A high-efficiency dynamic visual intelligent image analysis system for capturing images

Abstract

The application discloses a kind of high-efficiency capture object image dynamic vision intelligent image analysis systems, belong to image analysis technical field.High-efficiency capture object image dynamic vision intelligent image analysis system, including dynamic capture acquisition module, the motion state of moving object is collected in real time, after collecting object running total program image, frame processing is carried out, each frame picture is obtained, contour edge marking module, the object in each frame picture is cut out to form object image, the edge boundary of object image is mapped and marked, edge boundary marking point is obtained, the center point position of object image is determined, and key position marker point is selected in the edge boundary of object image.The high-efficiency capture object image dynamic vision intelligent image analysis system, compared with the traditional fixed frame rate sampling and static contour extraction, can effectively capture the continuous trajectory of high-speed moving object, and solve the problem of object image edge collection distortion under complex environment.

Description

Technical Field

[0001] This invention relates to the field of image analysis technology, and more specifically, to a highly efficient visual intelligent image analysis system for capturing dynamic images of objects. Background Technology

[0002] With the rapid development of industrial automation, intelligent monitoring and virtual reality technologies, the demand for accurate capture and real-time analysis of the dynamic motion of objects is becoming increasingly urgent.

[0003] In existing technologies, dynamic image analysis typically employs fixed frame rate sampling and static contour extraction methods, which cannot effectively capture the continuous trajectory of high-speed moving objects. Dynamic vision systems mainly rely on two-dimensional image acquisition from a single perspective, and are prone to edge recognition distortion under complex background interference. Moreover, most systems only remain at the level of two-dimensional trajectory monitoring and lack the ability to transform planar motion data into three-dimensional spatial models. They fail to systematically solve the problem of high-precision tracking and closed-loop control of dynamic objects in complex scenes, resulting in limited efficiency of three-dimensional mapping of dynamic trajectories and limited accuracy of subsequent deviation analysis and adaptive control. Summary of the Invention

[0004] The purpose of this invention is to provide a highly efficient intelligent image analysis system for capturing dynamic images of objects, in order to solve the problems mentioned in the background art above:

[0005] To achieve the above objectives, the present invention provides the following technical solution: A high-efficiency dynamic visual intelligent image analysis system for capturing images of objects includes a dynamic capture and acquisition module, which captures the motion state of moving objects in real time, and performs frame segmentation processing after capturing the total motion process of the object to obtain images of each frame. The contour edge marking module extracts objects from each frame of the image to form object images, maps and marks the edges of the object images to obtain edge mark points, determines the center point of the object image, and selects key position marks in the edge boundaries of the object image. The feature analysis and conversion module selects the marker point with the maximum distance from the center point from the key position markers as the base point, uses the distance from the base point to the center point as the base radius, constructs a circle with the center point as the center position as the base circle, and converts the base circle into a three-dimensional sphere. The spatiotemporal trajectory model construction module scales the environment of the object's entire motion process proportionally to form a basic environment model, and scales the object's entire motion trajectory proportionally to form a basic motion trajectory. The real-time trajectory mapping module maps the motion state of a 3D sphere on its basic motion trajectory in real time. The trajectory offset analysis module calculates the motion deviation of the 3D sphere on its motion trajectory based on the real-time motion state of the 3D sphere. The execution module, when the three-dimensional sphere deviates from its basic motion trajectory, formulates adjustment data based on the amount of deviation in the object's motion trajectory, and packages and outputs the data. The decision output module adjusts the object's motion deviation based on the motion trajectory deviation data.

[0006] Preferably, the contour edge marking module includes a contour mapping unit, a center point marking unit, and a key point extraction unit; The steps for the contour mapping unit to map and mark the edge boundaries of an object image are as follows: Step 1: Create a two-dimensional grid line on a white background and determine the reference coordinate point. Map the object image onto the two-dimensional grid line to form a mapping area. Color the mapping area to be different from the white background color, and form a color boundary between the white background and the mapping area color. Step 2: Establish a simulated ant colony in the mapping area. The ant colony crawls randomly in the mapping area. When the ant colony encounters a color boundary line that causes visual interference, the ant colony will stop at the color boundary line. Use a two-dimensional grid line to record several precise coordinate points of the ant colony at the stop point of the color boundary line.

[0007] Preferably, the center point marking unit determines the center point position of the object image based on the precise coordinate points recorded by the two-dimensional grid lines in the plane, and the target coordinate point set of the object image. Calculate the coordinates of the center point The formula is as follows: ; ; in, This represents the total number of discrete coordinate points. Indicates from the first point to the second point. Add the values ​​of each point together. Indicates the first The x-coordinates of discrete coordinate points Indicates the first The ordinates of discrete coordinate points; The key point extraction unit selects key location markers based on several coordinate points recorded by the two-dimensional grid lines on the plane.

[0008] Preferably, the feature analysis and conversion module includes a basic distance unit, a basic circle construction unit, and a three-dimensional sphere conversion unit; The basic interval unit selects the coordinate point that is furthest from the center point from the key position markers based on the two-dimensional grid lines in the plane, and uses the coordinate point with the largest distance as the basis; Construct a basic circular unit with the center point as the center and the distance from the center point as the basic radius, and construct a circle as the basic circle; The 3D Sphere Conversion Unit converts the constructed base circle into a 3D sphere using 3D conversion software.

[0009] Preferably, the spatiotemporal trajectory model construction module includes a proportional scaling unit and a basic trajectory construction unit; The proportional scaling unit scales the object's movement proportionally to the environment and facilities in which it is located, forming a basic environmental model. The scaled model retains the position, spacing, angle, and layout structure of the facilities in the real environment. The basic trajectory construction unit scales the object's entire motion trajectory proportionally to form a basic motion trajectory, which is then displayed in the scaled basic model.

[0010] Preferably, the real-time trajectory mapping module displays the trajectory of the three-dimensional sphere moving on the basic motion trajectory in real time through 3D simulation animation.

[0011] Preferably, the trajectory offset analysis module calculates the motion deviation of the three-dimensional sphere on its motion trajectory, and the steps are as follows: S1: Determine the center position of the 3D sphere and the position of the 3D sphere moving to the basic motion trajectory in any frame; S2: Based on the qualified motion trajectory of the object in the database on the basic motion trajectory, calculate the distance between the center of the 3D sphere in any frame and the basic motion trajectory, obtain the motion deviation of the 3D sphere on the basic motion trajectory, and determine whether the 3D sphere in any frame has deviated from the basic motion trajectory.

[0012] Preferably, when the deviation of the three-dimensional sphere on the basic motion trajectory is within the normal range, the data is packaged and input into the decision output module, and the decision output module does not adjust the environmental equipment.

[0013] Preferably, when the deviation of the three-dimensional sphere from its basic motion trajectory is not within the normal range, data is input to the execution module, which packages the data and inputs it into the decision output module, which then adjusts the environmental equipment.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1) This invention constructs a white background planar two-dimensional grid line and determines the reference coordinate points of the planar two-dimensional grid line. Then, the object image is mapped onto the planar two-dimensional grid line through a contour mapping unit, forming a mapping area on the planar two-dimensional grid line. Finally, the mapping area is colored to distinguish it, achieving a color boundary line between the white background and the colored mapping area. A simulated ant colony is established in the mapping area. The ant colony crawls randomly in the mapping area. When the ant colony encounters the color boundary line causing visual interference, the ant colony will stop at the color boundary line. Several precise coordinate points of the ant colony at the stopping point of the color boundary line are recorded using the planar two-dimensional grid line. Based on several... Precise coordinate points determine the center point coordinates of the object image. Key coordinate points of the object image are selected by the key point extraction unit. The coordinate point with the largest distance from the center point is selected from multiple key position markers by the basic distance unit. A basic circle unit is constructed with the center point as the center and the distance from the basic point to the center point as the basic radius. The constructed basic circle is converted into a 3D sphere by the 3D conversion unit through 3D conversion software. Compared with the traditional fixed frame rate sampling and static contour extraction, it can effectively capture the continuous trajectory of high-speed moving objects and solve the problem of image edge acquisition distortion in complex environments.

[0015] 2) This invention, based on the environment and facilities where the object is moving, pre-scales the environment and facilities in advance using a proportional scaling unit to form a basic environment model. Then, a basic trajectory construction unit scales the entire motion trajectory of the object to form a basic motion trajectory, which is displayed in the scaled basic model. The three-dimensional sphere is mapped onto the basic motion trajectory. The trajectory offset analysis module analyzes and calculates the motion deviation of the three-dimensional sphere on the basic motion trajectory. Based on the motion deviation data, it is determined whether the object's motion trajectory needs to be adjusted by external devices. This solves the problem of high-precision tracking and closed-loop control of dynamic objects in complex scenes, improves the efficiency of three-dimensional mapping during the object's movement, and ensures the accuracy of subsequent deviation analysis and adaptive control. Attached Figure Description

[0016] Figure 1 Overall flowchart of a visual intelligent image analysis system for efficiently capturing dynamic images of objects; Figure 2 Diagram of the contour edge marking module for an efficient visual intelligent image analysis system for capturing dynamic images of objects; Figure 3 A diagram of the feature analysis and conversion module for an efficient visual intelligent image analysis system for capturing dynamic images of objects; Figure 4 A module diagram for constructing a spatiotemporal trajectory model for an efficient visual intelligent image analysis system that captures dynamic images of objects; Figure 5This is a basic trajectory diagram for a visual intelligent image analysis system that efficiently captures the dynamics of objects. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0019] Please see Figure 1 - Figure 5 A high-efficiency dynamic visual intelligent image analysis system for capturing images of objects includes a dynamic capture and acquisition module, which captures the motion state of moving objects in real time, and performs frame segmentation processing after capturing the total motion process of the object to obtain images of each frame. The contour edge marking module extracts objects from each frame of the image to form object images, maps and marks the edges of the object images to obtain edge mark points, determines the center point of the object image, and selects key position marks in the edge boundaries of the object image. The feature analysis and conversion module selects the marker point with the maximum distance from the center point from the key position markers as the base point, uses the distance from the base point to the center point as the base radius, constructs a circle with the center point as the center position as the base circle, and converts the base circle into a three-dimensional sphere. The spatiotemporal trajectory model construction module scales the environment of the object's entire motion process proportionally to form a basic environment model, and scales the object's entire motion trajectory proportionally to form a basic motion trajectory. The real-time trajectory mapping module maps the motion state of a 3D sphere on its basic motion trajectory in real time. The trajectory offset analysis module calculates the motion deviation of the 3D sphere on its motion trajectory based on the real-time motion state of the 3D sphere. The execution module, when the three-dimensional sphere deviates from its basic motion trajectory, formulates adjustment data based on the amount of deviation in the object's motion trajectory, and packages and outputs the data. The decision output module adjusts the object's motion deviation based on the motion trajectory deviation data.

[0020] A white background 2D grid is pre-constructed, and the reference coordinates of the grid are determined. The object image is then mapped onto the grid using contour mapping units, forming a mapping area. This mapping area is then colored to create a color boundary between the white background and the colored mapping area. A simulated ant colony is established within the mapping area, crawling randomly. When the ants encounter the color boundary causing visual disturbance, they pause at that point. Several precise coordinates of these pauses are recorded using the 2D grid. The coordinates of the center point of the object image are determined by the coordinate point extraction unit. The key coordinate points of the object image are selected by the key point extraction unit. The coordinate point with the largest distance from the center point is selected from multiple key position markers by the basic distance unit. The basic circle unit is constructed with the center point as the center and the distance from the basic point to the center point as the basic radius. The constructed basic circle is converted into a three-dimensional sphere by the three-dimensional conversion software through the three-dimensional sphere conversion unit. Compared with the traditional fixed frame rate sampling and static contour extraction, it can effectively capture the continuous trajectory of high-speed moving objects and solve the problem of image edge acquisition distortion in complex environments.

[0021] The contour edge marking module includes a contour mapping unit, a center point marking unit, and a key point extraction unit; The steps for the contour mapping unit to map and mark the edge boundaries of an object image are as follows: Step 1: Create a two-dimensional grid line on a white background and determine the reference coordinate point. Map the object image onto the two-dimensional grid line to form a mapping area. Color the mapping area to be different from the white background color, and form a color boundary between the white background and the mapping area color. Step 2: Establish a simulated ant colony in the mapping area. The ant colony crawls randomly in the mapping area. When the ant colony encounters a color boundary line that causes visual interference, the ant colony will stop at the color boundary line. Use a two-dimensional grid line to record several precise coordinate points of the ant colony at the stop point of the color boundary line.

[0022] The center point marker unit determines the center point position of the object image based on the precise coordinate points recorded by the two-dimensional grid lines, forming the target coordinate point set of the object image. Calculate the coordinates of the center point The formula is as follows: ; ; in, This represents the total number of discrete coordinate points. Indicates from the first point to the second point. Add the values ​​of each point together. Indicates the first The x-coordinates of discrete coordinate points Indicates the first The ordinates of discrete coordinate points; The key point extraction unit selects key location markers based on several coordinate points recorded by the two-dimensional grid lines on the plane.

[0023] The feature analysis and transformation module includes basic fixed-distance units, basic circular units, and three-dimensional sphere transformation units; The basic interval unit selects the coordinate point that is furthest from the center point from the key position markers based on the two-dimensional grid lines in the plane, and uses the coordinate point with the largest distance as the basis; Construct a basic circular unit with the center point as the center and the distance from the center point as the basic radius, and construct a circle as the basic circle; The 3D Sphere Conversion Unit converts the constructed base circle into a 3D sphere using 3D conversion software.

[0024] The spatiotemporal trajectory model construction module includes a proportional scaling unit and a basic trajectory construction unit; The proportional scaling unit scales the object's movement proportionally to the environment and facilities it is in, forming a basic environment model. The scaled model retains the position, spacing, angle, and layout of the facilities in the real environment. The basic trajectory building unit scales the object's entire motion trajectory proportionally to form the basic motion trajectory, which is then displayed in the scaled basic model.

[0025] Based on the environment and facilities where the object is moving, the environment and facilities are scaled proportionally in advance using a proportional scaling unit to form a basic environment model. The basic trajectory construction unit then scales the entire motion trajectory of the object proportionally to form a basic motion trajectory, which is displayed in the scaled basic model. The 3D sphere is mapped onto the basic motion trajectory. The trajectory offset analysis module analyzes and calculates the motion deviation of the 3D sphere on the basic motion trajectory. Based on the motion deviation data, it is determined whether the object's motion trajectory needs to be adjusted by external equipment. This solves the problem of high-precision tracking and closed-loop control of dynamic objects in complex scenes, improves the efficiency of 3D mapping during object movement, and ensures the accuracy of subsequent deviation analysis and adaptive control.

[0026] The real-time trajectory mapping module displays the trajectory of a three-dimensional sphere moving on the basic motion trajectory in real time through 3D simulation animation.

[0027] The trajectory offset analysis module calculates the motion deviation of the 3D sphere along its trajectory. The steps are as follows: S1: Determine the center position of the 3D sphere and the position of the 3D sphere moving to the basic motion trajectory in any frame; S2: Based on the qualified motion trajectory of the object in the database on the basic motion trajectory, calculate the distance between the center of the 3D sphere in any frame and the basic motion trajectory, obtain the motion deviation of the 3D sphere on the basic motion trajectory, and determine whether the 3D sphere in any frame has deviated from the basic motion trajectory.

[0028] When the deviation of the three-dimensional sphere in the basic motion trajectory is within the normal range, the data is packaged and input into the decision output module, which does not adjust the environmental equipment.

[0029] When the deviation of the three-dimensional sphere from its basic motion trajectory is not within the normal range, data is input to the execution module. The execution module packages the data and inputs it into the decision output module, which then adjusts the environmental equipment.

[0030] The usage steps of this invention are as follows: Taking the deviation of an object's motion trajectory in an industrial production line as an example, during the processing of the object, a multi-directional dynamic video recorder is used to collect the object's real-time motion state, forming a total motion image of the object. This total motion image is divided into individual real-time motion images using single frames as segmentation points. A digital computer is used to cut out the object from each frame, forming an object image. A white background planar two-dimensional grid is pre-constructed, and the reference coordinates of the planar two-dimensional grid lines are determined. The object image is then mapped onto the planar two-dimensional grid lines through a contour mapping unit, forming a mapping area on the planar two-dimensional grid lines. Finally, the mapping area is colored. To differentiate the background and the colored mapping area, a color boundary is created. A simulated ant colony is established in the mapping area, crawling erratically. When the ants encounter the color boundary causing visual disturbance, they pause at the boundary. A two-dimensional grid is used to record several precise coordinates of these pauses. Based on these precise coordinates, the center point coordinates of the object are determined. Key point extraction units select key coordinates, and a basic distance unit selects the coordinates furthest from the center point among multiple key location markers. A basic circle unit is constructed with the center point as the center and the distance from the center point as the base radius. A three-dimensional sphere conversion unit is then used to construct the circle. The basic circle is converted into a 3D sphere using 3D conversion software. Based on the environment and facilities surrounding the object's movement, a basic environmental model is created by scaling the environment and facilities proportionally using a scaling unit. Then, a basic trajectory is created by scaling the object's entire motion trajectory proportionally using a basic trajectory construction unit, and displayed in the scaled basic model. The 3D sphere is mapped onto this basic trajectory. The trajectory offset analysis module calculates the 3D sphere's deviation from the basic trajectory. Based on this deviation data, it is determined whether external equipment is needed to adjust the object's trajectory. This approach involves pre-constructing a white background plane with a 2D grid and determining the reference coordinates of the grid lines. The object image is then mapped onto a two-dimensional planar grid line using a contour mapping unit, forming a mapping area on the grid line. This mapping area is then colored to create a color boundary between the white background and the colored mapping area. A simulated ant colony is established within the mapping area, crawling randomly. When the ants encounter a color boundary line causing visual disturbance, they pause at that line. The two-dimensional grid line is used to record several precise coordinates of these pauses. Based on these precise coordinates, the center point coordinates of the object image are determined. A key point extraction unit selects key coordinates of the object image, and a basic distance unit selects the coordinate point furthest from the center point among multiple key position markers.A basic circular unit is constructed with the center point as the center and the distance from the center point as the radius. This circular unit is then converted into a 3D sphere using 3D conversion software. Compared to traditional methods using fixed frame rate sampling and static contour extraction, this effectively captures the continuous trajectory of high-speed moving objects and solves the problem of image edge distortion in complex environments. Based on the environment and facilities surrounding the object's movement, a scaling unit is used to scale the environment and facilities proportionally in advance, forming a basic environment model. A basic trajectory construction unit then scales the entire motion trajectory of the object proportionally to form a basic motion trajectory, which is displayed in the scaled basic model. The 3D sphere is mapped onto this basic motion trajectory. A trajectory offset analysis module analyzes and calculates the motion deviation of the 3D sphere on the basic motion trajectory. Based on this deviation data, it is determined whether external equipment is needed to adjust the object's trajectory. This solves the problem of high-precision tracking and closed-loop control of dynamic objects in complex scenes, improves the efficiency of 3D mapping during object movement, and ensures the accuracy of subsequent deviation analysis and adaptive control.

[0031] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A highly efficient visual intelligent image analysis system for capturing dynamic images of objects, characterized in that, include: The dynamic capture module captures the motion state of moving objects in real time, and after capturing the total motion process of the object, it performs frame segmentation processing to obtain individual frame images. The contour edge marking module extracts objects from each frame of the image to form object images, maps and marks the edges of the object images to obtain edge mark points, determines the center point of the object image, and selects key position marks in the edge boundaries of the object image. The feature analysis and conversion module selects the marker point with the maximum distance from the center point from the key position markers as the base point, uses the distance from the base point to the center point as the base radius, constructs a circle with the center point as the center position as the base circle, and converts the base circle into a three-dimensional sphere. The spatiotemporal trajectory model construction module scales the environment of the object's entire motion process proportionally to form a basic environment model, and scales the object's entire motion trajectory proportionally to form a basic motion trajectory. The real-time trajectory mapping module maps the motion state of a 3D sphere on the basic motion trajectory in real time. The trajectory offset analysis module calculates the motion deviation of the 3D sphere on its motion trajectory based on the real-time motion state of the 3D sphere. The execution module, when the three-dimensional sphere deviates from its basic motion trajectory, formulates adjustment data based on the amount of deviation in the object's motion trajectory, and packages and outputs the data. The decision output module adjusts the object's motion deviation based on the motion trajectory deviation data.

2. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 1, characterized in that, The contour edge marking module includes a contour mapping unit, a center point marking unit, and a key point extraction unit; The steps for the contour mapping unit to map and mark the edge boundaries of an object image are as follows: Step 1: Create a two-dimensional grid line on a white background and determine the reference coordinate point. Map the object image onto the two-dimensional grid line to form a mapping area. Color the mapping area to be different from the white background color, and form a color boundary between the white background and the mapping area color. Step 2: Establish a simulated ant colony in the mapping area. The ant colony crawls randomly in the mapping area. When the ant colony encounters a color boundary line that causes visual interference, the ant colony will stop at the color boundary line. Use a two-dimensional grid line to record several precise coordinate points of the ant colony at the stop point of the color boundary line.

3. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 2, characterized in that, The center point marking unit determines the center point position of the object image based on the precise coordinate points recorded by the two-dimensional grid lines in the plane, and the target coordinate point set of the object image. Calculate the coordinates of the center point The formula is as follows: ； ； in, This represents the total number of discrete coordinate points. Indicates from the 1st point to the 2nd point. Add the values ​​of each point together. Indicates the first The x-coordinates of discrete coordinate points Indicates the first The ordinates of discrete coordinate points; The key point extraction unit selects key location markers based on several coordinate points recorded by the two-dimensional grid lines on the plane.

4. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 1, characterized in that, The feature analysis and conversion module includes a basic distance unit, a basic circle construction unit, and a three-dimensional sphere conversion unit; The basic interval unit selects the coordinate point that is furthest from the center point from the key position markers based on the two-dimensional grid lines in the plane, and uses the coordinate point with the largest distance as the basis; Construct a basic circular unit with the center point as the center and the distance from the center point as the basic radius, and construct a circle as the basic circle; The 3D Sphere Conversion Unit converts the constructed base circle into a 3D sphere using 3D conversion software.

5. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 1, characterized in that, The spatiotemporal trajectory model construction module includes a proportional scaling unit and a basic trajectory construction unit; The proportional scaling unit scales the object's movement proportionally to the environment and facilities in which it is located, forming a basic environmental model. The scaled model retains the position, spacing, angle, and layout structure of the facilities in the real environment. The basic trajectory construction unit scales the object's entire motion trajectory proportionally to form a basic motion trajectory, which is then displayed in the scaled basic model.

6. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 1, characterized in that, The real-time trajectory mapping module displays the trajectory of a three-dimensional sphere moving on the basic motion trajectory in real time through 3D simulation animation.

7. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 6, characterized in that, The trajectory offset analysis module calculates the motion deviation of the three-dimensional sphere on its trajectory, and the steps are as follows: S1: Determine the center position of the 3D sphere and the position of the 3D sphere moving to the basic motion trajectory in any frame; S2: Based on the qualified motion trajectory of the object in the database on the basic motion trajectory, calculate the distance between the center of the 3D sphere in any frame and the basic motion trajectory, obtain the motion deviation of the 3D sphere on the basic motion trajectory, and determine whether the 3D sphere in any frame has deviated from the basic motion trajectory.

8. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 1, characterized in that, When the deviation of the three-dimensional sphere in the basic motion trajectory is within the normal range, the data is packaged and input into the decision output module, which does not adjust the environmental equipment.

9. The high-efficiency dynamic visual intelligent image analysis system for capturing objects according to claim 8, characterized in that, When the deviation of the three-dimensional sphere from its basic motion trajectory is not within the normal range, data is input to the execution module. The execution module packages the data and inputs it into the decision output module, which then adjusts the environmental equipment.

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