original data layer, an engineering cache layer, a display cache layer and a terminal view layer; listening to data changes and user interaction events through an event bus; intelligently identifying a current application scene and dynamically loading corresponding simplification parameter configurations in response to the events; executing simplification logic on target building vector graphics based on the configurations; querying topological relationships to cooperatively process adjacent building outlines; and synchronously updating the processing results to the four-level data system. Through four-level data caching, double-drive triggering and scene self-adaptive decision-making, the application realizes efficient, high-quality and self-adaptive processing of building simplification in multiple scenes such as drawing synthesis, real-time display and spatial analysis, and improves system flexibility, resource utilization and user experience.

Description

Technical Field

[0001] This application relates to the field of geographic information system technology, and in particular to a simplified intelligent method and system for multi-scene building vector graphics. Background Technology

[0002] In the fields of Geographic Information Systems (GIS), digital mapping, and cartographic generalization, the automated simplification of building outline vector graphics is a fundamental and crucial technical step. Its core objective is to selectively remove redundant geometric details while retaining important morphological features and topological relationships when converting large-scale geographic data to small-scale representations, thus meeting the visualization, analysis, and storage needs of different application scenarios. Currently, this field mainly faces technical bottlenecks such as poor adaptability to multiple scenarios, rigid processing workflows, insufficient system scalability, and low efficiency in human-machine collaboration.

[0003] Most existing technical solutions are designed for single scenarios. For example, in cartographic scaling scenarios, algorithms typically focus on strictly adhering to cartographic specifications, using preset geometric thresholds (such as minimum area and shortest side length) to batch simplify building outlines. While these methods ensure the results meet publication requirements at a specific scale, the processing is often time-consuming, and the simplified data cannot be directly used in real-time display scenarios requiring high interactivity. Conversely, display simplification algorithms designed for rapid map rendering typically employ screen spatial error or viewpoint-dependent level of detail (LOD) techniques to generate visually coherent simplified graphics in real time. However, these algorithms often overemphasize rendering performance, potentially compromising key right-angle features, symmetry, or topological relationships with adjacent features, rendering the simplified data unusable for spatial analysis or as part of authoritative geographic databases.

[0004] A deeper technical deficiency lies at the system architecture level. Most existing systems employ a simple two-layer model of "raw data - displayed data," with processing flows typically unidirectional and static. When the raw data is updated, the system often needs to trigger a complete recalculation chain from the raw data to the final displayed data. This "one-size-fits-all" approach is inefficient when processing large-scale urban building data. Furthermore, its triggering mechanisms are mostly passive responses, driven either by data changes or by scheduled tasks, lacking proactive awareness and intelligent response capabilities to real-time user interactions (such as map zooming, panning, and changes in viewpoint focus) and hardware context (such as terminal device performance and network conditions). For example, when a user quickly pans the map viewport, the system may still be processing building details that have been moved off-screen in the previous viewport, resulting in wasted computing resources and delayed interactive responses.

[0005] Furthermore, existing technologies have significant shortcomings in supporting complex editing operations (such as "pushing edges" and "grooving") and topological collaborative processing (such as synchronous adjustment of adjacent buildings). These operations require the system to not only modify the geometry of a single building but also maintain and update its related spatial relationships in real time, which traditional simplification engines based on isolated object processing struggle to handle. For complex surface structures containing inner islands (such as building atriums), existing methods also lack effective mechanisms for inner and outer ring collaboration and protection, easily leading to topological errors during simplification or editing.

[0006] Therefore, there is an urgent need in this field for a novel, system-level solution capable of uniformly addressing the entire chain of needs, from data production and cartographic synthesis to real-time visualization and interactive editing. This system should possess scenario-adaptive intelligent decision-making capabilities, support flexible and diverse triggering and response mechanisms, adopt a layered and decoupled architecture to balance processing efficiency and data quality, and fully support various refined operations and topology consistency maintenance requirements. Summary of the Invention

[0007] This application provides a simplified intelligent method and system for building vector graphics across multiple scenarios, addressing the systemic technical problems of poor adaptability, low efficiency, difficulty in maintaining topological consistency, and rigid system architecture in automated building vector graphics simplification technologies when facing multiple application scenarios (such as drafting, analysis, real-time display, and interactive editing).

[0008] In a first aspect, embodiments of this application propose an intelligent simplification method for multi-scene building vector graphics, comprising: establishing a four-level data system in a computer system, including an original data layer, an engineering cache layer, a display cache layer, and a terminal view layer; listening to and receiving data change events and / or user interaction events at any layer via an event bus; responding to any triggered event, identifying the current application scenario and dynamically loading the corresponding simplification parameter configuration; performing simplification processing on one or more layers of building vector graphics within the event's influence range, wherein the simplification processing includes simplification logic for verifying overlapping areas between three consecutive judgment units and / or adjacent judgment units according to the simplification parameter configuration; querying the topological relationships between buildings and performing collaborative processing on the outlines of adjacent buildings; and synchronously updating the simplification processing results to the corresponding level of the four-level data system within the event's influence range.

[0009] In one embodiment of this application, identifying the current application scenario specifically includes: extracting multi-dimensional features from the current context, the features including at least one of the following: viewport display scale, user operation mode, and terminal device performance; matching the extracted features with a predefined scene feature template to determine the scene type; the scene type includes at least one of the following: real-time display scene, geographic analysis scene, and cartographic integration scene.

[0010] In one embodiment of this application, the simplification logic for verifying the overlapping area between three consecutive judgment units and / or adjacent judgment units according to the simplification parameter configuration specifically includes: for the outer ring contour of a building, starting from the initial vertex, constructing a first judgment unit with three consecutive vertices along the vector direction; sliding one vertex to construct an adjacent second judgment unit; calculating the geometric overlap area between the first judgment unit and the second judgment unit; when the overlap area meets the conditions in the simplification parameter configuration of the current scene, performing boundary simplification on the corresponding protruding or concave part; repeating the above process until the outer ring contour is traversed.

[0011] In one embodiment of this application, the conditions in the simplification parameter configuration include at least one of the following: the area of ​​the overlapping region is less than the area threshold, the length of the short side of the judgment unit is less than the short side threshold, and the length of the long side of the judgment unit is less than the long side threshold.

[0012] In one embodiment of this application, the method further includes adaptive simplification of gaze focus: obtaining the user's gaze point position on the screen; dividing the current viewport into a focus area, a transition area, and a background area centered on the gaze point; and applying different simplification parameter configuration values ​​to buildings in different areas.

[0013] In one embodiment of this application, the method further includes multi-scale continuous level of detail processing: pre-generating multiple discrete levels of detail for buildings; establishing a continuous mapping relationship between the display scale and the level of detail; and dynamically interpolating intermediate geometry based on the mapping relationship and the simplified parameter configuration value when the user zooms in on the map.

[0014] In one embodiment of this application, the querying of the topological relationship between buildings and the collaborative processing of the outlines of adjacent buildings specifically includes: when the boundary of a single building moves due to simplification, querying the topological relationship table to obtain all adjacent buildings; and performing collaborative translation adjustment on the corresponding boundaries of all adjacent buildings related to the moved boundary.

[0015] In one embodiment of this application, the collaborative processing of the outlines of adjacent buildings further includes the processing of composite surface structures: when performing outer ring simplification or editing operations on a building containing an inner ring outline, the geometric coordinates of the inner ring outline are automatically locked and remain unchanged.

[0016] Secondly, embodiments of this application also propose an intelligent simplification device for building vector graphics, used to implement the method described in any embodiment of the first aspect of this application. The device includes: a four-level data system manager for establishing a four-level data system; a dual-drive event listener for listening to and receiving data change events and user interaction events at any level; a scene recognition engine for identifying the current application scene and loading corresponding scene configuration parameters; an adaptive simplification decision maker for performing simplification processing on building vector graphics within the event's influence range; a topology relationship processor for querying spatial relationships between buildings and performing collaborative processing; and a data synchronization controller for synchronously updating the simplification processing results to the corresponding level of the four-level data system within the event's influence range.

[0017] Thirdly, embodiments of this application also provide a building vector graphics processing system, comprising: a building vector graphics intelligent simplified device as described above, deployed in a data processing server, or the data processing server being configured to execute the method described in any one of the embodiments of the first aspect of this application; an original database storing building data and topological relationships; a cache server storing project cache and display cache; one or more user terminals; and a message communication middleware connecting the data processing server, the original database, the cache server, and the user terminals.

[0018] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned intelligent simplified method for multi-scene building vector graphics.

[0019] Fifthly, embodiments of this application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the intelligent simplified method for multi-scene building vector graphics as described above.

[0020] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects:

[0021] In terms of quality, the scene-adaptive decision mechanism ensures that the simplification results always maintain an optimal match with the current application goals. In display scenarios, the rendering frame rate is more stable and smooth; in analysis scenarios, the loss of geometric accuracy is reduced; and in mapping scenarios, the topology error rate is reduced, resulting in a significant improvement in output quality.

[0022] In terms of system flexibility, the modular design allows new simplification algorithms or business rules to be easily integrated like plug-ins. The event- and data-driven dual-engine model enables the system to respond to various internal and external changes. Multi-terminal adaptability allows the same core system to serve a full range of products, from professional mapping workstations to mobile field data acquisition equipment.

[0023] In terms of efficiency, the system avoids redundant calculations through a four-level data caching system and an intelligent triggering mechanism, improving the cache hit rate and reducing the response latency of real-time interaction. The distributed collaborative processing architecture significantly improves the speed of processing massive amounts of building data compared to traditional serial methods.

[0024] In terms of user experience, adaptive gaze focus and continuous LOD technology enhance visual smoothness and immersion, making human-computer interaction more intuitive and efficient. Attached Figure Description

[0025] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0026] Figure 1 This is a flowchart illustrating an embodiment of the intelligent multi-scene method for building vector graphics in this application;

[0027] Figure 2 This is a flowchart of an embodiment of the method of this application that is further optimized based on the focal point of the line of sight;

[0028] Figure 3 This is a flowchart of an embodiment of the method of this application that is further optimized according to the scale change;

[0029] Figure 4 The flowchart illustrates a further optimized embodiment of the method in this application that incorporates distributed collaboration.

[0030] Figure 5 This is an embodiment of the intelligent simplified device for multiple scenes using building vector graphics, as described in this application;

[0031] Figure 6 This is a further optimized embodiment of the device of this application;

[0032] Figure 7 This is a flowchart illustrating an embodiment of the intelligent simplified system for multiple scenes using building vector graphics, as described in this application.

[0033] Figure 8 A schematic diagram illustrating the adaptive simplification effect of the line of sight focus;

[0034] Figure 9 This is a schematic diagram illustrating the generation and mapping effects of multi-scale continuous LOD.

[0035] Figure 10 A schematic diagram illustrating the effects of distributed collaborative simplification and boundary coordination;

[0036] Figure 11 A schematic diagram illustrating the adjustment effect of adjacent buildings in topology collaborative processing;

[0037] Figure 12 This is a schematic diagram illustrating the effect of the inner ring island protection mechanism for topology collaborative processing. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0039] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0040] Figure 1 This is a flowchart illustrating an embodiment of the intelligent multi-scene method for building vector graphics in this application. (Refer to...) Figure 1 , 8 ~9, 11, The method provided in this embodiment includes:

[0041] Step 110: Establish and maintain a four-level data system in the computer system, including the raw data layer, the project cache layer, the display cache layer, and the terminal view layer.

[0042] This application abandons the traditional two-layer model and introduces four logical levels:

[0043] Raw data layer: Stores fully detailed, high-precision building vector surface data and its complete topological relationship table, serving as the sole true data source.

[0044] Project caching layer: Designed for specific graph or analysis projects, it stores data that has been preprocessed and partially simplified according to project rules.

[0045] Display cache layer: geared towards real-time visualization, storing display-optimized and simplified data relevant to the current and predictive viewports.

[0046] Terminal view layer: Located on the client device, it stores the minimalist geometry currently displayed on the screen and the user interaction state.

[0047] The key to the four-level system lies in intelligent synchronization and incremental updates between levels. When the original data changes, the change information propagates outwards layer by layer like ripples, but the system intelligently determines which downstream caches need to be invalidated and rebuilt, rather than recalculating the entire dataset. In other words, the impact of an event at any level extends to one or more levels, or involves a predefined spatial range. For example, a minor edit to a building might only trigger an update to the display cache of its viewport, without affecting other unrelated data in the project cache. The foundation of the data layer is the raw database, typically composed of a cluster of relational databases with powerful spatial processing capabilities (such as PostgreSQL with PostGIS). This stores the original data of all buildings: each building face is precisely recorded by its outer ring vertex sequence, and if an inner ring (such as a courtyard) exists, it is stored as an independent ring sequence. More importantly, an explicit topological relationship table is maintained here, recording spatial relationships such as "adjacent," "disjoint," and "contained" between buildings, and calculating and storing information such as the minimum distance and shared edges between them. This table is the data foundation for all subsequent collaborative processing.

[0048] Step 120: Listen for and receive data change events and / or user interaction events from any layer via the event bus.

[0049] Specifically, the system simultaneously monitors two types of trigger sources: one is data-driven triggering: when the building geometry in the original database is modified, added, or deleted, or its topological relationships change, the system automatically captures these change events and triggers the update process of related data in the project cache and display cache. The other is event-driven triggering: mainly responding to user interactions and system state changes. This includes: viewport change events; user interaction operation events; scene switching events; system resource events, etc.

[0050] Internally, the system operates an event bus or message queue that continuously listens for signals from various sources. Data-side signals are relatively stable but critical. Database triggers or change data capture tools monitor the raw data tables. Once a building is inserted, updated, or deleted, or the topology table changes, a structured message is published to the event bus.

[0051] The real-time requirements for event-side signals are high. In one embodiment of this application, the user interaction event includes at least one of the following: viewport change events and direct editing operation events. Processing priorities are assigned to different types of events, with direct editing operation events having a higher priority than viewport change events. For example, user interaction events have the highest priority: when a user presses the mouse to start a "push" operation, a high-priority event containing the operation type, target building ID, and drag vector is immediately issued. As another example, viewport change events have the highest frequency: continuous viewport change events are filtered, and a simplification process is triggered in response to parameter changes exceeding a preset threshold. Every zoom and pan on the map generates an event, but the system performs intelligent filtering. In a preferred embodiment, a true reprocessing process is only triggered when the change exceeds a certain threshold (e.g., a zoom ratio change exceeding 10%, or a panning distance exceeding 20% ​​of the screen), preventing invalid calculations caused by micro-operation jitter. Scene switching events indicate changes in the macroscopic working state, such as switching from "browse" to "edit".

[0052] Step 130: In response to any triggering event, identify the current application scenario and dynamically load the corresponding simplified parameter configuration.

[0053] In some embodiments, identifying the current application scenario specifically includes: extracting multi-dimensional features from the current context, the features including at least one of the following: viewport display scale, user operation mode, and terminal device performance; matching the extracted features with a predefined scene feature template to determine the scene type; the scene type includes at least one of the following: real-time display scene, geographic analysis scene, and cartographic generalization scene. These scene types also determine the hierarchy involved in the scope of the event's impact.

[0054] The scene recognition engine analyzes the current context to determine the strategy configuration to be followed for simplification. Internally, it maintains a "scene feature library." For example, features for a "display scene" might include high-frequency viewport events and strict frame rate requirements; features for a "scenario analysis scene" might include the need for area measurement and high geometric accuracy requirements. The decision maker matches the current context with the feature library, calculating the scene label with the highest confidence, such as "display - fast walkthrough." Based on the identified scene, the corresponding parameter configuration file is loaded. For example, in the "display - background area" scene, the system uses larger area and length thresholds for more aggressive simplification to improve rendering speed; while in the "edit - focus building" scene, it uses extremely small thresholds to preserve almost all details to ensure editing accuracy.

[0055] The simplification parameter configuration is a key data carrier connecting the application scenario and the core simplification algorithm. It is a set of predefined or real-time calculated thresholds and rules used to precisely control the intensity and criteria of building outline simplification. It is not fixed, but dynamically selected and invoked by the system's scene recognition engine according to the different emphases on accuracy, speed, and topology consistency in different scenarios (such as "real-time display", "geographic analysis", "cartographic generalization").

[0056] For example, the simplification parameter configuration may include at least one of the following configurable parameters: geometric threshold parameters, operation strategy parameters, and context fine-tuning parameters, the combination of which determines different simplification conditions.

[0057] The geometric threshold parameters may further include at least one of the following parameters: Area threshold: used to determine whether the overlapping area formed by three adjacent judgment units (see step 140) is small enough to be negligible. For example, in a display scenario, this threshold is larger for radical simplification; in an editing scenario, this threshold is extremely small to preserve all details. Short side threshold and long side threshold: used to directly determine excessively short sides or disproportionately long sides in the building outline, as a supplement to the area criterion. These thresholds collectively determine which geometric features are considered "redundant" and should be simplified.

[0058] The operational strategy parameters may further include at least one of the following: Simplification mode: for example, an "aggressive mode" allows for greater geometric deformation in exchange for performance, while a "conservative mode" prioritizes maintaining the original appearance. Detail retention level: indicates whether secondary structures such as doors, windows, and balconies are retained. Topology maintenance rules: specifies the strength of topological consistency maintenance for adjacency relationships, shared edges, etc., during simplification.

[0059] Context-adjusted parameters, for example, combined with the viewpoint focus adaptive process, assign differentiated thresholds to the building dynamics in different areas of the screen (focus area, transition area, background area) to achieve optimal resource allocation, as well as differentiated thresholds for different scale ranges.

[0060] Step 140: According to the simplification parameter configuration, perform simplification processing on the vector graphics of one or more buildings within the event's influence range. The simplification processing includes simplification logic for verifying the overlapping areas between three consecutive judgment units and / or adjacent judgment units.

[0061] In one embodiment, the logic specifically includes: for the outer ring contour of the building, starting from the initial vertex, constructing a first judgment unit (e.g., P1-P2-P3) with three consecutive vertices along the vector direction; sliding one vertex to construct an adjacent second judgment unit (e.g., P2-P3-P4); calculating the geometric overlap region between the first and second judgment units (this region shares edge P2-P3); when the overlap region satisfies the conditions in the simplification parameter configuration of the current scene, performing boundary simplification on the corresponding protruding or concave part; and repeatedly executing the above sliding construction and judgment process until the outer ring contour has been traversed.

[0062] It should be noted that the protruding or concave structures that need simplification are often found near the common edge (P2-P3) of two decision units. By comparing the shape, area, and side length of the two units, it can be determined whether the contour segment represented by this common edge is a "redundant protrusion" or an "irrelevant concavity," thus deciding whether to flatten or fill it. The simplification strategy can be to remove the shared edge that meets the simplification conditions or at least one of the two adjacent decision units.

[0063] In some embodiments, the conditions in the simplified parameter configuration are generally multi-dimensional threshold conditions, which include at least one of the following: the area of ​​the overlapping region is less than the area threshold, the length of the short side of the judgment unit is less than the short side threshold, and the length of the long side of the judgment unit is less than the long side threshold.

[0064] For example, the decision maker starts from the first valid vertex of the building's outer ring, constructing a "decision unit A" consisting of three consecutive vertices, followed by constructing adjacent "decision units B" sharing two vertices. The overlap between the geometric regions of these two units is calculated. At this point, dynamic parameters come into play: if the overlap area is less than the area threshold for the current scene (e.g., 100 square pixels), the local contour represented by this overlap area (which might be a small bump or groove) is deemed redundant, and a simplification operation of deletion or filling is performed. If the area condition is not met, the process continues to check if the shorter or longer side is less than its corresponding threshold. After completing one judgment / operation, the window slides one vertex to continue processing the next group of adjacent units, until all vertices have been traversed.

[0065] A further optimized simplification scheme allows the effective vertices to be selected from those participating in the simplification process. For example, it can be achieved by comparing whether the deviation of the vertex angle from the standard angle (e.g., 90°) is less than a set value (e.g., 10°). This ensures that only minor irregularities within an approximately right-angled system are simplified. Other selection rules can also be set, which will not be detailed here.

[0066] As a further optimization and simplification scheme, the calculation may also include "reverse overlap judgment". When two judgment units do not overlap directly, one of the judgment units is flipped along the common edge to artificially create an overlapping area.

[0067] In some embodiments, the decision maker may also be fine-tuned in real time based on more nuanced context. For example, even in a "display-fast roaming" scenario, if the system predicts that the currently processed building is near the user's mouse pointer, the decision maker will temporarily reduce the parameter threshold for that building by half, thereby ensuring visual detail in the focus area even in the context of fast roaming.

[0068] Step 150: During the simplification process, query the topological relationships between buildings and perform collaborative processing on the outlines of adjacent buildings.

[0069] In this application, the simplified parameter configuration values ​​are set independently or in association, depending on the building entity (or geographic entity).

[0070] The effect of independent settings is that different building entities can be simplified separately. When setting up independently, the simplification parameter configuration values ​​can be the same or different.

[0071] The effect of association settings is that different building entities can undergo simplification operations simultaneously. When setting up association, the simplification parameter configuration values ​​can be the same or different. In this case, when simplifying a building, its adjacent buildings are adjusted simultaneously. Specifically, this is done by detecting whether there are other building boundaries within a preset pixel distance of the moving boundary; if so, corresponding translation or clipping is performed. This avoids topological conflicts (overlaps or gaps) caused by simplifying a single building, maintaining the overall consistency of the building group.

[0072] Preferably, the system maintains an explicit "topology table" to record spatial relationships such as adjacency and containment between buildings. Querying the topology relationships between buildings and collaboratively processing the outlines of adjacent buildings includes: when the boundary of a single building moves due to simplification, querying the topology table to obtain all adjacent buildings; and performing collaborative translation adjustments on the corresponding boundaries of all adjacent buildings related to the moved boundary. If the boundary of a building moves due to simplification, the system immediately queries the topology table to find all other adjacent buildings within the tolerance distance, and automatically performs collaborative translation or adjustment on the conjugate boundaries of these buildings, completely eliminating graphic gaps or overlaps caused by processing individual buildings.

[0073] Figure 11Taking two adjacent buildings as an example, this demonstrates how the system automatically identifies the adjacent relationship and synchronously adjusts the boundary of the other building when the boundary of one building shifts due to simplification, thereby maintaining the original collinear or gap relationship. It should be noted that the boundaries of the adjacent buildings can also be different parts of the same building entity; when an adjacent relationship exists, collaborative processing can also be performed.

[0074] Step 160: Synchronously update the simplification results to the corresponding level of the four-level data system within the scope of the event's impact.

[0075] In some embodiments, the simplified or edited final result is reverse-synchronized to the original database (e.g., for editing operations), and the project cache, display cache, and terminal view data are updated incrementally and level by level to ensure data consistency. For example, when a user requests new viewport data, the search proceeds upwards level by level until the cache is hit at a certain level or the data is finally retrieved from the original database. The top-down data flow is primarily driven by "data changes." For instance, if a user edits a building on the terminal, this modification is treated as a transaction. First, the original database is committed and updated, then a "data updated" event is triggered. This event intelligently notifies the project cache and display cache: "The old version of the XX building you hold is invalid; please update." The system accurately reconstructs the affected data blocks based on the scope of the invalidation, rather than clearing the entire cache. This incremental synchronization mechanism is key to the system's efficiency.

[0076] Figure 2 As a further optimization of the method of this application, refer to Figure 2 , Figure 8 In this embodiment, after step 130, an adaptive simplification process for the line of sight focus is further included.

[0077] Step 210: Obtain the user's gaze point position on the screen.

[0078] For example, the system estimates the user's current visual focus using an eye tracker (if available) or mouse position.

[0079] Step 220: Divide the current viewport into a focal area, a transition area, and a background area, centered on the gaze point.

[0080] Centered on this point, define multiple concentric regions: the core focal area (e.g., radius 100 pixels), the outer transition area (100-300 pixels), and the outermost background area (beyond 300 pixels).

[0081] Step 230: Apply different simplified parameter configuration values ​​to buildings in different areas.

[0082] In embodiments of this application, the simplification parameter configuration values ​​change in response to changes in the display area. For buildings falling within different areas, the system applies completely different simplification strategies. Buildings in the focus area enjoy the highest privilege: the system can disable aggressive simplification, employing a strict threshold similar to that used in the analysis scene, preserving fine details such as doors, windows, and balconies. Buildings in the transition area receive conventional display simplification. Buildings in the background area are significantly simplified: the system uses the highest threshold, aggregating multiple small buildings into clusters and simplifying complex outlines into basic rectangles. In a further optimized embodiment, to achieve natural integration between areas, the system performs "boundary smoothing" on adjacent but different buildings at the edges of the transition area, using geometric interpolation to gradually change the degree of simplification, avoiding harsh detail break lines. This process is particularly suitable for real-time navigation of large-scale 3D city models.

[0083] Figure 3 As a further optimization of the method of this application, refer to Figure 3 , Figure 9 This embodiment further includes a multi-scale continuous detail level processing flow after step 130.

[0084] Step 310: Pre-generate multiple discrete levels of detail for the building.

[0085] During the preprocessing stage, the system generates multiple discrete simplification levels for important or complex buildings, ranging from the full detail model (LOD0) to the minimum bounding box (LODn).

[0086] Step 320: Establish a continuous mapping relationship between the display scale and the level of detail.

[0087] The system establishes a mapping relationship between the scale and the LOD level during the preprocessing stage. For example, 1:500 is mapped to LOD0, 1:2000 is mapped to LOD2, and 1:10000 is mapped to LOD4.

[0088] In this application, the simplified parameter configuration value changes in response to a change in scale. For example, at a scale of 1:2000, the overlapping area is set to 50 square pixels.

[0089] Step 330: When the user zooms in on the map, the intermediate geometry is dynamically generated by interpolation based on the mapping relationship and the simplified parameter configuration value.

[0090] When a user zooms in on the map, the system quickly locates the two closest pre-calculated LOD levels based on the current scale, and then interpolates the geometry of the intermediate state in real time based on the simplified parameter configuration values ​​of different scales, thus achieving continuous detail changes.

[0091] Figure 4As a further optimization of the method of this application, refer to Figure 4 , Figure 10 Based on steps 140-150, this embodiment further includes a distributed collaborative simplification and boundary processing flow.

[0092] Step 410: Divide the geographic region into multiple computing partitions and assign them to different computing nodes.

[0093] For example, the spatial extent of the entire geographic region can be divided into several non-overlapping grids (partitions), and each partition can be assigned to a computing node.

[0094] Step 420: Identify and coordinate the handling of boundary buildings that cross the zone.

[0095] The system identifies "boundary buildings" that geometrically span multiple partitions. The data for these boundary buildings is replicated to all relevant nodes. Each node processes the buildings within its own partition (including local buildings and replicated boundary buildings) independently and in parallel.

[0096] In this application, the simplification parameter configuration values ​​are set independently for different nodes. Depending on the needs, the simplification parameter configuration values ​​may be the same or different on different nodes.

[0097] Step 430: Collect the results from each node and apply the consensus algorithm to determine the final version.

[0098] In a further optimized embodiment, the simplified parameter configuration values ​​of different nodes can be unified. For example, each node processes data according to the same simplified parameter configuration values, or after processing, a coordinator node is responsible for collecting the processing results of all "boundary buildings" on each node, determining a final version through a consensus algorithm (such as voting or taking the centralized result), and distributing it back to all relevant nodes for unified updates, thereby ensuring the topological consistency of the entire region's data after distributed processing.

[0099] In further optimized embodiments, the simplification parameter configuration values ​​for different nodes can also be responded to independently. For example, in processing composite surface structures, in one embodiment, when performing outer ring simplification or editing operations on a building containing an inner ring contour (such as a building courtyard), the geometric coordinates of the inner ring contour are automatically locked to remain unchanged. The system explicitly marks the inner and outer ring attributes in the data model. When performing any simplification or "edge pushing (boundary translation)" or "grooving (local inward translation of the boundary to form a groove)" operations on the building's outer ring, the geometric coordinates of the inner ring can be automatically locked to remain unchanged, thereby ensuring the integrity of the composite surface structure. Conversely: the inner ring can be translated, rotated, or deleted independently, while the outer ring remains unchanged.

[0100] Figure 12This means that when a user performs a "pull edge" operation on a building with a courtyard, the geometry editing operator only calculates and applies the translation transformation of the outer ring vertices, while the coordinates of all vertices in the inner ring are forced to remain unchanged. Therefore, no matter how the user drags the outer wall, the inner "courtyard" remains fixed in its original geographical location.

[0101] Figure 5 This is a schematic diagram of an embodiment of the intelligent simplified device for building vector graphics according to this application. The device is used to implement the steps of the aforementioned method embodiments. The device 500 includes:

[0102] The four-level data system manager 51 is used to establish and maintain a four-level data system comprising a raw data layer, a project cache layer, a display cache layer, and a terminal view layer, corresponding to step 110 in the method embodiment. Its output consists of access interfaces and status information for each level of data storage, which can be called by other modules.

[0103] The dual-drive event listener 52 is used to simultaneously listen for and receive events from either layer, such as data change events from the original database and user interaction events from the user terminal (user interaction events such as viewport change events and direct editing operation events), corresponding to step 120 in the method embodiment. Its output is a captured and structured stream of high, medium, and low priority events.

[0104] Scene recognition engine 53 is used to identify the current application scene and load the corresponding scene configuration parameters. In response to any triggered event, it extracts multi-dimensional features from the current context (including at least one of the following: viewport display scale, user operation mode, terminal device performance), and matches these features with predefined scene feature templates to determine the scene type (including at least one of the following: real-time display scene, geographic analysis scene, and cartographic integration scene), corresponding to step 130 in the method embodiment. Its inputs are the event content captured by the dual-drive event listener 52, and the current operation mode and device performance information fed back from other parts of the system (such as the terminal or performance monitoring unit). Its output is the scene label and the corresponding simplified parameter configuration set.

[0105] The adaptive simplification decision unit 54 is used to perform simplification processing on the building vector graphics within the event's influence range based on the scene configuration parameters. The simplification processing includes simplification logic that verifies overlapping areas between three consecutive judgment units and / or adjacent judgment units, corresponding to step 140 in the method embodiment. Its input is the building geometry data to be processed and the dynamically loaded simplification parameter configuration, and its output is the simplified building geometry after judgment.

[0106] The topology relation processor 55 is used to query and maintain the topology relations between buildings during the simplification process, and to perform collaborative processing on the outlines of adjacent buildings. Specifically, when the boundary of a single building moves due to simplification, it queries the topology relation table to obtain all adjacent buildings, and performs collaborative translation adjustment on the corresponding boundaries of all adjacent buildings related to the moved boundary, corresponding to step 150 in the method embodiment. Its input is the building and its change information that have undergone geometric changes, output by the adaptive simplification decision unit 54, and its output is the final geometric shape of all buildings that need to be synchronously adjusted (including the original changed building and its adjacent buildings).

[0107] The data synchronization controller 56 is used to synchronously update the simplification processing results to the corresponding levels of the four-level data system (original data layer, engineering cache layer, display cache layer, and terminal view layer) within the scope of the event's influence, corresponding to step 160 in the method embodiment. Its input is the final geometric result output by the topology relationship processor 55, and its output is an incremental update instruction or data failure notification initiated to each level of data storage to maintain data consistency.

[0108] Figure 6 The schematic diagram illustrates a further optimized embodiment of the device of this application, showing the refined modules of the adaptive simplification decision unit 54 and the newly added optimized functional modules. The adaptive simplification decision unit 54 further includes:

[0109] The parameter dynamic configuration module 541 is used to load the corresponding threshold parameters (such as area threshold, short side threshold, and long side threshold) according to the scene type provided by the scene recognition engine 53, so as to realize the multi-dimensional dynamic configuration of the conditions in the parameter configuration.

[0110] The judgment unit construction module 542 is used to construct continuous three-vertex judgment units. For the outer ring contour of the building, starting from the initial vertex, a first judgment unit is constructed with three consecutive vertices along the vector direction, and a second judgment unit is constructed by sliding one vertex.

[0111] The overlapping area calculation module 543 is used to calculate the geometric overlapping area between adjacent judgment units, such as the first judgment unit and the second judgment unit.

[0112] The condition decision module 544 is used to evaluate the overlapping region based on a threshold and trigger simplification. For example, based on the threshold provided by the parameter dynamic configuration module 541, the overlapping region calculated by the overlapping region calculation module 543 is evaluated. When the conditions in the simplification parameter configuration are met, boundary simplification is performed on the corresponding convex or concave parts, and this process is repeated until the outer ring contour is traversed.

[0113] Preferably, the apparatus further includes a distributed processing coordinator (not shown in the figure) for implementing distributed collaborative simplification, specifically including: dividing the geographical area into multiple computing partitions and assigning them to different computing nodes; identifying and coordinating the processing of boundary buildings crossing the partitions; collecting the results from each node and applying a consensus algorithm to determine the final version, corresponding to the method embodiment. Figure 4 The process involves interacting with each computing node through a message communication interface. The input consists of the area to be processed and building data, and the output is a unified and simplified result after boundary coordination.

[0114] In one embodiment, the distributed processing coordinator receives batch simplification task events (e.g., a cartographic generalization project processing data across an entire city) from the dual-drive event listener 52, or regional task sharding instructions from the task scheduler (located at the system server layer, not shown in the figure). Additionally, it obtains full building data and topological relationships for the region to be processed from the four-level data system manager 51. The output distributes the partitioned tasks and boundary building data to each computing node via a message communication middleware; receives and integrates the preliminary results returned by each node; and sends the final results, determined through coordination, to the data synchronization controller 56 for unified updating. The functions of the adaptive simplification decision maker 54 and the topology relationship processor 55 are distributedly encapsulated and extended. It decomposes a large-scale geosimplification task into multiple subtasks, each of which, on an independent computing node, essentially still executes the simplification and topology coordination logic defined by the decision maker 54 and the processor 55. Its core added value lies in solving the data consistency problem at partition boundaries.

[0115] Preferably, the device further includes a performance adaptive optimizer (not shown in the figure), used to: detect the hardware performance of the terminal device; and dynamically adjust the simplified configuration parameter values ​​and rendering parameters according to the device performance. Its inputs are device performance indicators and user behavior logs, and its output is an optimization strategy instruction, which can be fed back to the scene recognition engine 53 to affect the simplified parameter configuration, or directly trigger the data synchronization controller 56 to perform data preloading.

[0116] Figure 7 This is a flowchart illustrating an embodiment of the building vector graphics processing system of this application, showing the interaction of the various components of the system. The system 700 includes:

[0117] Data processing server 701 is configured to deploy an intelligent simplified device for building vector graphics as described in any embodiment of this application, or to implement the method described in any embodiment of this application. This device serves as the computing core, executing the main processing logic in the method embodiments. Data processing server 701 can be further divided into an application server group (responsible for user authentication and API gateway), a computing server group (deploying the intelligent simplified device), a cache server group (storing hot data and session states), and a message queue server group (processing event streams and task queues).

[0118] The original database 702 is used to persistently store fully detailed building vector data and its explicit topological relationship table. It corresponds to the original data layer in the four-level data system and is the source of data processing in the method embodiment.

[0119] Cache server 703 is used to store project cache and display cache, corresponding to the project cache layer and display cache layer in the four-level data system, serving the project preprocessing and real-time visualization needs in the method embodiment.

[0120] User terminal 704 is the interface through which users interact with the system, corresponding to the terminal view layer in the four-level data architecture. User terminal 704 can include different types such as professional cartographic terminals (containing full-featured editing tools and a high-performance rendering engine), mobile acquisition terminals (containing offline data management and lightweight editing tools), and web browser terminals (containing WebGL-based vector rendering and basic query functions). User actions on the terminal (such as zooming and editing) generate user interaction events.

[0121] The message communication middleware 705 connects the data processing server 701, the raw database 702, the cache server 703, and the user terminal 704. It is responsible for transmitting data change events, user interaction events, processing tasks, calculation results, and cache synchronization instructions, and is a key infrastructure for implementing a dual-driven event and data triggering mechanism.

[0122] System working data flow: User operation generates events on user terminal 704, which are transmitted to the intelligent simplified device in data processing server 701 through message communication middleware 705; the device retrieves data from the original database 702 or queries the cache from cache server 703 as needed; the processing result is updated back to the original database 702 and cache server 703 through data synchronization controller, and the final display data is synchronized to terminal 704 for rendering through middleware 705.

[0123] It should be noted that the execution subject of each step of the method provided in each embodiment of this application can be the same device, or the method can be executed by different devices. For example, the execution subject of steps 110 and 120 can be device 1, and the execution subject of step 130 can be device 2; or the execution subject of step 110 can be device 1, and the execution subject of steps 120 and 130 can be device 2; and so on.

[0124] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0125] Therefore, this application also proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in any embodiment of this application, and provides a computer program product including computer program instructions that, when executed by a processor, implement the aforementioned intelligent simplified method for multi-scene building vector graphics.

[0126] Furthermore, this application also proposes an electronic device (or computing device) including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in any embodiment of this application.

[0127] The following description, in conjunction with the accompanying drawings, further illustrates the implementation effects of the methods, apparatus, and systems of this application.

[0128] Figure 8 This diagram illustrates the principle of adaptive simplification based on gaze focus. Centered on the user's gaze point (estimated by an eye tracker or mouse position), the current screen viewport is divided into three regions: a core focus area, a peripheral transition area, and an outermost background area. The system applies significantly different simplification intensities to buildings in each region: buildings in the focus area retain the highest level of detail, approaching original precision; buildings in the transition area undergo normal display simplification; and buildings in the background area are drastically simplified, even aggregated. By applying differentiated parameter thresholds to different regions and performing smooth transitions at region boundaries, the system, with limited hardware resources, achieves the goal of precisely allocating computational resources to the area of ​​greatest user interest. This creates a visually clear center and a generalized periphery, avoiding the problems of wasted distant details or insufficient near details caused by uniform simplification.

[0129] Figure 9 This diagram illustrates the generation and mapping of multi-scale continuous Level of Detail (LOD) layers, explaining the process of generating and scheduling LOD layers at multiple scales. The left side shows a series of discrete LOD layers pre-generated for the same building, from a fully detailed model (LOD0) to a highly simplified model (LODn), and records the simplification operation sequence (simplification parameter configuration) between layers. The scale axis on the right establishes the mapping relationship between the display scale and the LOD layers. When the user continuously zooms the map, and the current scale (e.g., 1:1500) falls between two pre-calculated LOD layers (e.g., LOD1 corresponds to 1:1000, and LOD2 corresponds to 1:2000), the system does not simply perform linear interpolation between the geometry of the two layers. Instead, based on the pre-recorded simplification parameter configuration values, it dynamically partially executes the operation steps required from LOD1 to LOD2, thereby generating a visually reasonable intermediate geometry in real time. This interpolation method based on operation sequences ensures the continuity and rationality of building outline morphological changes during map scaling, fundamentally eliminating the "geometric jump" phenomenon caused by traditional discrete LOD switching and providing a smooth visual experience.

[0130] Figure 10 This diagram illustrates the distributed collaborative simplification and boundary coordination process. Faced with massive amounts of urban building data, the system divides the entire geographic area into non-overlapping grids (computation partitions 1-9) and assigns data processing tasks for each partition to different computing nodes (Node A, Node B, Node C) within the cluster. The key challenge lies in handling "boundary buildings" that geometrically span multiple partitions. As shown, the data for these boundary buildings is replicated to all relevant computing nodes, ensuring that each node, while processing its local building, also obtains information about related buildings in adjacent partitions for topology coordination. Each node independently and in parallel processes its assigned tasks. After processing, a coordinator node collects the processing results for all boundary buildings from each node. Since nodes may produce slightly different results based on local context, the coordinator runs a consensus algorithm (such as voting, geometric mean, or boundary alignment) to determine the final version for each boundary building. Subsequently, the coordinator broadcasts this final version to all nodes holding copies of that building for unified updates. This mechanism ensures that while enjoying the speed improvements brought by distributed parallel computing, the simplified data for the entire region maintains global topological consistency.

[0131] Figure 11This diagram illustrates the effect of topology collaborative processing on adjacent building adjustments. Using two adjacent buildings as an example, it visually demonstrates how the system achieves topology collaborative processing to maintain topological consistency in the simplified results. The left image shows two adjacent buildings, A and B, before simplification, with a small protrusion on the right side of A. According to the simplification rules, this protrusion might be considered a redundant detail. The right image shows the result after the system performs simplification: the right boundary of building A is moved inward (simplification). If only A is processed, an unexpected gap would appear between A and B. However, in this system, after modifying the boundary of building A, the simplification module immediately notifies the topology relation processor. The topology relation processor queries the topology relation table and identifies that building B and building A are "adjacent" at this boundary. It then automatically triggers a collaborative adjustment task, synchronously translating the relative boundaries of buildings B and A (moving the same vector). As shown in the right image, the two buildings ultimately maintain their original close adjacency, eliminating the graphic gap. This process is transparent to the user and automatically maintains the logical correctness of the spatial data, forming the foundation for supporting high-quality cartographic generalization and spatial analysis.

[0132] Figure 12This diagram illustrates the protection mechanism for inner ring islands in topology collaborative processing. It shows how the system protects composite surface structures containing inner ring islands (such as building courtyards). The building shown consists of an outer ring (main outline) and an inner ring (courtyard outline). The inner and outer ring attributes are explicitly marked in the data model, representing a special type of adjacent building outline topology. When a user performs outer ring editing operations on such composite surfaces (e.g., "pushing edges" to expand the building as a whole), traditional geometric editing might move all vertices simultaneously, causing unintended changes to the position of the inner courtyard. In this system, upon receiving an editing instruction for the outer ring (as shown by the pushing edge vector to the right in the diagram), the geometric editing operator first queries the topological relationships between buildings to check and confirm that the building contains an inner ring. In "inner ring locking mode," the operator applies translation transformations only to the coordinates of the outer ring vertices, while the coordinates of all vertices of the inner ring are forcibly locked and remain unchanged. As shown, after the operation, the building's outer outline expands eastward, but its inner "courtyard" remains fixed in place, seemingly embedded within the building structure. It should be noted that the building outline simplification process alters the average range of the outline boundary, resulting in a "pull edge" operation response. This mechanism effectively prevents damage to the internal structure during simplification or editing of complex surfaces, ensuring the accuracy of geographic feature representation. This is crucial for handling buildings with complex internal structures (such as those with courtyards or atriums). The method and apparatus of this application integrate the overall editing and acquisition process, combining drawing, editing, and simplification into a single system. It supports starting from three-point simplification and using shortcut keys to perform operations such as pushing edges, slotting, adding / deleting vertices, rotating, and merging. It achieves an integrated workflow from acquisition to cartographic generalization, utilizing multiple work scenarios to improve operational efficiency.

[0133] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0134] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A simplified intelligent multi-scene method for building vector graphics, characterized in that, include: Establish a four-level data system in the computer system, comprising a raw data layer, a project cache layer, a display cache layer, and a terminal view layer; The event bus listens for and receives data change events and user interaction events from any layer, assigns processing priorities to different types of events, filters events, and triggers processing when changes exceed a threshold. In response to any triggering event, the current application scenario is identified and the corresponding simplification parameter configuration is dynamically loaded; the simplification parameter configuration is a set of predefined or real-time calculated thresholds or rules used to control the simplification of building outlines; The configuration method is at least one of the following: In response to different building entities, the simplification parameter configuration value is set independently, and simplification is performed separately for different building entities; In response to different building entities, the simplification parameter configuration value is set in association, and simplification is performed simultaneously for different building entities; In response to different nodes, the simplification parameter configuration value is set independently, and each node independently processes the buildings in its respective partition in parallel. The vector graphics of one or more buildings within the scope of the event's impact are simplified. The simplification process includes simplification logic that verifies the overlapping areas between three consecutive judgment units and / or adjacent judgment units according to the simplification parameter configuration. Query the topological relationships between buildings and collaboratively process the outlines of adjacent buildings; The simplification results are synchronously updated to the corresponding level or associated space of the four-level data system within the scope of the event's impact. Change information in the four-level system is updated outward layer by layer to determine which downstream caches need to be rebuilt, rather than being recalculated entirely.

2. The method as described in claim 1, characterized in that, The identification of the current application scenario specifically includes: Extract multidimensional features from the current context, the features including at least one of the following: viewport display scale, user operation mode, and terminal device performance; The extracted features are matched with predefined scene feature templates to determine the scene type; The scenario types include at least one of the following: real-time display scenario, geographic analysis scenario, and cartographic integration scenario.

3. The method as described in claim 1, characterized in that, The simplification logic for verifying the overlapping regions between adjacent judgment units according to the simplification parameter configuration specifically includes: For the outer ring outline of the building, starting from the initial vertex, construct the first judgment unit with three consecutive vertices along the vector direction; Slide a vertex to construct an adjacent second judgment unit; Calculate the geometric overlap region between the first judgment unit and the second judgment unit; When the overlapping region meets the conditions in the simplification parameter configuration of the current scene, boundary simplification is performed on the corresponding protruding or concave part; Repeat the above process until the outer ring contour has been traversed.

4. The method as described in claim 1, characterized in that, The conditions in the simplification parameter configuration include at least one of the following: the area of ​​the overlapping region is less than the area threshold, the length of the short side of the judgment unit is less than the short side threshold, and the length of the long side of the judgment unit is less than the long side threshold.

5. The method as described in claim 1, characterized in that, The method also includes a step of adaptive simplification of gaze focus: Obtain the user's gaze point position on the screen; Centered on the fixation point, the current viewport is divided into a focal area, a transition area, and a background area; Different simplified parameter configuration values ​​are applied to buildings in different areas.

6. The method as described in claim 1, characterized in that, The method also includes a step of multi-scale continuous detail processing: Pre-generate multiple discrete levels of detail for the building; Establish a continuous mapping relationship between the display scale and the level of detail; When the user zooms in on the map, intermediate geometry is dynamically generated by interpolation based on the mapping relationship and the simplified parameter configuration values.

7. The method as described in claim 1, characterized in that, The query of the topological relationships between buildings, and the collaborative processing of the outlines of adjacent buildings, specifically includes: When the boundary of a single building moves due to simplification, the topology table is queried to obtain adjacent buildings; Perform coordinated translation adjustments on the corresponding boundaries of adjacent buildings that are related to the moving boundary.

8. The method as described in claim 1, characterized in that, The coordinated processing of the outlines of adjacent buildings also includes the inner ring protection of the composite surface structure: When performing outer ring simplification or editing operations on a building containing an inner ring outline, the geometric coordinates of the inner ring outline are automatically locked and remain unchanged.

9. A building vector graphics processing system, characterized in that, include: A data processing server, configured to execute the method according to any one of claims 1 to 8; The original database stores building data and topological relationships; Cache server, storing project cache and display cache; One or more user terminals; The message communication middleware connects the data processing server, the raw database, the cache server, and the user terminal.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 8.

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