A method and system for gesture capture based on virtual reality

Abstract

The present invention is applicable to the field of virtual reality, and provides a method and system for gesture capture based on virtual reality. The system includes: an environmental state and gesture capture module, a gesture state evaluation and analysis module, a virtual reality connection module, and an optimal state analysis module. This solution deeply analyzes the captured gesture data to quickly identify whether there are abnormal gestures in plants, which helps to take timely measures. When an abnormal gesture is recognized, multiple growth environment control groups can be established, and the growth conditions of plants in different environments can be simulated through virtual reality technology to help researchers or agricultural workers understand the impact of environmental changes on plant growth. For plants with normal gestures, the system can also generate predictions of future growth gesture changes, providing a scientific basis for the long-term management of plants.

Description

Technical Field

[0001] The present invention belongs to the field of virtual reality, and particularly relates to a posture capture method and system based on virtual reality. Background Art

[0002] The virtual reality posture capture system is an advanced technology applied to plant growth analysis. It utilizes virtual reality technology and posture capture technology to capture the posture and motion data of plants in real time and present them in a virtual form. Through virtual reality technology, the posture and motion data of plants can be presented in the form of a three-dimensional virtual model, enabling researchers to more intuitively observe and analyze the growth process of plants. At the same time, virtual reality technology can also provide interactivity, and researchers can interact with the virtual model through gestures or other means to further deeply study the growth mechanism of plants.

[0003] The application of the virtual reality posture capture system provides a new method for plant growth analysis. It captures and presents the posture and motion data of plants in real time through virtual reality technology and posture capture technology, providing researchers with a more intuitive and interactive research tool, which helps to deeply understand the growth mechanism and laws of plants.

[0004] Traditional plant growth monitoring often relies on periodic observations and data collection, and it is unable to capture the minute changes in plant postures in real time. Moreover, the specific impacts of environmental changes on plant growth are often difficult to quantify and predict. Summary of the Invention

[0005] The purpose of the present invention is to provide a posture capture method based on virtual reality, aiming to solve the technical problems existing in the prior art identified in the background art.

[0006] The present invention is implemented as follows. A posture capture method based on virtual reality, the method includes the following steps:

[0007] Obtain the growth environment data of the current plant, and capture the posture data of the plant in real time through a camera, and extract specific posture features from the posture data;

[0008] Analyze the extracted posture features to identify and determine whether the current plant has abnormal postures;

[0009] When the plant has abnormal postures and when the plant does not have abnormal postures respectively, establish a virtual reality model of plant growth, and set an environmental parameter adjustment interface to analyze the growth posture changes in different growth environment data;

[0010] Based on the growth posture change data, obtain the optimal growth environment data and generate a report.

[0011] As a further solution of the present invention, acquiring the growth environment data of the current plant, capturing the pose data of the plant in real time through a camera, and extracting specific pose features from the pose data specifically includes:

[0012] Collecting various environmental parameters in the plant growth environment in real time through sensors, and establishing an environmental parameter set to store the data;

[0013] Capturing the pose of the plant from different angles, and extracting pose feature information, including but not limited to: leaf angle, leaf morphological change, branch curvature, plant height.

[0014] As a further solution of the present invention, analyzing the extracted pose features to identify and judge whether the current plant has an abnormal pose, specifically including:

[0015] Establishing an anomaly detection model, analyzing the extracted plant pose features, and judging whether there is an abnormal pose based on the status data of all plants;

[0016] Based on the anomaly detection result, comprehensively evaluating the health status of the plant and analyzing the change trend of the plant.

[0017] As a further solution of the present invention, establishing a virtual reality model of plant growth, setting an environmental parameter adjustment interface, and analyzing the growth pose changes in different growth environment data, specifically including:

[0018] Obtaining the anomaly pose analysis result. If there is no abnormal pose, analyzing the current growth environment data; if there is an abnormal pose, establishing several growth environment control groups based on the current growth environment data;

[0019] When there is no abnormal pose, establishing a virtual reality model of plant growth by combining the analysis result of the growth environment data, and generating the future growth pose change result of the plant based on the current growth environment data;

[0020] When there is an abnormal pose, establishing a virtual reality model of plant growth, generating the future growth pose change result of the plant under different control groups, and identifying the virtual reality model of plant growth with no abnormal pose or the smallest degree of abnormal pose, as well as the corresponding control group data.

[0021] Another object of the present invention is to provide a pose capture system based on virtual reality, and the system includes:

[0022] An environmental state and pose capture module, configured to acquire the growth environment data of the current plant, capture the pose data of the plant in real time through a camera, and extract specific pose features from the pose data;

[0023] The posture state evaluation and analysis module is used to analyze the extracted posture features, identify and judge whether the current plant has abnormal postures;

[0024] The virtual reality connection module is used to establish a virtual reality model of plant growth and set an environmental parameter adjustment interface when the plant has abnormal postures and when the plant does not have abnormal postures, and analyze the growth posture changes in different growth environment data;

[0025] The optimal state analysis module is used to obtain the optimal growth environment data based on the growth posture change data and generate a report.

[0026] As a further solution of the present invention, the environmental state and posture capture module includes:

[0027] The environmental sensing unit is used to collect various environmental parameters in the plant growth environment in real time through sensors and establish an environmental parameter set to store the data;

[0028] The posture capture unit is used to capture the posture of the plant from different angles and extract posture feature information, including but not limited to: leaf angle, leaf morphological changes, branch curvature, plant height.

[0029] As a further solution of the present invention, the posture state evaluation and analysis module includes:

[0030] The abnormal posture detection unit is used to establish an abnormal detection model, analyze the extracted plant posture features, and judge whether there are abnormal postures based on the state data of all plants;

[0031] The health evaluation unit is used to comprehensively evaluate the health state of the plant based on the abnormal detection results and analyze the change trend of the plant.

[0032] As a further solution of the present invention, the virtual reality connection module includes:

[0033] The abnormal state analysis unit is used to obtain the abnormal posture analysis result. If there are no abnormal postures, analyze the current growth environment data; if there are abnormal postures, establish several growth environment control groups based on the current growth environment data;

[0034] The virtual reality model generation unit is used to establish a virtual reality model of plant growth by combining the growth environment data analysis result when there are no abnormal postures, and generate the future growth posture change result of the plant based on the current growth environment data;

[0035] When there is an abnormal posture, a virtual reality model of plant growth is established to generate the results of the future growth posture changes of plants under different control groups, and identify the virtual reality model of plant growth with no abnormal posture or the smallest degree of abnormal posture, as well as the corresponding control group data.

[0036] The beneficial effects of the present invention are as follows:

[0037] This solution deeply analyzes the captured posture data to quickly identify whether there is an abnormal posture in the plant, which helps to take timely measures. When an abnormal posture is identified, multiple growth environment control groups can be established, and the growth conditions of plants under different environments can be simulated through virtual reality technology to help researchers or agricultural workers understand the impact of environmental changes on plant growth. For plants with normal postures, the system can also generate predictions of future growth posture changes, providing a scientific basis for the long-term management of plants. Description of the Drawings

[0038] Figure 1 It is a flowchart of a posture capture method based on virtual reality provided by an embodiment of the present invention;

[0039] Figure 2 It is a flowchart of obtaining the growth environment data of the current plant, capturing the posture data of the plant in real time through a camera, and extracting specific posture features from the posture data provided by an embodiment of the present invention;

[0040] Figure 3 It is a flowchart of analyzing the extracted posture features to identify and determine whether there is an abnormal posture in the current plant provided by an embodiment of the present invention;

[0041] Figure 4 It is a flowchart of establishing a virtual reality model of plant growth, setting an environmental parameter adjustment interface, and analyzing the growth posture changes in different growth environment data provided by an embodiment of the present invention;

[0042] Figure 5 It is a structural block diagram of a posture capture system based on virtual reality provided by an embodiment of the present invention;

[0043] Figure 6 It is a structural block diagram of an environmental state and posture capture module provided by an embodiment of the present invention;

[0044] Figure 7 It is a structural block diagram of a posture state evaluation and analysis module provided by an embodiment of the present invention;

[0045] Figure 8 It is a structural block diagram of a virtual reality connection module provided by an embodiment of the present invention. Detailed Embodiments

[0046] To make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0047] It can be understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of this application, the first xx script may be referred to as the second xx script, and similarly, the second xx script may be referred to as the first xx script.

[0048] Figure 1 It is a flowchart of a posture capture method based on virtual reality provided by an embodiment of the present invention. As Figure 1 shown, a posture capture method based on virtual reality, the method includes:

[0049] S100, obtain the growth environment data of the current plant, and capture the posture data of the plant in real time through a camera, and extract specific posture features from the posture data;

[0050] The sensors used in this step include temperature sensors, humidity sensors, light sensors, CO2 sensors, soil humidity sensors, etc. Through the above sensors, various environmental parameters in the plant growth environment can be collected in real time, such as temperature, humidity, light intensity, CO2 concentration, soil humidity, etc., and these parameters are used as growth environment data;

[0051] For the posture capture of the plant, devices such as high-resolution cameras, 3D sensors, depth cameras, etc. will be used to capture the posture of the plant from multiple angles to ensure the comprehensiveness and accuracy of the posture data.

[0052] S200, analyze the extracted posture features, and identify and judge whether the current plant has abnormal postures;

[0053] In this step, key features will be extracted from the captured plant posture data, such as leaf angle, leaf morphology change, branch curvature, plant height, etc. At the same time, an abnormal monitoring model will be set up to analyze the extracted posture features and identify whether there are abnormal postures. Whether the characteristic parameters exceed the normal range is judged through the set threshold range to detect possible posture abnormalities. In the identification process, specific abnormal types (such as leaf drooping, leaf curling, branch bending, etc.) will be identified and the detection results will be recorded.

[0054] Based on the anomaly detection results and other pose features, the health status of the plant will also be comprehensively evaluated to give a health score. Then, the current pose features will be compared with historical data to analyze the changing trend of the plant's health status. And a detailed health report will be generated later, including the anomaly detection results, health score, and trend analysis.

[0055] Through the collaborative work of multiple modules, it is possible to efficiently and accurately analyze the pose features of plants, identify abnormal poses, and evaluate the health status of plants, providing reliable data support for the subsequent establishment of virtual reality models and the analysis of optimal states.

[0056] S300, respectively, when the plant has an abnormal pose and when the plant does not have an abnormal pose, establish a virtual reality model of plant growth, set an interface for adjusting environmental parameters, and analyze the changes in growth poses in different growth environment data;

[0057] This step integrates functions such as real-time data reception, virtual reality modeling, anomaly recognition, environmental parameter adjustment, future growth prediction, control group establishment and analysis, optimal model display, and report generation.

[0058] If there is no abnormal pose, analyze the current growth environment data, establish a virtual reality model of plant growth in combination with the analysis results of the growth environment data, and generate the results of the future growth pose changes of the plant based on the current growth environment data;

[0059] If there is an abnormal pose, based on the current growth environment data, establish several growth environment control groups, establish a virtual reality model of plant growth, generate the results of the future growth pose changes of the plant under different control groups, and identify the virtual reality model of plant growth with no abnormal pose or the smallest degree of abnormal pose, as well as the corresponding control group data.

[0060] S400, based on the growth pose change data, obtain the optimal growth environment data and generate a report.

[0061] Figure 2 This is a flowchart for obtaining the growth environment data of the current plant, capturing the pose data of the plant in real time through a camera, and extracting specific pose features from the pose data, as Figure 2 shown. The obtaining of the growth environment data of the current plant, capturing the pose data of the plant in real time through a camera, and extracting specific pose features from the pose data specifically include:

[0062] S110, collect various environmental parameters in the plant growth environment in real time through sensors, and establish an environmental parameter set to store the data;

[0063] S120. Capture the postures of plants from different angles and extract posture feature information, including but not limited to: leaf angles, morphological changes of leaves, branch curvatures, and plant heights.

[0064] In the embodiments of the present invention, the process of collecting various environmental parameters in the plant growth environment in real time through sensors and establishing an environmental parameter set for storing data corresponds to the following relational expression:

[0065] ;

[0066] Wherein, represents the total length of the time period, represents a time point, represents the comprehensive environmental parameter set at the time point t ; represents the environmental parameter i 's weight factor, represents the real-time data of the environmental parameter t at the time point i ; represents the natural exponential function regarding the non-linear influence of environmental conditions, represents the adjustment factor used to control the influence of the exponential function on the final result, represents the weakening factor used to adjust the attenuation speed in the exponential function, represents the number of types of environmental parameters, represents the number of environmental conditions, represents the environmental condition j 's weight factor, represents the real-time data of the environmental condition t at the time point j ;

[0067] In the process of establishing the above environmental parameter set, the weighted summation part of the present invention can flexibly adjust the influence of each environmental parameter in the comprehensive environmental parameter set by using weights. Therefore, the weights can be adjusted according to the types of plants and specific requirements to customize the importance of each environmental parameter.

[0068] And the exponential decay part can capture the non-linear influence of certain environmental conditions, such as the rapid influence of extreme light or humidity on plant growth. Through exponential decay, this part can effectively reduce the influence of some adverse environmental conditions while amplifying the positive effects of key environmental conditions, thereby more accurately reflecting the influence on plants in the real environment. And the adjustment factor and the weakening factor provide the ability to control the influence and attenuation speed of the exponential function, ensuring the flexibility of the calculation process.

[0069] Finally, by considering the changes in environmental parameters over the entire time period through time integration, a global perspective is provided, avoiding the limitations of data at a single time point, being able to capture the dynamic changes in environmental parameters, reflecting the time-varying characteristics of the plant growth environment, and thus providing a more comprehensive and accurate set of environmental parameters.

[0070] Figure 3 The flowchart for analyzing the extracted pose features to identify and determine whether there is an abnormal pose of the current plant provided by the embodiment of the present invention is as Figure 3 shown. Analyzing the extracted pose features to identify and determine whether there is an abnormal pose of the current plant specifically includes:

[0071] S210, establishing an anomaly detection model, analyzing the extracted plant pose features, and judging whether there is an abnormal pose based on the status data of all plants;

[0072] S220, based on the anomaly detection results, comprehensively evaluating the health status of the plant and analyzing the plant change trend.

[0073] In the embodiment of the present invention, judging whether there is an abnormal pose based on the status data of all plants specifically includes:

[0074] Reading all the status data of the plant pose and establishing a dimensional vector:

[0075] ;

[0076] Among them, represents all the status data, represents the n th data point;

[0077] Performing standardization processing on all the obtained data:

[0078] ;

[0079] Among them, represents the mean value of represents the standard deviation of represents the n th standardized data point;

[0080] Selecting a distance metric, the distance from each data point to its th nearest neighbor :

[0081] ;

[0082] Among them, Represents a data point and the th nearest neighbor distance between; Represents the th nearest neighbor , Represents the distance from the data point to its th nearest neighbor ;

[0083] Calculate the reachability distance for each data point :

[0084] ;

[0085] wherein, Represents the neighborhood feature of the data point of, neighborhood feature, Represents the distance between the data point and the data point ;

[0086] Calculate the local reachability density for each data point :

[0087] ;

[0088] wherein, Represents the number of data points in the neighborhood of the data point , the local reachability density of the data point , Represents the neighborhood of the data point ;

[0089] Calculate the local outlier factor value for each data point :

[0090] ;

[0091] wherein, Represents the local outlier factor value of the data point , respectively represent the local reachability densities of the data points and the data point ;

[0092] Based on the above calculations, obtain the local outlier factor value for each data point, and select a threshold , and perform outlier judgment.

[0093] Among them, the setting of the threshold can be determined according to specific experiments and data analysis, and the general empirical value is between 1.5 and 2.

[0094] Suppose we have a dataset that contains the following features:

[0095] Leaf density ( ), the number or mass of leaves per unit area.

[0096] Bending angle ( ), the degree of bending of plant branches or leaves, which can be measured by an angle.

[0097] Plant height ( ), the vertical height of the plant from the root to the top.

[0098] Leaf angle ( ), the inclination angle of the leaf relative to the stem or branch.

[0099]

[0100] Subsequent steps:

[0101] Data standardization: Standardize each feature.

[0102] Calculate the k-distance: Select an appropriate distance metric (such as the Euclidean distance) and calculate the distance from each data point to its th nearest neighbor.

[0103] Calculate the reachability distance: Calculate the reachability distance of each data point.

[0104] Calculate the local reachability density: Calculate the local reachability density of each data point.

[0105] Calculate the local outlier factor (LOF): Calculate the LOF value of each data point.

[0106] The LOF values obtained after the calculation are as follows:

[0107]

[0108] In this example, the LOF value of the data point (50, 45, 300, 90) is 3.5, which is significantly higher than other data points, indicating that this is an outlier.

[0109] In the embodiment of the present invention, the process of comprehensively evaluating the health status of plants based on the anomaly detection results corresponds to the following relational expression:

[0110] ;

[0111] Among them, represents at the time pointt The health status of the plant under denotes the comprehensive adjustment factor, denotes the number of extracted pose features, denotes the pose feature weight factor, denotes at the time point t the real-time data of the pose feature under denotes at the time point t the abnormal detection result matrix of the pose feature under denotes the integral adjustment factor, denotes from time 0 to the time point t in between, denotes at the time point the incremental change data matrix of the pose feature under denotes at the time point the environmental response matrix of the pose feature under denotes the state adjustment factor for controlling the influence of plant state data, denotes at the time point the overall plant state data matrix under

[0112] In the process of comprehensively evaluating the health status of the plant, the weighted summation part of the present invention comprehensively considers various factors affecting plant health by performing weighted summation on various pose features, and the weights can be adjusted according to the importance of different features to flexibly cope with different environments and plant species.

[0113] In addition, the integral part considers the cumulative changes of pose features within a time period, reflects the dynamic changes of pose features and environmental responses, avoids the limitations of single time point data, can capture the dynamic changes of pose features, and provides a comprehensive and accurate health status assessment.

[0114] Figure 4 is a flowchart for establishing a virtual reality model of plant growth provided by an embodiment of the present invention, setting an environmental parameter adjustment interface, and analyzing the growth pose changes in different growth environment data. Establishing the virtual reality model of plant growth, setting the environmental parameter adjustment interface, and analyzing the growth pose changes in different growth environment data specifically include:

[0115] S310, obtaining the abnormal pose analysis result. If there is no abnormal pose, analyze the current growth environment data; if there is an abnormal pose, based on the current growth environment data, establish several growth environment control groups;

[0116] S320. When there is no abnormal posture, a virtual reality model of plant growth is established by combining the analysis results of the growth environment data. Based on the current growth environment data, the future growth posture change results of the plant are generated.

[0117] When there is an abnormal posture, a virtual reality model of plant growth is established, and the future growth posture change results of the plant under different control groups are generated. The virtual reality model of plant growth with no abnormal posture or the smallest degree of abnormal posture, and the corresponding control group data are identified.

[0118] In the embodiment of the present invention, the process of establishing a virtual reality model of plant growth by combining the analysis results of the growth environment data when there is no abnormal posture corresponds to the following relational expression:

[0119] ;

[0120] Wherein, represents the virtual reality model under normal conditions, respectively represent 3 different adjustment factors, represents the real-time data of the environmental parameter t at the time point i , represents the environmental parameter matrix at the time point ; represents the overall plant state data matrix at the time point ; represents the plant posture feature data matrix at the time point t ; represents the posture feature weight matrix at the time point t .

[0121] In the embodiment of the present invention, when there is an abnormal posture, the process of establishing a virtual reality model of plant growth corresponds to the following relational expression:

[0122] ;

[0123] Wherein, represents the virtual reality model under abnormal conditions, represents the number of growth environment control groups, represents the control group weight factor, represents the model data matrix of the control group t at the time point , represents the control group adjustment factor, represents the number of types of environmental parameters within each control group, Represents the environmental parameters k and the weight factor; Represents at the time point t under the control group the real-time data of the environmental parameters k within; Represents at the time point t the real-time data of the pose characteristics k under; Represents the integral adjustment factor, represents the time point under the control group the cumulative environmental and pose characteristic data.

[0124] During the process of establishing the virtual reality model under normal conditions, by performing weighted summation on the environmental parameters and pose characteristic data, various factors affecting plant growth are comprehensively considered, and the adjustment factor can be adjusted according to the importance of different parameters, flexibly responding to different environments and plant species, providing the virtual reality model output under normal conditions, and ensuring the comprehensiveness and accuracy of the model.

[0125] During the process of establishing the virtual reality model under abnormal conditions, by establishing multiple control groups and analyzing the growth pose changes of plants in different environments, the integral part considers the cumulative changes of the environment and pose characteristics within a time period, reflects the dynamic changes of the pose characteristics and environmental responses, provides the virtual reality model output under abnormal conditions, and ensures the adaptability and accuracy of the model in different environments.

[0126] Figure 5 The following is a structural block diagram of a pose capture system based on virtual reality provided by an embodiment of the present invention. As Figure 5 shown, a pose capture system based on virtual reality, the system includes:

[0127] An environmental state and pose capture module 100, configured to obtain the growth environment data of the current plant, and capture the pose data of the plant in real time through a camera, and extract specific pose characteristics from the pose data;

[0128] A pose state evaluation and analysis module 200, configured to analyze the extracted pose characteristics, and identify and determine whether the current plant has abnormal poses;

[0129] A virtual reality connection module 300, configured to establish a virtual reality model of plant growth respectively when the plant has abnormal poses and when the plant does not have abnormal poses, and set an environmental parameter adjustment interface to analyze the growth pose changes in different growth environment data;

[0130] The optimal state analysis module 400 is configured to obtain optimal growth environment data based on the growth posture change data and generate a report.

[0131] Figure 6 The following is the structural block diagram of the environmental state and posture capture module provided by the embodiment of the present invention, as Figure 6 shown, the environmental state and posture capture module includes:

[0132] The environmental sensing unit 110 is configured to collect various environmental parameters in the plant growth environment in real time through sensors and establish an environmental parameter set to store the data.

[0133] The posture capture unit 120 is configured to capture the posture of the plant from different angles and extract posture feature information, including but not limited to: leaf angle, leaf morphological change, branch curvature, plant height.

[0134] Figure 7 The following is the structural block diagram of the posture state evaluation and analysis module provided by the embodiment of the present invention, as Figure 7 shown, the posture state evaluation and analysis module includes:

[0135] The abnormal posture detection unit 210 is configured to establish an abnormal detection model, analyze the extracted plant posture features, and judge whether there is an abnormal posture according to the state data of all plants.

[0136] The health evaluation unit 220 is configured to comprehensively evaluate the health state of the plant based on the abnormal detection result and analyze the change trend of the plant.

[0137] Figure 8 The following is the structural block diagram of the virtual reality connection module provided by the embodiment of the present invention, as Figure 8 shown, the virtual reality connection module includes:

[0138] The abnormal state analysis unit 310 is configured to obtain the abnormal posture analysis result. If there is no abnormal posture, analyze the current growth environment data; if there is an abnormal posture, establish several growth environment control groups based on the current growth environment data.

[0139] The virtual reality model generation unit 320 is configured to, when there is no abnormal posture, establish a virtual reality model of plant growth in combination with the analysis result of the growth environment data, and generate the future growth posture change result of the plant based on the current growth environment data.

[0140] When there is an abnormal posture, establish a virtual reality model of plant growth, generate the future growth posture change result of the plant under different control groups, and identify the virtual reality model of plant growth with no abnormal posture or the smallest degree of abnormal posture, as well as the corresponding control group data.

[0141] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0142] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0143] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0144] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several variations and improvements can be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

[0145] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A posture capture method based on virtual reality, characterized in that: The method comprises the following steps: Obtain the current plant growth environment data, capture the plant posture data in real time through the camera, and extract posture features from the posture data; Analyze the extracted posture features to identify and determine whether the current plant has an abnormal posture; A plant growth virtual reality model is established when the plant has an abnormal posture and when the plant does not have an abnormal posture, and an environmental parameter adjustment interface is set to analyze the growth posture changes in different growth environment data; Based on the growth posture change data, obtain the optimal growth environment data and generate a report; The method of obtaining the growth environment data of the current plant, capturing the posture data of the plant in real time through a camera, and extracting posture features from the posture data specifically includes: Various environmental parameters in the plant growth environment are collected in real time through sensors, and an environmental parameter set is established to store the data; Capture the posture of plants from different angles and extract posture feature information, including but not limited to: leaf angle, leaf morphology changes, branch curvature, and plant height.

2. A virtual reality based gesture capture method according to claim 1, characterized in that: The process of collecting various environmental parameters in the plant growth environment in real time through sensors and establishing an environmental parameter set to store data corresponds to the following relationship: ； in, Indicates the total length of the time period, Indicates a point in time, Indicates at a point in time t A comprehensive set of environmental parameters under Indicates environmental parameters i The weight factor of Indicates at a point in time t Environmental parameters i Real-time data, A natural exponential function that represents the nonlinear effects of environmental conditions, represents the adjustment factor used to control the influence of the exponential function on the final result, represents the attenuation factor used to adjust the decay speed in the exponential function, Indicates the number of environmental parameter types, Table of environmental conditions, Indicates environmental conditions j The weight factor of Indicates at a point in time t Lower environmental conditions j real-time data.

3. A virtual reality based gesture capture method according to claim 2, characterized in that: The step of analyzing the extracted posture features to identify and determine whether the current plant has an abnormal posture specifically includes: Establish an anomaly detection model, analyze the extracted plant posture features, and determine whether there is an abnormal posture based on the status data of all plants; Based on the abnormal detection results, the health status of the plants is comprehensively evaluated and the plant change trends are analyzed.

4. A method for capturing gestures based on virtual reality according to claim 3, characterized in that: The process of comprehensively evaluating the health status of the plant based on the abnormal detection results corresponds to the following relationship: ； in, Indicates at a point in time t The health of the plants below, represents the comprehensive regulatory factor, represents the number of extracted posture features, Indicates posture characteristics The weight factor of Indicates at a point in time t Lower posture features Real-time data, Indicates at a point in time t Lower posture features The anomaly detection result matrix, represents the integral adjustment factor, Indicates 0 to time point t The time points between Indicates at a point in time The incremental change data matrix of the posture feature is: Indicates at a point in time The environmental response matrix of the posture feature is represents a state adjustment factor for controlling the influence of plant state data, Indicates at a point in time Below is the overall plant status data matrix.

5. A method for capturing gestures based on virtual reality according to claim 4, characterized in that: The step of judging whether there is an abnormal posture based on the status data of all plants specifically includes: Read all the status data of the plant posture and create a dimension vector: ； in, Indicates all status data, Indicates n data points; Standardize all acquired data: ； in, express The mean of express The standard deviation of Indicates n Normalized data points; Choose a distance metric, each data point To its Nearest Neighbor Distance: ； in, Represents data points and Nearest Neighbor The distance between Indicates Nearest Neighbor , Represents data points To its Nearest Neighbor distance; Calculate each data point The reachable distance: ； in, Represents data points of Neighborhood features, Represents data points and data points The actual distance between Calculate each data point The local reachable density of is: ； in, Represents data points of The number of data points in the neighborhood, Data Points The local reachable density of Represents data points of Neighborhood; Calculate each data point The local anomaly factor value of is: ； in, Represents data points The local anomaly factor value of Represents data points and data points The local reachable density of Based on the above calculation, the local anomaly factor value of each data point is obtained and the threshold is selected , make abnormal judgment.

6. A method for capturing gestures based on virtual reality according to claim 5, characterized in that: The plant growth virtual reality model is established, and an environmental parameter adjustment interface is set to analyze the growth posture changes in different growth environment data, specifically including: Obtain abnormal posture analysis results. If there is no abnormal posture, analyze the current growth environment data; if there is an abnormal posture, establish several growth environment control groups based on the current growth environment data; When there is no abnormal posture, a virtual reality model of plant growth is established in combination with the analysis results of the growth environment data, and the future growth posture change results of the plant are generated based on the current growth environment data; When there is an abnormal posture, a plant growth virtual reality model is established to generate the results of future plant growth posture changes under different control groups, and identify the plant growth virtual reality model with no abnormal posture or the smallest abnormal posture, as well as the corresponding control group data.

7. A method for capturing gestures based on virtual reality according to claim 6, characterized in that: When there is no abnormal posture, the process of establishing a virtual reality model of plant growth in combination with the growth environment data analysis results corresponds to the following relationship: ； in, Represents a virtual reality model without abnormal conditions. Represents three different regulatory factors, Indicates at a point in time t Environmental parameters i Real-time data, Indicates at a point in time The environmental parameter matrix under Indicates at a point in time The overall plant status data matrix under Indicates at a point in time t The plant posture feature data matrix under Indicates at a point in time t The pose feature weight matrix under .

8. The method for capturing gestures based on virtual reality according to claim 7, characterized in that: When there are abnormal postures, the process of establishing a plant growth virtual reality model corresponds to the following relationship: ； in, A virtual reality model representing an abnormal situation, represents the number of growth environment control groups, The control group The weight factor of Indicates at a point in time t Lower control group The model data matrix, The control group The regulating factor, represents the number of environmental parameter types in each control group, Indicates environmental parameters k The weight factor of Indicates at a point in time t In the control group Internal environmental parameters k Real-time data; Indicates at a point in time t Lower posture features k Real-time data; represents the integral adjustment factor, Indicates time point Lower control group The accumulated environment and posture feature data.

9. A virtual reality-based gesture capture system, the system applying the virtual reality-based gesture capture method according to any one of claims 1 to 8, characterized in that: The system comprises: The environment state and posture capture module is used to obtain the current plant growth environment data, and to capture the plant posture data in real time through the camera, and to extract posture features from the posture data; The posture state evaluation and analysis module is used to analyze the extracted posture features, identify and determine whether the current plant has an abnormal posture; A virtual reality connection module is used to establish a plant growth virtual reality model when the plant has an abnormal posture and when the plant does not have an abnormal posture, and to set an environmental parameter adjustment interface to analyze the growth posture changes in different growth environment data; The optimal state analysis module is used to obtain the optimal growth environment data based on the growth posture change data and generate a report.

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