CN116227834A - Intelligent scenic spot digital platform based on three-dimensional point cloud model - Google Patents
Intelligent scenic spot digital platform based on three-dimensional point cloud model Download PDFInfo
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Abstract
The invention relates to the technical field of digitization, in particular to an intelligent scenic spot digitization platform based on a three-dimensional point cloud model, which comprises the following components: the system comprises a model construction module, a data processing module, a behavior information database, a scenic spot information input module, a data visualization module, a scenic spot service module and a background management module; the scenic spot service module is provided with a scenic spot information unit, an electronic tour guide unit, a virtual experience unit, a path planning unit, a peripheral analysis unit and an electronic commerce group unit; the background management module is provided with a people stream monitoring unit, a personnel scheduling unit, a facility management unit, an emergency processing unit and a planning development unit; the method realizes the transition of the operation management of the scenic spot from the traditional passive processing, the post-hoc management to the process management and the real-time management, and realizes a more convenient and scientific management mode integrating the management of the scenic spot and the planning development.
Description
Technical Field
The invention relates to the technical field of digitization, in particular to an intelligent scenic spot digitization platform based on a three-dimensional point cloud model.
Background
How to balance the relation between the protection and the development of tourist attractions is always a difficult problem to be solved in China, and for some scenic spots with heritage protection value, the scenic spots face the dilemma of disappearance and forgetting by people due to fire, earthquake, artificial damage and the like. How to scientifically plan and protect scenic spots and how to develop economy on the premise of meeting the premise of not damaging ecological environment, the problems are all in the process of promoting the travel work to accelerate the digital transformation, and the digital protection has become an important trend and development direction of the research and practice of the current cultural heritage.
With the continuous development of material civilization and mental civilization construction and the reform and update of high and new technologies such as big data, cloud computing and the Internet of things, in the mass travel age, the requirements of people on the integrity and experience of travel landscapes are gradually increased, the traditional tourist attraction tour mode has poor flexibility, insufficient experience and poor information transmissibility, and the requirements of individuation, autonomy and diversification of vast tourists cannot be met.
For the scenic spot line upstream tour mode, the three-dimensional scene has more real scene effect compared with the two-dimensional scene, and the scenic spot line upstream tour mode can bring more immersive tour experience to people. The point cloud is not the only method for creating the three-dimensional model, but because the method has the advantages of high efficiency, high precision, low cost, strong operability and great development prospect, the method can closely integrate mathematical models of different subjects and can become a powerful means for researching climate change, ecological environment transition, regional change and design in the future. However, in the processing manner of the point cloud, the semantics are difficult to model by the traditional method, and many new challenges still face at present, so that the exploration of a new deep learning model needs to be enhanced.
At present, the daily management work of a scenic spot is heavy, and a large amount of access information needs to be fed back in time and processed quickly. The traditional scenic spot management mode uses more manpower, and its is with high costs, inefficiency, can't better satisfy a large amount of tourists's tour service demands, and management accuracy to the tourist is insufficient, lacks emergency handling ability and to the whole control of scenic spot, can't realize simultaneously with professional visual angle to the planning development contribution strength of scenic spot. Therefore, a more flexible and intelligent management mode is needed, the transition from traditional passive processing, post management to process management and real-time management of scenic spot operation management is realized, and a more convenient and scientific management mode integrating scenic spot management and planning development is realized.
Disclosure of Invention
The invention aims to provide an intelligent scenic spot digital platform based on a three-dimensional point cloud model so as to solve the problems in the background technology.
In order to achieve the technical purpose and the technical effect, the invention is realized by the following technical scheme:
an intelligent scenic spot digital platform based on a three-dimensional point cloud model, comprising:
the model construction module is used for constructing a three-dimensional point cloud model and a refined model of the scenic spot of the original two-dimensional data transmitted by the user;
the data processing module is used for processing the point cloud data, performing semantic segmentation and other operations, and realizing semantic identification and three-dimensional accurate identification of the ground object target;
the data processing module adopts a method of point cloud segmentation and classification identification to process, and the method of point cloud segmentation and classification identification is specifically expressed as follows: all points are marked by using a point cloud marking tool (cloudCompare), elements such as a fence, a road sign, a street lamp and the like are combined in consideration of the scarcity and the similarity of certain category data points, and five semantic categories are finally determined: building, road, vegetation, natural landscape, others, each point is marked as one of five semantic categories, all marks are manually cross checked to ensure consistency and high quality;
testing the scenic spot data set by using classical neural network (PondLA-net) and comparing the classical neural network with the RandLA-net and other networks with accuracy and efficiency; in addition, performance evaluation is performed on the data set by performing a conventional point cloud processing algorithm. Training a deep learning network, learning point cloud characteristics, adjusting training parameters and a network structure according to actual training results, enabling the detection accuracy of semantic tags to be the highest, improving and designing the network, and optimizing the training results;
the behavior information database is used for collecting, storing and analyzing tourist data based on the constructed virtual reality experiment platform;
the scenic spot information input module is used for inputting scenic spot information, exhibits information, facilities information, places information and the like of the scenic spot by an administrator, and storing the information into the database to facilitate later updating management and use;
the data visualization module is used for corresponding visualization presentation of three-dimensional data, chart characters and other data;
the scenic spot service module is used for meeting the tourist's tour requirement of scenic spots, providing the use data for the behavior information database, and covering the characteristic functions of scene virtual experience, path planning and the like;
the background management module is used for managing personnel to monitor and manage scenic spots and personnel in real time, and has planning functions such as updating and developing scenic spots.
Further, the scenic spot service module includes:
scenic spot information unit, including scenic spot geographic information, detailed description, real-time weather, traffic situation, flow distribution, etc., and virtual pre-tour of scenic spots in scenic spots;
the electronic tour guide unit realizes self-service tour guide and explanation of scenic spots based on the electronic mobile equipment, wherein the triggering modes include key triggering, GPS positioning triggering and two-dimensional code scanning triggering, and character introduction, video image or three-dimensional model display of the scenic spots appear after the triggering is successful;
the virtual experience unit is a carrier of a virtual reality experiment platform by combining an AR (augmented reality) technology and a VR (virtual reality) technology with a 3D modeling technology; the virtual tour page comprises a real-time virtual tour page and a virtual interaction page, so that the play of a scenic spot historical evolution virtual image or the restoration reproduction of a historical remains, a living scene and the like are realized, and a tourist can complete body instructions and experience folk-custom activities according to corresponding folk-custom skills by using corresponding AR equipment.
Further, the virtual experience unit is specifically expressed as follows: in a VR virtual scene, a street network database constructed by combining a network surface density method and ArcGIS is used for searching real-time coordinate values of points where people reside, so as to generate a behavior information database; in an AR real-scene environment, acquiring a real-time position outdoors through a user GPS, calling the matching of a user mobile phone camera and a point cloud data scene indoors through a SLAM algorithm, acquiring the indoor positioning of the user, wherein a software system is a Unity development platform, and a hardware system is HCTVEVEPROEYEARFoudation.
Further, the scenic spot service module further includes:
the path planning unit is used for analyzing user hobbies and characteristics by combining with guest behavior analysis of the behavior information database, and excavating a movement mode of the guest by using a movement path prediction technology so as to predict future positions of the guest and generate various recommended routes;
the peripheral analysis unit acquires the positions of scenic spots in all areas, businesses and the specific positions and sales types of all businesses in the scenic spot according to GPS positioning, service facilities such as public places, stations and the like are highlighted, and tourists can conveniently select and quickly navigate to arrive.
The electronic commerce group unit integrates all business states of tourist attractions, and a resident merchant provides commodity introduction and reservation or purchase functions for tourists; and adding a community mechanism into the scenic spot platform webpage, so that tourists can share scenic spot graphic and text information in real time and recommend special commodities.
Further, the background management module includes:
the people stream monitoring unit is used for storing and processing the tourist's visit space-time data, counting and predicting the scenic spot passenger stream, the traffic stream density and the like, and displaying the statistical and predicted scenic spot passenger stream, traffic stream density and the like on a management end in real time;
the personnel scheduling unit reasonably distributes and schedules tourists and vehicles based on the data result of the people stream monitoring unit, and simultaneously performs task distribution and supervision on staff in the scenic spot according to the scenic spot scale, the distribution of the tourists, the logistic needs and the like;
the emergency processing unit is used for checking and solving scenic spot emergency, tourists send help signals through intelligent terminals such as mobile phones and the like, corresponding event types are selected, and management staff can quickly take out a solution according to experience and programs.
Further, the background management module further includes:
the facility management unit is intelligent facility equipment such as a movable garbage truck, a street lamp and an exhibition cabinet in a scenic spot, and is connected with the management terminal, so that the running condition of the facility can be checked in real time, and damaged or poorly-running facility equipment can be marked and repaired in time; the access times and the use times of various facility equipment can be checked to obtain which exhibits and scenic spots are places with the greatest flow of people and most interested by tourists;
the planning development unit can be used for checking the information of greenbelts, rivers, buildings, people flows and the like in the scenic spots in a classified manner, and comprises various scenic analysis such as sunlight analysis, vision analysis, road network analysis and the like for expanding the scenic spots, and reasonable scenic nodes are arranged on the basis of a behavior information database by utilizing a mobile prediction algorithm.
The invention has the beneficial effects that:
the intelligent scenic spot digital platform based on the three-dimensional point cloud model realizes the transition of scenic spot operation management from traditional passive processing, post management to process management and real-time management, and realizes a more convenient and scientific management mode integrating scenic spot management and planning development.
According to the invention, the three-dimensional point cloud model construction of the scenic spot is carried out through the model construction module, so that the subsequent data processing module can conveniently carry out point cloud segmentation and classification identification, and the platform can determine five semantic categories: building, road, vegetation, natural landscape and others, and is convenient for subsequent treatment; the data module adopts classical neural network (Ponet++) to test the scenic spot data set, and is matched with RandLA-net and other networks to compare with the classical neural network (Ponet++), so that the detection accuracy of semantic tags is improved, and a high-precision scenic spot three-dimensional point cloud model can be constructed.
According to the invention, the tourist data are acquired and analyzed through the behavior information database, and the tourist behavior information data are acquired and analyzed by matching with the tourist information input module for inputting scenic spots, exhibits and facilities, so that the tourist is required to collect related information data, the tourist behavior information data can be provided for the scenic spot service module, and the data visualization module can present three-dimensional data, chart characters and other visualization forms, so that staff or management staff can more intuitively grasp various data, the scenic spot can be conveniently and correspondingly adjusted according to the tourist's tourist requirements on the scenic spot, the adjustment of subsequent scene virtual experience, path planning and the like is facilitated, and the tourist comfort level is improved; scenic spot management personnel can carry out real-time monitoring of scenic spots and tourists and management of staff through the background management module, and corresponding adjustment of scenic spots can be carried out according to the behavior information database and the data visualization module.
The scenic spot service module comprises a plurality of groups of units which are matched together, wherein the scenic spot information unit comprises scenic spot geographic information, detailed description, real-time weather, traffic conditions, people flow distribution and the like, and scenic spot virtual pre-tour in the scenic spot; the electronic tour guide unit is used for realizing self-service tour guide and explanation of scenic spots based on the electronic mobile equipment; the virtual experience unit comprises a real-time virtual tour page and a virtual interaction page, so that the play of a scenic spot history evolution virtual image or the recovery reproduction of a history remains, a living scene and the like are realized; the path planning unit is combined with guest behavior analysis of the behavior information database to analyze user hobbies and characteristics and generate various recommended routes; the peripheral analysis unit obtains the positions of scenic spots in all areas, businesses and the specific positions and sales types of all businesses in the scenic spot according to GPS positioning, service facilities such as public places, stations and the like are highlighted, and tourists can conveniently select and quickly navigate to arrive; the electronic commerce group unit integrates all business states of tourist attractions, and a resident merchant provides commodity introduction and reservation or purchase functions for tourists; the tourist can be provided with a plurality of reference services such as scenic spot geography, environment, routes, facilities and the like, so that the knowledge and grasp of the tourist on each area of the scenic spot can be improved, the tourist tour efficiency can be improved, the effective time of the tourist tour can be prolonged, and the people flow pressure can be relieved.
The background management module comprises a plurality of groups of units which are matched together to perform background management of scenic spots, and the people flow monitoring unit is used for counting and predicting the passenger flow, the traffic flow density and the like of the scenic spots, so that a manager can grasp the specific information of tourists in the scenic spots conveniently; the personnel scheduling unit reasonably distributes and schedules tourists and vehicles based on the data result of the people stream monitoring unit, so that the personnel can conveniently distribute tasks; the emergency processing unit is used for checking and solving scenic spot emergency events and guaranteeing personal safety of tourists; the facility management unit is connected with the movable garbage truck, the street lamp, the exhibition cabinet and the like in the scenic spot, so that the running condition of the facility can be checked in real time, damaged or poorly-running facility equipment can be marked and repaired in time, the time for invalidating the facility in the scenic spot is reduced, and the comfort level of tourists is improved; the planning development unit can be used for checking the information of greenbelts, rivers, buildings, people flows and the like in the scenic spots in a classified manner, and comprises various scenic analyses for expanding the scenic spots, and reasonable scenic nodes are arranged on the basis of a behavior information database by utilizing a mobile prediction algorithm; the method ensures the effective grasp of the manager on the scenic spot, realizes the transition of the operation management of the scenic spot from the traditional passive processing, post management to the process management and real-time management, reduces the complicated steps in the middle of the management and improves the management efficiency.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below, in which the drawings are only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a diagram of an embodiment of guest trajectory prediction and recommendation.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
An intelligent scenic spot digital platform based on a three-dimensional point cloud model according to the embodiment includes:
the model construction module is used for constructing a three-dimensional point cloud model and a refined model of the scenic spot of the original two-dimensional data transmitted by the user;
the data processing module is used for processing the point cloud data, performing semantic segmentation and other operations, and realizing semantic identification and three-dimensional accurate identification of the ground object target;
the data processing module adopts a method of point cloud segmentation and classification identification to process, and the method of point cloud segmentation and classification identification is specifically expressed as follows: all points are marked by using a point cloud marking tool (cloudCompare), elements such as a fence, a road sign, a street lamp and the like are combined in consideration of the scarcity and the similarity of certain category data points, and five semantic categories are finally determined: building, road, vegetation, natural landscape, others, each point is marked as one of five semantic categories, all marks are manually cross checked to ensure consistency and high quality;
testing the scenic spot data set by using classical neural network (PondLA-net) and comparing the classical neural network with the RandLA-net and other networks with accuracy and efficiency; in addition, performance evaluation is performed on the data set by performing a conventional point cloud processing algorithm. Training a deep learning network, learning point cloud characteristics, adjusting training parameters and a network structure according to actual training results, enabling the detection accuracy of semantic tags to be the highest, improving and designing the network, and optimizing the training results;
the behavior information database is used for collecting, storing and analyzing tourist data based on the constructed virtual reality experiment platform;
the scenic spot information input module is used for inputting scenic spot information, exhibits information, facilities information, places information and the like of the scenic spot by an administrator, and storing the information into the database to facilitate later updating management and use;
the data visualization module is used for corresponding visualization presentation of three-dimensional data, chart characters and other data;
the scenic spot service module is used for meeting the tourist's tour requirement of scenic spots, providing the use data for the behavior information database, and covering the characteristic functions of scene virtual experience, path planning and the like;
the background management module is used for managing personnel to monitor and manage scenic spots and personnel in real time, and has planning functions such as updating and developing scenic spots.
In this embodiment, the scenic spot service module includes:
scenic spot information unit, including scenic spot geographic information, detailed description, real-time weather, traffic situation, flow distribution, etc., and virtual pre-tour of scenic spots in scenic spots;
the electronic tour guide unit realizes self-service tour guide and explanation of scenic spots based on the electronic mobile equipment, wherein the triggering modes include key triggering, GPS positioning triggering and two-dimensional code scanning triggering, and character introduction, video image or three-dimensional model display of the scenic spots appear after the triggering is successful;
the virtual experience unit is a carrier of a virtual reality experiment platform by combining an AR (augmented reality) technology and a VR (virtual reality) technology with a 3D modeling technology; the virtual tour page comprises a real-time virtual tour page and a virtual interaction page, so that the play of a scenic spot historical evolution virtual image or the restoration reproduction of a historical remains, a living scene and the like are realized, and a tourist can complete body instructions and experience folk-custom activities according to corresponding folk-custom skills by using corresponding AR equipment.
In this embodiment, the virtual experience unit is specifically expressed as: in a VR virtual scene, a street network database constructed by combining a network surface density method and ArcGIS is used for searching real-time coordinate values of points where people reside, so as to generate a behavior information database; in an AR real-scene environment, acquiring a real-time position outdoors through a user GPS, calling the matching of a user mobile phone camera and a point cloud data scene indoors through a SLAM algorithm, acquiring the indoor positioning of the user, wherein a software system is a Unity development platform, and a hardware system is HCTVEVEPROEYEARFoudation.
In this embodiment, the scenic spot service module further includes:
the path planning unit is used for analyzing user hobbies and characteristics by combining with guest behavior analysis of the behavior information database, and excavating a movement mode of the guest by using a movement path prediction technology so as to predict future positions of the guest and generate various recommended routes;
the peripheral analysis unit acquires the positions of scenic spots in all areas, businesses and the specific positions and sales types of all businesses in the scenic spot according to GPS positioning, service facilities such as public places, stations and the like are highlighted, and tourists can conveniently select and quickly navigate to arrive.
The electronic commerce group unit integrates all business states of tourist attractions, and a resident merchant provides commodity introduction and reservation or purchase functions for tourists; and adding a community mechanism into the scenic spot platform webpage, so that tourists can share scenic spot graphic and text information in real time and recommend special commodities.
In this embodiment, the background management module includes:
the people stream monitoring unit is used for storing and processing the tourist's visit space-time data, counting and predicting the scenic spot passenger stream, the traffic stream density and the like, and displaying the statistical and predicted scenic spot passenger stream, traffic stream density and the like on a management end in real time;
the personnel scheduling unit reasonably distributes and schedules tourists and vehicles based on the data result of the people stream monitoring unit, and simultaneously performs task distribution and supervision on staff in the scenic spot according to the scenic spot scale, the distribution of the tourists, the logistic needs and the like;
the emergency processing unit is used for checking and solving scenic spot emergency, tourists send help signals through intelligent terminals such as mobile phones and the like, corresponding event types are selected, and management staff can quickly take out a solution according to experience and programs.
In this embodiment, the background management module further includes:
the facility management unit is intelligent facility equipment such as a movable garbage truck, a street lamp and an exhibition cabinet in a scenic spot, and is connected with the management terminal, so that the running condition of the facility can be checked in real time, and damaged or poorly-running facility equipment can be marked and repaired in time; the access times and the use times of various facility equipment can be checked to obtain which exhibits and scenic spots are places with the greatest flow of people and most interested by tourists;
the planning development unit can be used for checking the information of greenbelts, rivers, buildings, people flows and the like in the scenic spots in a classified manner, and comprises various scenic analysis such as sunlight analysis, vision analysis, road network analysis and the like for expanding the scenic spots, and reasonable scenic nodes are arranged on the basis of a behavior information database by utilizing a mobile prediction algorithm.
Example 2
An intelligent scenic spot digital platform based on a three-dimensional point cloud model according to the embodiment includes:
the system comprises a model construction module, a data processing module, a behavior information database, a scenic spot information input module, a data visualization module, a scenic spot service module and a background management module. The scenic spot service module is provided with a scenic spot information unit, an electronic tour guide unit, a virtual experience unit, a path planning unit, a peripheral analysis unit and an electronic commerce group unit. The background management module is provided with a people stream monitoring unit, a personnel scheduling unit, a facility management unit, an emergency processing unit and a planning development unit.
In this embodiment, the guest service module includes:
tourist client
Virtual reality helmet: support AR, VR;
cell phone application client: support AR, VR;
in this embodiment, the virtual experience unit provides the interactive AR tour guide service for the on-site tourists by using the AR technology, and the client that the tourists can use is a mobile phone with a depth camera or hollens so as to display the virtual object on the interactive device. Virtual objects overlapped with the real scene such as virtual signs, virtual tour guides, virtual commodity experience, historical remains reproduction, virtual commodity experience, path navigation and the like, and the interestingness of tourist experience is increased. The application was developed using ARFoundation.
And a VR technology is applied to provide complete virtual scene client browsing for remote tourists. The user can visit great river mountain and ancient points by sitting at home, and the defect that the user cannot reach the scenic spot for various reasons is overcome. In addition, the VR platform is used for collecting the behavior data of the tourists and training a tourist recommendation model. Its function is the same as the AR interaction design.
In this embodiment, the tourist track prediction module is configured to predict a track of a user, locate a scenic spot tag of a point where the tourist is located according to an age, a sex, and a previous track location of the user, and predict a track of the tourist 5 minutes later.
In this embodiment, the peripheral analysis unit: the method comprises the steps of obtaining positions of scenic spots in all areas in a scenic spot according to GPS positioning, clicking and checking the positions of the scenic spots in all areas by tourists at the end points of mobile phone tourists, and positioning the end points through a mobile phone navigation system; in addition, according to the selection, the business in the scenic spot and the specific position and sales type page of each business can be switched to navigate; the service facilities such as the toilet, the bus station, the service station, the emergency center and the like are highlighted, so that tourists can conveniently select and quickly navigate to arrive, and in the process of visiting, the tourists can check surrounding facilities and environments at any time.
In this embodiment, the e-commerce group unit: the electronic commerce module is used for integrating all the business states of the tourist attractions, so that the opportunity of contacting tourists is increased for local merchants of all the tourist attractions, and the income is increased. The merchant comprises one or more of a restaurant type shop, a lodging type shop and a supermarket shop, each shop has the functions of introducing and reserving or purchasing goods, tickets, hotels, tickets and the like can be reserved, and local specialities or other products can be mailed to the home. The multi-stage distribution of the travel related industry is realized through the recommendation function of tourists to merchants and the pushing function of tourists to merchant commodities, and the marketing channel is optimized. By adding a community mechanism in the scenic spot platform webpage, tourists can share scenic spot image-text information in real time and recommend special commodities without blocking tourist information.
In this embodiment, the administrator module: scene loading
The method is used for constructing a three-dimensional model of a scenic spot, and is a foundation for constructing a digital platform. The user may upload PCD point cloud files from the results of three-dimensional digital mapping such as UAVDP (unmanned aerial vehicle close-up photogrammetry), TLS (terrestrial three-dimensional laser scanning), etc. The data preprocessing process of the system comprises multi-file point cloud registration, downsampling, outlier point removal, point cloud smoothing and Mesh three-dimensional model generation.
In this embodiment, the scenic spot information unit is recorded: the platform home page layout comprises a two-dimensional or three-dimensional map of the whole scenic spot, the home page displays scenic spot information including scenic spot geographic information, detailed description, real-time weather, traffic conditions, people flow distribution and the like, and tourists can log in the platform system to grasp scenic spot information in advance so as to determine destinations, carry articles and the like. All scenic spots can be checked on the scenic spot map, tourists can select the data of a detailed scenic spot to check, and the scenic spot panorama is browsed on line, so that virtual pre-tour of scenic spots in the scenic spot is realized, tourists can be helped to select favorite scenic spots in advance, travel planning is done, and the travel efficiency and the tour satisfaction of the tourists are improved. For specific buildings, scenic spot service facilities, point clouds of stores, manual calibration classifications, and introductions. And when the sight of the client of the tourist is detected to stay on the corresponding object, displaying the introduction of the client of the tourist.
In this embodiment, the guest trajectory prediction model is trained and deployed: the tourist track prediction model is trained by building a scenic spot virtual reality model through a network by means of VR technology, real-time environment emotion measurement and environment behavior perception measurement are carried out on a crowd in a VR environment by using virtual reality equipment and an eye movement instrument, data of a user in behavior tracks, time and views and standing points are collected, comparison analysis is carried out on the data and the same data collected in a real field, difference data of user behavior perception and relationship between the difference data are researched in the two scenes, and then building of a behavior perception research virtual reality experiment platform can be realized. The model is trained using LSTM neural networks.
In this embodiment, the scene semantic segmentation model is deployed: the system deploys automatic semantic segmentation models of point cloud scenes, such as pre-trained outdoor scene model parameters of kpconv, randlanet, pointe++, pct and the like, and the identifiable types are thirteen types: buildings, grasslands, roads, plants, bridges, waterways, automobiles, sundries, and the like.
In this embodiment, a model for people flow prediction is deployed in the system, and an administrator monitors people flow in real time, predicts people flow, avoids a congested road section when tourists navigate and route is recommended, and gives a timely alarm for a congestion event which may occur.
In this embodiment, scenic spot employee management: scenic spot management personnel input, task allocation and scheduling.
In this embodiment, the emergency processing unit: if people flow monitoring gives out an alarm for inducing the risk of safety accidents such as trampling and traffic accidents, or a tourist gives out a help signal through an intelligent terminal such as a mobile phone, a corresponding event type is selected, a manager can quickly take out a solution according to experience and programs, relevant people are dispatched to follow up the event in the first time, actions are quickly taken, and the best opportunity is prevented from being delayed.
In this embodiment, the planning development unit: the method can be used for checking the information of the quantity, the spatial distribution and the like of resources such as green land, river, building, residents and the like in the scenic spot in a classified manner, and can be used for expanding various scenic analyses such as sunlight analysis, vision analysis, road network analysis and the like aiming at the inside of the scenic spot, so that the method can be used for finding the best scenic mode for tourists, and can be also suitable for site planning and post-disaster restoration; and a mobile prediction algorithm is used for acquiring the position of a user at a specific time, reasonable landscape nodes and road nodes are arranged on the basis of a behavior information database, facilities such as pavilion flower frames and sign rows are optimized, reasonable space layout is given to rest play, humanized service experience is used as the basis, the view structure is improved subsequently, the characteristic clear direction of a scenic spot is highlighted, the satisfaction degree of tourists and the convenience degree of scenic spot management are improved, and meanwhile scientific and effective data support is provided for future planning and development of the scenic spot.
Example 3
As shown in fig. 1
In the embodiment, a client supports a virtual helmet from hardware, an eye tracker and mobile phone equipment with a depth camera, and supports two sets of designs of VR and AR; for users, if they want to have a relatively high immersive experience, such as a smoother real-time response for positioning, navigation, and recommendation of the user, there is a need to install an edge computing server for high performance and high bandwidth data communications in the vicinity of the scenic spot. The scene semantic segmentation, the user real-time positioning and camera pose estimation algorithm, the tourist track prediction, the people flow prediction and other model operations are all carried out at the server side, and the result is returned to the client side to provide better experience service for the tourist.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (6)
1. Intelligent scenic spot digital platform based on three-dimensional point cloud model, its characterized in that, the platform includes:
the model construction module is used for constructing a three-dimensional point cloud model and a refined model of the scenic spot of the original two-dimensional data transmitted by the user;
the data processing module is used for processing the point cloud data, performing semantic segmentation and other operations, and realizing semantic identification and three-dimensional accurate identification of the ground object target;
the data processing module adopts a method of point cloud segmentation and classification identification to process, and the method of point cloud segmentation and classification identification is specifically expressed as follows: all points are marked by using a point cloud marking tool (cloudCompare), elements such as a fence, a road sign, a street lamp and the like are combined in consideration of the scarcity and the similarity of certain category data points, and five semantic categories are finally determined: building, road, vegetation, natural landscape, others, each point is marked as one of five semantic categories, all marks are manually cross checked to ensure consistency and high quality;
testing the scenic spot data set by using classical neural network (PondLA-net) and comparing the classical neural network with the RandLA-net and other networks with accuracy and efficiency; in addition, performing a traditional point cloud processing algorithm on the data set, and performing performance evaluation; training a deep learning network, learning point cloud characteristics, adjusting training parameters and a network structure according to actual training results, enabling the detection accuracy of semantic tags to be the highest, improving and designing the network, and optimizing the training results;
the behavior information database is used for collecting, storing and analyzing tourist data based on the constructed virtual reality experiment platform;
the scenic spot information input module is used for inputting scenic spot information, exhibits information, facilities information, places information and the like of the scenic spot by an administrator, and storing the information into the database to facilitate later updating management and use;
the data visualization module is used for corresponding visualization presentation of three-dimensional data, chart characters and other data;
the scenic spot service module is used for meeting the tourist's tour requirement of scenic spots, providing the use data for the behavior information database, and covering the characteristic functions of scene virtual experience, path planning and the like;
the background management module is used for managing personnel to monitor and manage scenic spots and personnel in real time, and has planning functions such as updating and developing scenic spots.
2. The intelligent scenic spot digitizing platform based on the three-dimensional point cloud model of claim 1, wherein the scenic spot service module comprises:
scenic spot information unit, including scenic spot geographic information, detailed description, real-time weather, traffic situation, flow distribution, etc., and virtual pre-tour of scenic spots in scenic spots;
the electronic tour guide unit realizes self-service tour guide and explanation of scenic spots based on the electronic mobile equipment, wherein the triggering modes include key triggering, GPS positioning triggering and two-dimensional code scanning triggering, and character introduction, video image or three-dimensional model display of the scenic spots appear after the triggering is successful;
the virtual experience unit is a carrier of a virtual reality experiment platform by combining an AR (augmented reality) technology and a VR (virtual reality) technology with a 3D modeling technology; the virtual tour page comprises a real-time virtual tour page and a virtual interaction page, so that the play of a scenic spot historical evolution virtual image or the restoration reproduction of a historical remains, a living scene and the like are realized, and a tourist can complete body instructions and experience folk-custom activities according to corresponding folk-custom skills by using corresponding AR equipment.
3. The intelligent scenic spot digitizing platform based on the three-dimensional point cloud model according to claim 2, wherein the virtual experience unit is specifically expressed as: in a VR virtual scene, a street network database constructed by combining a network surface density method and ArcGIS is used for searching real-time coordinate values of points where people reside, so as to generate a behavior information database; in an AR real-scene environment, a real-time position is obtained outdoors through a user GPS, matching of a user mobile phone camera and a point cloud data scene is invoked indoors through a SLAM algorithm, indoor positioning of a user is obtained, a software system is a Unity development platform, and a hardware system is HCTVIVEPROEYEAR Foudation.
4. The intelligent scenic spot digitizing platform based on the three-dimensional point cloud model of claim 2, wherein the scenic spot service module further comprises:
the path planning unit is used for analyzing user hobbies and characteristics by combining with guest behavior analysis of the behavior information database, and excavating a movement mode of the guest by using a movement path prediction technology so as to predict future positions of the guest and generate various recommended routes;
the peripheral analysis unit is used for acquiring the positions of scenic spots in all areas, businesses and the specific positions and sales types of all businesses in the scenic spot according to GPS positioning, service facilities such as public places, stations and the like are highlighted, and tourists can conveniently select and quickly navigate to arrive;
the electronic commerce group unit integrates all business states of tourist attractions, and a resident merchant provides commodity introduction and reservation or purchase functions for tourists; and adding a community mechanism into the scenic spot platform webpage, so that tourists can share scenic spot graphic and text information in real time and recommend special commodities.
5. The intelligent scenic spot digitizing platform based on the three-dimensional point cloud model of claim 1, wherein the background management module comprises:
the people stream monitoring unit is used for storing and processing the tourist's visit space-time data, counting and predicting the scenic spot passenger stream, the traffic stream density and the like, and displaying the statistical and predicted scenic spot passenger stream, traffic stream density and the like on a management end in real time;
the personnel scheduling unit reasonably distributes and schedules tourists and vehicles based on the data result of the people stream monitoring unit, and simultaneously performs task distribution and supervision on staff in the scenic spot according to the scenic spot scale, the distribution of the tourists, the logistic needs and the like;
the emergency processing unit is used for checking and solving scenic spot emergency, tourists send help signals through intelligent terminals such as mobile phones and the like, corresponding event types are selected, and management staff can quickly take out a solution according to experience and programs.
6. The intelligent scenic spot digitizing platform based on the three-dimensional point cloud model of claim 5, wherein the background management module further comprises:
the facility management unit is intelligent facility equipment such as a movable garbage truck, a street lamp and an exhibition cabinet in a scenic spot, and is connected with the management terminal, so that the running condition of the facility can be checked in real time, and damaged or poorly-running facility equipment can be marked and repaired in time; the access times and the use times of various facility equipment can be checked to obtain which exhibits and scenic spots are places with the greatest flow of people and most interested by tourists;
the planning development unit can be used for checking the information of greenbelts, rivers, buildings, people flows and the like in the scenic spots in a classified manner, and comprises various scenic analysis such as sunlight analysis, vision analysis, road network analysis and the like for expanding the scenic spots, and reasonable scenic nodes are arranged on the basis of a behavior information database by utilizing a mobile prediction algorithm.
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