Guide method and system based on 3D visualization technology

Abstract

The invention discloses a navigation method and system based on a 3D visualization technology, and the method comprises the steps: obtaining a current position of a user in an exhibition hall and a historical exhibition path of the user in the exhibition hall; predicting a current exhibition path of the user according to the current position and the historical exhibition path; determining a next position where the user arrives in the current exhibition path; acquiring three-dimensional scene data of a next position, and constructing three-dimensional navigation information corresponding to the three-dimensional scene data; and when the distance between the current position and the next position is smaller than a preset threshold value, switching the currently displayed guide information into three-dimensional guide information. The problems that in a traditional navigation system, a mobile terminal needs to load a large amount of three-dimensional scene data in real time, so that equipment load is too heavy, and system response lags behind are solved, and three-dimensional navigation information is displayed in time.

Description

Technical Field

[0001] The present application relates to the field of terminal technology, and in particular to a navigation method and system based on 3D visualization technology. Background Art

[0002] With the development of digital technology, intelligent guide systems have been widely used in museums, art galleries and other exhibition halls. Compared with traditional manual explanations and flat guide maps, intelligent guide systems can provide visitors with a more personalized and immersive visiting experience, and have become an important means for modern exhibition halls to improve service quality.

[0003] In the related technology, the existing 3D visualization guide system usually adopts the method of panoramic loading, that is, the 3D scene data of the entire exhibition hall is loaded at one time when the user enters the exhibition hall. The system will navigate in the pre-loaded 3D scene according to the real-time location of the user, and then display the 3D guide information display of the corresponding location.

[0004] However, this panoramic loading 3D navigation method has obvious defects. When the exhibition hall is large and the number of exhibits is large, the 3D scene data of the entire exhibition hall always resides in the memory of the mobile terminal. As users move around the exhibition hall, the system needs to calculate the relative position of the user and the exhibits, update the scene display range, process interactive responses, etc. in real time, which occupies most of the processing resources of the mobile terminal, making the mobile terminal device overloaded, the system response delayed, and affecting the timely display of 3D navigation information. Summary of the invention

[0005] The present application provides a navigation method and system based on 3D visualization technology, which is used to solve the problem that the three-dimensional navigation method with panoramic loading occupies most of the processing resources of the mobile terminal, causing the mobile terminal device to be overloaded, and realizes the timely display of three-dimensional navigation information.

[0006] In a first aspect of the present application, a navigation method based on 3D visualization technology is provided, which is applied to a mobile terminal. The method comprises: Obtain the current position of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; predict the current exhibition path of the user based on the current position and the historical exhibition path; determine the next position to be reached by the user in the current exhibition path; obtain the three-dimensional scene data of the next position, and construct three-dimensional guide information corresponding to the three-dimensional scene data; when the distance between the current position and the next position is less than a preset threshold, switch the currently displayed guide information to the three-dimensional guide information.

[0007] Optionally, the user's current exhibition path is predicted based on the current position and the historical exhibition path, specifically including: obtaining the coordinates of each position in the historical exhibition path and the arrival time of the user at each position; performing feature extraction on the coordinates and arrival time to obtain the user's motion feature data; inputting the motion feature data into a prediction model, and outputting the current exhibition path.

[0008] Optionally, after predicting the user's current exhibition path according to the current location and the historical exhibition paths, the method further includes: The predicted path data is corrected by the first calculation formula; the first calculation formula is: in, is the predicted path error, P j is the discretized point coordinate of the current exhibition path during the calibration process, f(F,W,b,t j ) is the position point prediction function, F is the user's motion feature, W, b are the model parameters of the prediction model; is the smoothness constraint of the current exhibition path, λ1, λ2 are weight parameters, P(t) is the path function, is the second-order derivative of the path function, is the third-order derivative of the path function; is the collision detection constraint, C j (P j ,B) is P j The minimum distance to the obstacle boundary set B, P j is the discretized point coordinate of the current exhibition path during the correction process, d threshold is the safety distance threshold, and λ3 is the weight parameter.

[0009] Optionally, after determining the next location to be reached by the user in the current exhibition path, the method further includes: Determine whether the current position is within the preset tolerance range of the current exhibition path; if the current position is not within the preset tolerance range of the current exhibition path, re-predict and re-determine the next position.

[0010] Optionally, obtaining the three-dimensional scene data of the next position and constructing the three-dimensional navigation information corresponding to the three-dimensional scene data specifically includes: Based on the three-dimensional scene data of the next position, three-dimensional navigation information corresponding to the three-dimensional scene data is constructed through a preset rendering method; the visual angle data of the mobile terminal is obtained, and the three-dimensional navigation information is adjusted according to the visual angle data.

[0011] Optionally, based on the three-dimensional scene data of the next position, three-dimensional navigation information corresponding to the three-dimensional scene data is constructed by a preset rendering method, specifically including: The three-dimensional scene data is divided into first data and second data, wherein the fineness of the first data is higher than that of the second data; when the distance between the current position and the next position is greater than a preset distance, the second data is rendered to generate a visual navigation view of the target area, where the target area is the area where the next position is located; when the distance is less than or equal to the preset distance, the first data is rendered to generate a visual navigation view of the target area.

[0012] Optionally, a navigation method based on 3D visualization technology is applied to a mobile terminal, the method also including: collecting an environmental image of the current position through a camera of the mobile terminal, and extracting environmental feature information from the environmental image; obtaining three-dimensional scene data of the current position, and fusing the three-dimensional scene data of the current position with the environmental image according to the environmental feature information to generate an augmented reality scene; superimposing and displaying interactive navigation information on a display screen of the mobile terminal according to the augmented reality scene; and updating and displaying corresponding three-dimensional navigation information on the display screen in response to operation instructions input by the user for the interactive navigation information.

[0013] In a second aspect of the present application, a navigation system based on 3D visualization technology is provided, comprising: The acquisition module is used to acquire the current position of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; A prediction module, used to predict the user's current exhibition path based on the current location and historical exhibition paths; A determination module, used to determine the next location that the user reaches in the current exhibition path; The construction module is used to obtain the three-dimensional scene data of the next position and construct the three-dimensional navigation information corresponding to the three-dimensional scene data; the switching module is used to switch the currently displayed navigation information to the three-dimensional navigation information when the distance between the current position and the next position is less than a preset threshold.

[0014] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any one of the methods described above.

[0015] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any of the methods described above is executed.

[0016] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Through the user's current location and historical exhibition path, the user's exhibition trajectory is predicted and the 3D scene data of the next location is preloaded. When the user approaches the target booth, seamless switching of the guide information is achieved. This effectively solves the problem that in the traditional guide system, the mobile terminal needs to load a large amount of 3D scene data in real time, resulting in excessive equipment load and delayed response, and realizes the timely display of 3D guide information.

[0017] 2. By extracting the user's historical location coordinates and arrival time to establish a prediction model, we can deeply analyze the user's movement patterns and visiting habits, thereby accurately predicting the user's exhibition path. At the same time, based on the user's current location, the predicted current exhibition path is detected in real time. If the user deviates from the current path, the path is re-predicted to display the guide information of the next location in a timely manner. It makes full use of the user's personalized behavior data, improves the accuracy of path prediction, provides more personalized guide services for different types of visitors, and effectively optimizes the intelligence level and service quality of the guide system.

[0018] 3. By adopting a hierarchical rendering mechanism for 3D scene data and combining it with real-time adjustment of the visual angle of the mobile terminal, the system can intelligently switch scene data of different fineness for rendering according to the distance between the user and the next location. When the distance is far, low-precision data is rendered, and when the distance is close, it switches to high-precision data. This not only ensures the continuity and immersion of the navigation effect, but also effectively solves the problem of always loading high-precision 3D models in traditional navigation systems, resulting in high device performance consumption and slow response, and realizes the rational use of mobile terminal resources and dynamic optimization of the navigation experience.

[0019] 4. By intelligently integrating the real-time collected environmental images with the 3D scene data and providing a dynamic update mechanism for interactive guide information, the system achieves a seamless combination of real environment and virtual information. The application of this augmented reality technology effectively solves the problems of virtual-real separation and poor interactivity in traditional guide systems, allowing users to intuitively see the guide information superimposed on the actual environment and obtain the required 3D display content through simple operating instructions, which enhances the immersiveness and interactive experience of the guide system and makes the presentation of exhibition content more vivid and intuitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flowchart of a navigation method based on 3D visualization technology in an embodiment of the present application; Figure 2 is another flowchart of a navigation method based on 3D visualization technology in an embodiment of the present application; Figure 3It is a structural schematic diagram of a navigation system based on 3D visualization technology in an embodiment of the present application; Figure 4 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application.

[0021] Explanation of the accompanying drawings: 301, acquisition module; 302, prediction module; 303, determination module; 304, construction module; 305, switching module; 306, correction module; 307, judgment module; 308, interaction module; 401, processor; 402, communication bus; 403, user interface; 404, network interface; 405, memory. DETAILED DESCRIPTION

[0022] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0023] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0024] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0025] Figure 1 It is a flow chart of a navigation method based on 3D visualization technology in an embodiment of the present application.

[0026] See also Figure 1 , is a navigation method based on 3D visualization technology in an embodiment of the present application, applied to a mobile terminal, the method comprising: S101, obtaining the current location of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; Detect the positioning methods supported by the terminal device. In indoor exhibition hall environments, Bluetooth beacon positioning is preferred, followed by WiFi positioning, and finally GPS positioning. The user's current location coordinates can be obtained through one or more methods.

[0027] After obtaining the user's current location coordinates, the location coordinates are mapped to the floor plan of the exhibition hall to obtain the user's specific location information in the exhibition hall. A standard data structure is generated for each location coordinate point, including user ID, location coordinates and timestamp information. These location point data are stored in two locations at the same time: on the local mobile terminal, the system uses key-value pair storage to store the location point sequence with "visitPath" as the key name; on the server side, the system uses relational database storage to establish an association table between user ID and location points to ensure the persistence of data.

[0028] When obtaining the historical exhibition path, the system first reads the historical path data from the local storage of the mobile terminal, and obtains all historical path records corresponding to the user ID from the server. The system merges the local data and the server data, and sorts all the location points in time according to the timestamp to form a complete historical path sequence. To ensure data quality, the system will perform data cleaning and optimization on the acquired historical path sequence. By setting the valid range of coordinates, invalid positioning points outside the exhibition hall are filtered out; by comparing the time and space distances of adjacent location points, duplicate location points caused by positioning errors are removed; at the same time, the path is smoothed to eliminate path jitter caused by positioning noise.

[0029] Finally, the system starts the timer and executes the location update operation in a loop at intervals of 1 second. During each update, the system obtains the user's latest location coordinates, saves them as new location point records, and updates the current location mark in real time on the user interface. The new location point data is synchronously updated to the local storage and server database to ensure data consistency and integrity.

[0030] S102, obtaining the coordinates of each location in the historical exhibition path and the arrival time of the user at each location; The spatial coordinates and time series information of each historical location point are extracted from the historical exhibition path. The spatial coordinates are represented by a three-dimensional coordinate system (x, y, z), where x and y represent the plane position of the exhibition hall and z represents the height of the floor. The time series information includes the arrival timestamp (accurate to milliseconds) and the length of stay. The length of stay is calculated based on the time difference between two adjacent historical location points.

[0031] Verify the validity of the extracted coordinates and time data. Check whether the coordinates are within the valid range of the exhibition hall; verify whether the time series is continuous and logical; verify whether the distance between adjacent location points is within the normal movement speed range of personnel; confirm whether the length of stay is reasonable. Mark or correct the data that does not meet the verification rules.

[0032] Convert the verified location-time association data into a standard format. Specifically, the timestamp is converted into a standard time format (such as YYYY-MM-DD HH:mm:ss.SSS); the coordinate value is uniformly retained to two decimal places; the exhibition area number and exhibit number are converted into corresponding semantic descriptions; and path feature data such as moving speed, acceleration, and steering angle are calculated and added.

[0033] S103, extracting features from the coordinates and arrival time to obtain motion feature data of the user; The spatial displacement vector is obtained by calculating the Euclidean distance between adjacent position points, and the time interval is obtained by calculating the difference between adjacent time points. Based on the spatial displacement vector and time interval, the instantaneous movement speed and movement direction θ of the user at each position point are calculated (obtained by the angle between the displacement vector and the reference coordinate system), and the speed sequence and direction sequence are obtained. The speed sequence and direction sequence are statistically analyzed to extract features such as the average speed v_avg, speed standard deviation v_std, direction change frequency dir_change_freq, and spatial distribution range of the position point coord_range, and the user's movement feature vector F = [v_avg, v_std, dir_change_freq, coord_range] is obtained.

[0034] S104: Input the motion feature data into a prediction model, and output the current exhibition path.

[0035] The system collects user motion data samples. Each sample contains the user's motion feature vector at the current moment and the corresponding actual position coordinates at the next moment. The collected sample data needs to be preprocessed by the system. The preprocessing process includes two main steps: data cleaning and data standardization. In the data cleaning stage, a reasonable speed threshold range must be set first, and data outside this range must be marked as outliers and removed. At the same time, data points whose position coordinates obviously deviate from the normal activity range and samples with missing data also need to be removed. In order to eliminate noise interference in the data, the sliding window method is used to smooth the position coordinate sequence, and the median filtering technology is used to eliminate mutation points to ensure the quality of the data.

[0036] In the data standardization stage, each component of the motion feature vector needs to be standardized. The z-score standardization method can be used for standardization. The specific calculation formula is: Among them, F' represents the standardized eigenvalue, F represents the original eigenvalue, μ represents the mean of this feature, and σ represents the standard deviation of this feature. Through the standardization process, the motion feature components with different dimensions can be mapped to the same scale range, which is conducive to improving the stability of model training and the accuracy of prediction.

[0037] After completing the data preprocessing, the processed dataset is randomly divided into a training set and a test set according to the ratio of 8:2. Among them, 80% of the samples are used for model training, and the remaining 20% of the samples are used for evaluating the model performance. This division ratio can ensure both sufficient data for model training and an appropriate amount of data for testing the generalization ability of the model.

[0038] After the dataset is divided, a prediction model is constructed using the training set, and the model performance is evaluated through the test set. First, according to the requirements of motion feature and position prediction, a suitable prediction model is selected. For example, a regression model (such as linear regression, support vector regression, decision tree regression, etc.) is suitable for scenarios where continuous position coordinates need to be predicted, or a time series model (such as long short-term memory network LSTM, gated recurrent unit GRU, etc.) is suitable for trajectory prediction tasks based on time series. Then, the motion feature vectors in the training set are used as the input of the model, and the actual position coordinates at the next moment are used as the target output. The model training is completed by optimizing the objective function (such as mean squared error), and finally an accurate prediction model is obtained. Finally, the performance of the model is evaluated using the test set. The mean squared error (MSE) is used to measure the average squared error between the predicted value and the true value. The smaller the error, the more accurate the prediction; the mean absolute error (MAE) is used to measure the average absolute deviation between the predicted value and the true value to reflect the prediction deviation of the model; the coefficient of determination (R 2 ) is used to evaluate the goodness of fit of the model. The closer R 2 is to 1, the better the prediction effect of the model. Through the above evaluation indicators, the accuracy and generalization ability of the model can be comprehensively judged to ensure that the model can well adapt to unseen data.

[0039] The motion feature vector is input into the trained prediction model. The model outputs the complete motion path (i.e., the exhibition path) of the user in the future according to the input user motion features. For example, when the motion features of the user are [v_avg = 1.2 m / s, v_std = 0.3 m / s, dir_change_freq = 0.2 times / s, coord_range = (5, 15)], the model may predict the future motion trajectory of the user as a continuous path curve, represented as a sequence of coordinate points [(x1, y1), (x2, y2),...,(x n , y n)] or a three-dimensional path [(x1,y1,z1),(x2,y2,z2),...,(x n ,y n ,z n )].

[0040] S105, determining the next location reached by the user in the current exhibition path; The exhibition path output by the prediction model is usually a continuous sequence of coordinate points, such as [(x1,y1),(x2,y2),...,(x n ,y n )] or a three-dimensional path [(x1,y1,z1),(x2,y2,z2),...,(x n ,y n ,z n )], indicating the future motion trajectory of the user. In one possible case, by setting a time interval Δt (such as 1 second or 0.5 second), the next point P corresponding to the time interval is selected from the path sequence. next =(x next ,y next ,z next ) and use the selected coordinates as the coordinates of the user's next location.

[0041] After selecting the coordinates of the next location, a rationality check is required to ensure that the prediction results conform to the user's movement patterns and scene restrictions. Check whether the distance from the user's current location to the next location is consistent with the average speed and the set time interval Δt to ensure that the moving distance is reasonable.

[0042] S106, obtaining three-dimensional scene data of the next position, and constructing three-dimensional navigation information corresponding to the three-dimensional scene data; According to the next location that the user may reach, the three-dimensional scene data associated with the location is retrieved from the database of the exhibition system, including geometric information (such as exhibits, three-dimensional models of scene structures), texture information (such as materials and surface mapping), environmental information (such as lighting and shadow effects), and detailed information of exhibits (such as names, introductions, and interactive functions). Subsequently, the three-dimensional navigation information is constructed in combination with the user's navigation needs. Specifically, the system generates a real-time rendered three-dimensional view based on the user's position and viewing direction, annotates the exhibits within the user's field of view, and attaches the exhibits' names, introductions, or interactive options. At the same time, navigation prompts (such as ground arrows or floating markers) are embedded in the scene to guide the user to the next destination.

[0043] S107: When the distance between the current position and the next position is less than a preset threshold, the currently displayed navigation information is switched to three-dimensional navigation information.

[0044] When the distance between the user's current location and the next location is less than the preset threshold, that is, within a certain distance before the user reaches the next location, the system will automatically switch the currently displayed navigation information to the three-dimensional navigation information corresponding to the next location to achieve a smooth navigation experience and accurate scene switching. Specifically, the system calculates the spatial distance between the two points by monitoring the distance between the user's current location and the next location in real time. The spatial distance can be a straight-line distance or a path distance. When the spatial distance is less than the preset threshold (such as a few meters or a reasonable distance range in a specific scene), the system believes that the user has approached the next location or reached the next location. At this time, the rendering of the current navigation information is stopped and the newly generated three-dimensional navigation information is switched to the current display content. During the switching process, the system will dynamically load the three-dimensional scene data of the next location and adjust the viewing angle parameters (such as viewing direction, viewing distance, etc.) to ensure that the user's viewpoint matches the actual scene of the next location. At the same time, the exhibit annotations, navigation prompts and interactive options will be updated in the navigation information, so that users can clearly understand the exhibition content of the current location and obtain detailed information related to the scene. Users can seamlessly transition from the navigation information of one location to the navigation information of the next location during the movement.

[0045] Optional, in Figure 1 After step S106 of the illustrated embodiment, the following steps may be performed: Specifically, the predicted path data is corrected by a first calculation formula; the first calculation formula is: in, is the predicted path error, P j is the discretized point coordinate of the current exhibition path during the calibration process, f(F,W,b,t j ) is the position point prediction function, F is the user's motion feature, W, b is the model parameter of the prediction model, t j is the time variable; is the smoothness constraint of the current exhibition path, λ1, λ2 are weight parameters, P(t) is the path function, is the second-order derivative of the path function, is the third-order derivative of the path function; is the collision detection constraint, C j (P j ,B) is P j The minimum distance to the obstacle boundary set B, P j is the discretized point coordinate of the current exhibition path during the correction process, d threshold is the safety distance threshold, and λ3 is the weight parameter. j (P j,B) is less than the threshold d threshold , a penalty term is introduced to force the path to stay away from obstacles.

[0046] The core of the first formula is a multi-objective optimization problem. The goal is to generate a smooth, safe path that conforms to the historical movement characteristics through constraints such as path prediction, smoothing, and collision detection. The correction process of the formula is mainly to minimize the loss of each item in the objective function by gradually optimizing the position of the position point. The path prediction error part makes the points after discretization of the current exhibition path fit the output of the prediction model as much as possible during the correction process to ensure that the path conforms to the historical movement characteristics. If the position point deviates too much from the prediction model, the optimization process will adjust the position point P j position to make it closer to the predicted path.

[0047] The smoothness constraint is divided into acceleration term and rate of change term, where the acceleration term By limiting the change of the second-order derivative (acceleration), the path is prevented from having abrupt acceleration or deceleration, ensuring the smoothness of the path. If the acceleration change between the position points is too large, the optimization process will adjust the position of the position point to reduce The magnitude of the rate of change Further limit the rate of change of acceleration to avoid drastic dynamic changes in the path in a short period of time. If the rate of change of acceleration of the path is large, the optimization process will adjust the position points to reduce The value of .

[0048] Collision detection constraints ensure that the position point maintains a safe distance d from obstacles threshold , to prevent the location point from being too close to or colliding with obstacles. If a location point is too close to an obstacle, the optimization algorithm will adjust the location point to keep it away from the obstacle.

[0049] Figure 2 This is another flowchart of a navigation method based on 3D visualization technology in an embodiment of the present application.

[0050] See also Figure 2 , is a navigation method based on 3D visualization technology in an embodiment of the present application, applied to a mobile terminal, the method comprising: S201, obtaining the current location of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; S202, predicting the user's current exhibition path according to the current location and historical exhibition paths; S203, determining the next location reached by the user in the current exhibition path; The details of steps S201 to S203 may refer to steps S101 to S105 and will not be described again here.

[0051] S204, determining whether the current position is within a preset tolerance range of the current exhibition path; By determining whether the user's current location is within the preset tolerance range of the current exhibition path, it is possible to determine whether the user has deviated from the predicted exhibition path, thereby providing a basis for subsequent adjustment of the navigation strategy or updating of the user path. The preset tolerance range is a tolerance value set based on the exhibition scene requirements, which usually includes dimensions such as spatial distance tolerance, direction tolerance, and time tolerance. In this embodiment, the spatial distance tolerance is used to determine whether the user's actual movement trajectory deviates from the system's predicted path.

[0052] S205: if the current position is not within the preset tolerance range of the current exhibition path, re-predict and re-determine the next position; When the system detects that the user's current location is not within the preset tolerance range of the current exhibition path, it means that the user's actual movement trajectory deviates from the system's predicted path. At this time, the system first needs to re-predict the path, re-analyze the user's exhibition behavior pattern based on the user's current location and historical exhibition path, and generate a new exhibition path. Subsequently, based on the new exhibition path, the system re-determines the next location that the user is about to arrive at to update the navigation information and guidance strategy.

[0053] S206, constructing three-dimensional navigation information corresponding to the three-dimensional scene data by a preset rendering method based on the three-dimensional scene data of the next position; Specifically, the three-dimensional scene data is divided into first data and second data, wherein the fineness of the first data is higher than that of the second data; when the distance between the current position and the next position is greater than a preset distance, the second data is rendered to generate a visual navigation view of the target area, where the target area is the area where the next position is located; when the distance is less than or equal to the preset distance, the first data is rendered to generate a visual navigation view of the target area.

[0054] Among them, the system needs to perform fine-grained layering processing on the 3D scene data of the next location. This process divides the 3D scene data into two data layers with different accuracy levels. The first data layer contains high-precision 3D model data, which includes detailed building exterior textures, precise geometric structure information, complete interior layout details, high-resolution material maps, and fine decorative elements. The second data layer contains low-precision simplified model data, which only retains simplified building outlines, basic geometric shapes, rough spatial layouts, low-resolution textures, and omits minor detail elements.

[0055] Next, the system will calculate and monitor the distance between the user's current location and the target next location in real time. This process requires the use of GPS or other positioning technology to obtain the precise coordinates of the current location and compare them with the pre-stored coordinates of the next location. The system will compare the calculated distance value with the preset distance threshold to determine which rendering strategy to use.

[0056] When the distance between the user and the next location is greater than the preset distance threshold, the system will enable the long-distance rendering strategy. In this case, the system will select the low-precision data of the second data layer for rendering to generate a visual navigation view of the target area. This view mainly shows the overall outline and basic spatial structure of the target area. Although the details are relatively few, it can significantly reduce the amount of data processing and ensure the smoothness of system operation. This rendering strategy is suitable for scenarios where users need to have an overall understanding of the target area and grasp the direction.

[0057] When the distance between the user and the next location is less than or equal to the preset distance threshold, the system switches to the close-range rendering strategy. At this point, the system loads the high-precision data of the first data layer for rendering, generating a visual navigation view with rich details. This view shows the complete architectural features, fine environmental details, and complete material effects of the target area, providing users with an immersive visual experience. This rendering strategy is suitable for scenarios where users need to carefully observe and understand the specific details of the target area.

[0058] In order to ensure the stable operation of the system and a good user experience, optimization is required in many aspects. In terms of data loading, the system adopts a preloading mechanism and a progressive loading strategy, and establishes an effective data caching mechanism to optimize data transmission efficiency. In terms of rendering performance, the system uses LOD (Level of Detail) technology and frustum clipping to reasonably allocate system resources and ensure the efficiency of the rendering process. In terms of visual effects, the system achieves a smooth hierarchical transition effect, optimizes the processing of lighting and shadows, and ensures the stability and continuity of the picture.

[0059] The system also needs to perform continuous parameter tuning and performance monitoring. By adjusting the distance threshold, optimizing the data stratification strategy, adjusting the rendering parameter configuration, etc. according to the actual application scenario, the system's operating effect is continuously improved. At the same time, the system will monitor resource usage in real time, track rendering frame rate changes, record data loading time, analyze user interaction responses and other indicators to ensure that the system always maintains the best operating state.

[0060] S207, obtaining visual angle data of the mobile terminal, and adjusting the three-dimensional navigation information according to the visual angle data; Visual angle data is usually collected by sensors of user devices (such as mobile phones, tablets, etc.). These sensors include gyroscopes, accelerometers, and magnetometers, which are used to calculate the device's direction and posture information in real time, namely the device's pitch angle (Pitch), yaw angle (Yaw), and roll angle (Roll) in three-dimensional space. These angle data describe the direction of the user's line of sight, such as whether the user is currently moving his or her line of sight up, down, or left or right.

[0061] Based on the acquired visual angle data, the system will dynamically adjust the display content and viewing angle of the 3D navigation information to ensure that the user's interaction with the 3D scene is always consistent with their current viewing direction. Specifically, when the user turns the device or changes the line of sight, the system will recalculate the user's observation point and viewing angle range, adjust the view rendered by the 3D scene, and update the exhibits and information visible within the user's line of sight in real time. For example, if the user tilts or rotates the device in a certain direction, the system will shift the user's perspective to the corresponding direction in the 3D scene and load the 3D model and annotation information of the exhibits in that direction; if the user turns to other areas, the system will hide the previously invisible exhibit information and display new related content. In addition, changes in visual angle can also trigger the recalculation of dynamic navigation prompts, such as adjusting the direction of arrows or path guides to always point to the user's next location.

[0062] S208: When the distance between the current position and the next position is less than a preset threshold, the currently displayed navigation information is switched to three-dimensional navigation information.

[0063] For details of step S208, please refer to step S107, which will not be described in detail here.

[0064] Optionally, in the above embodiment, a navigation method based on 3D visualization technology further includes: The environmental image of the current position is collected through the camera of the mobile terminal, and environmental feature information is extracted from the environmental image; the three-dimensional scene data of the current position is obtained, and the three-dimensional scene data of the current position is integrated with the environmental image according to the environmental feature information to generate an augmented reality scene; the interactive guide information is superimposed and displayed on the display screen of the mobile terminal according to the augmented reality scene; in response to the operation instructions input by the user for the interactive guide information, the corresponding three-dimensional guide information is updated and displayed on the display screen.

[0065] When a user uses a mobile device, the system first collects image data of the current environment in real time through the mobile phone camera. The system processes the collected images in real time and uses computer vision algorithms to extract key environmental feature information. These feature information include significant feature points in the image, object edges, texture features, etc. Specifically, the system uses feature detection algorithms such as SIFT or SURF to identify key points in the image, and uses edge detection algorithms to extract the contour information of objects in the scene. It also uses deep learning models to perform scene segmentation and target recognition.

[0066] The system accesses the pre-stored 3D scene database to obtain the 3D model data corresponding to the current position. These 3D data may come from a pre-modeled 3D map, real-time depth sensor acquisition, or a scene model dynamically reconstructed through SLAM technology. The system then aligns and fuses the extracted 2D environmental feature information with the 3D scene data. This process first requires determining the correspondence between the image and the 3D model through feature point matching, and then calculating the precise position and orientation of the camera in 3D space through a pose estimation algorithm. The system also analyzes the lighting conditions of the scene to ensure that the rendering effect of the virtual content is consistent with the real environment lighting.

[0067] Based on the results of the fusion processing, the system will overlay various virtual information on the real scene image to generate a complete augmented reality scene. These virtual information include annotations of buildings, navigation path instructions, points of interest markers, 3D virtual models and other content. The system will intelligently determine the placement of this information based on the results of scene understanding to ensure that they are clearly visible and do not block important real-life content. At the same time, the system will take into account the screen size and display characteristics of mobile devices to optimize the adaptive layout of information.

[0068] The system provides a variety of interactive methods for users to operate, including touch screen clicks, gesture recognition, and voice commands. When users perform interactive operations, the system will respond to the user's instructions in real time. For example, when a user clicks a point of interest mark, the system will display detailed information about the location; when a user performs a gesture to zoom, the system will adjust the display ratio of the virtual content accordingly; when a user requests navigation, the system will plan and display the optimal path. All these interactive responses need to ensure real-time and smoothness.

[0069] See also Figure 3 , is a structural diagram of a navigation system based on 3D visualization technology provided in an embodiment of the present application, a navigation system 300 based on 3D visualization technology specifically includes: The acquisition module 301 is used to acquire the current position of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; Prediction module 302, used to predict the user's current exhibition path based on the current location and historical exhibition paths; A determination module 303 is used to determine the next location that the user reaches in the current exhibition path; The construction module 304 is used to obtain the three-dimensional scene data of the next position and construct the three-dimensional navigation information corresponding to the three-dimensional scene data; the switching module 305 is used to switch the currently displayed navigation information to the three-dimensional navigation information when the distance between the current position and the next position is less than a preset threshold.

[0070] Optionally, the prediction module 302 is specifically configured to: The coordinates of each position in the historical exhibition path and the arrival time of the user at each position are obtained; the coordinates and the arrival time are feature extracted to obtain the user's motion feature data; the motion feature data is input into the prediction model, and the current exhibition path is output.

[0071] Optionally, the construction module 304 is specifically used to: Based on the three-dimensional scene data of the next position, three-dimensional navigation information corresponding to the three-dimensional scene data is constructed through a preset rendering method; the visual angle data of the mobile terminal is obtained, and the three-dimensional navigation information is adjusted according to the visual angle data.

[0072] Optionally, the construction module 304 is further specifically configured to: The three-dimensional scene data is divided into first data and second data, wherein the fineness of the first data is higher than that of the second data; when the distance between the current position and the next position is greater than a preset distance, the second data is rendered to generate a visual navigation view of the target area, where the target area is the area where the next position is located; when the distance is less than or equal to the preset distance, the first data is rendered to generate a visual navigation view of the target area.

[0073] Optionally, the system further includes a correction module 306, specifically configured to: Correcting the predicted path data using a first calculation formula; The first calculation formula is: in, is the predicted path error, P j is the discretized point coordinate of the current exhibition path during the calibration process, f(F,W,b,t j ) is the position point prediction function, F is the user's motion feature, W, b are the model parameters of the prediction model; is the smoothness constraint of the current exhibition path, λ1, λ2 are weight parameters, P(t) is the path function, is the second-order derivative of the path function, is the third-order derivative of the path function; is the collision detection constraint, C j (P j ,B) is P j The minimum distance to the obstacle boundary set B, P j is the discretized point coordinate of the current exhibition path during the correction process, d threshold is the safety distance threshold, and λ3 is the weight parameter.

[0074] Optionally, the system further includes a judgment module 307, which is specifically used to: Determine whether the current position is within the preset tolerance range of the current exhibition path; if the current position is not within the preset tolerance range of the current exhibition path, re-predict and re-determine the next position.

[0075] Optionally, the system further includes an interaction module 308, which is specifically used to: Acquire three-dimensional scene data of the current position, fuse the three-dimensional scene data of the current position with the environmental image according to the environmental feature information, and generate an augmented reality scene; overlay and display interactive guide information on the display screen of the mobile terminal according to the augmented reality scene; and update and display the corresponding three-dimensional guide information on the display screen in response to the operation instructions input by the user for the interactive guide information.

[0076] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0077] This embodiment also discloses an electronic device, referring to Figure 4 The electronic device may include: at least one processor 401 , at least one communication bus 402 , a user interface 403 , a network interface 404 , and at least one memory 405 .

[0078] The communication bus 402 is used to realize the connection and communication between these components.

[0079] The user interface 403 may include a display screen (Display) and a camera (Camera), and the optional user interface 403 may also include a standard wired interface and a wireless interface.

[0080] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0081] Among them, the processor 401 may include one or more processing cores. The processor 401 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the processor 401 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 401 can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 401, and it can be implemented by a single chip.

[0082] Among them, the memory 405 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 405 may optionally be at least one storage device located away from the aforementioned processor 401. As Figure 4 As shown, the memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a navigation method based on 3D visualization technology.

[0083] exist Figure 4 In the electronic device shown, the user interface 403 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 401 can be used to call an application program storing a navigation method based on 3D visualization technology in the memory 405. When executed by one or more processors 401, the electronic device executes one or more methods in the above-mentioned embodiments.

[0084] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0085] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0086] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0087] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0088] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0089] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory 405. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory 405 and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory 405 includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk.

[0090] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A navigation method based on 3D visualization technology, characterized in that: Applied to a mobile terminal, the method comprises: Obtaining the current location of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; Predicting the current exhibition path of the user according to the current location and the historical exhibition path; Determine the next location reached by the user in the current exhibition path; Acquire the three-dimensional scene data of the next position, and construct three-dimensional navigation information corresponding to the three-dimensional scene data; When the distance between the current position and the next position is less than a preset threshold, the currently displayed navigation information is switched to the three-dimensional navigation information.

2. The method according to claim 1, characterized in that The predicting the current exhibition path of the user according to the current location and the historical exhibition path specifically includes: Obtaining the coordinates of each location in the historical exhibition path and the arrival time of the user at each location; Performing feature extraction on the coordinates and the arrival time to obtain motion feature data of the user; The motion feature data is input into a prediction model, and the current exhibition path is output.

3. The method according to claim 1, characterized in that After predicting the current exhibition path of the user according to the current location and the historical exhibition path, the method further includes: Correcting the predicted path data using a first calculation formula; The first calculation formula is: in, is the predicted path error, P j is the discretized point coordinate of the current exhibition path in the calibration process, f(F,W,b,t j ) is a position point prediction function, F is the motion feature of the user, W, b are model parameters of the prediction model; is the smoothness constraint of the current exhibition path, λ1, λ2 are weight parameters, P(t) is the path function, is the second-order derivative of the path function, is the third-order derivative of the path function; is the collision detection constraint, C j (P j ,B) is P j The minimum distance to the obstacle boundary set B, P j is the discretized point coordinate of the current exhibition path in the correction process, d threshold is the safety distance threshold, and λ3 is the weight parameter.

4. The method according to claim 1, characterized in that: After determining the next location reached by the user in the current exhibition path, the method further includes: Determining whether the current position is within a preset tolerance range of the current exhibition path; If the current position is not within the preset tolerance range of the current exhibition path, a new prediction is performed and a next position is re-determined.

5. The method according to claim 1, characterized in that The acquiring the three-dimensional scene data of the next position and constructing the three-dimensional navigation information corresponding to the three-dimensional scene data specifically includes: Based on the three-dimensional scene data of the next position, constructing three-dimensional navigation information corresponding to the three-dimensional scene data by a preset rendering method; Visual angle data of the mobile terminal is obtained, and the three-dimensional navigation information is adjusted according to the visual angle data.

6. The navigation method according to claim 5, characterized in that: The constructing the three-dimensional navigation information corresponding to the three-dimensional scene data based on the three-dimensional scene data of the next position by a preset rendering method specifically includes: Dividing the three-dimensional scene data into first data and second data, wherein the fineness of the first data is higher than the fineness of the second data; When the distance between the current position and the next position is greater than a preset distance, the second data is rendered to generate a visual navigation view of a target area, where the target area is the area where the next position is located; When the distance is less than or equal to the preset distance, the first data is rendered to generate a visual navigation view of the target area.

7. The method according to claim 1, characterized in that The method further comprises: The camera of the mobile terminal collects an environmental image of the current location and extracts environmental feature information from the environmental image; obtains three-dimensional scene data of the current location, and fuses the three-dimensional scene data of the current location with the environmental image according to the environmental feature information to generate an augmented reality scene; Overlaying and displaying interactive navigation information on a display screen of the mobile terminal according to the augmented reality scene; In response to the operation instruction input by the user for the interactive navigation information, the corresponding three-dimensional navigation information is updated and displayed on the display screen.

8. A navigation system based on 3D visualization technology, characterized in that: include: An acquisition module, used to acquire the current position of the user in the exhibition hall and the historical exhibition path of the user in the exhibition hall; A prediction module, configured to predict the current exhibition path of the user according to the current location and the historical exhibition path; A determination module, used to determine the next location reached by the user in the current exhibition path; A construction module, used to obtain the three-dimensional scene data of the next position and construct the three-dimensional navigation information corresponding to the three-dimensional scene data; The switching module is used to switch the currently displayed navigation information to the three-dimensional navigation information when the distance between the current position and the next position is less than a preset threshold.

9. A navigation device based on 3D visualization technology, characterized in that: include: one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the navigation device based on 3D visualization technology to execute the method as described in any one of claims 1-7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a navigation device based on 3D visualization technology, the navigation device based on 3D visualization technology executes the method as described in any one of claims 1 to 7.

Images