Man-machine interaction system based on visual big data analysis

Abstract

The invention relates to a man-machine interaction system based on visual big data analysis. The system comprises an instruction analysis device, a side capture device, a multi-layer enhancement device and a data analysis mechanism. The system is reasonable in design and simple to implement, and has a wide application prospect.

Description

Technical Field

[0001] The present invention relates to the field of human-computer interaction, and more specifically, to a human-computer interaction system based on visual big data analysis. Background Art

[0002] CN118701087A discloses a human-computer interaction device, system, method, program product and vehicle. The human-computer interaction device is used to obtain the driving environment information and / or intelligent driving control information of the vehicle, and construct an intelligent driving scene image according to the driving environment information and / or the intelligent driving control information; the human-computer interaction device is also used to send the intelligent driving scene image to a display device so that the intelligent driving scene image is displayed on the display device. In this way, the driving environment information and / or the intelligent driving control information are processed by the human-computer interaction device to obtain the intelligent driving scene image, and there is no need for the display device to perform rendering processing, which effectively reduces the delay in rendering the intelligent driving scene image, thereby improving the user experience.

[0003] CN118708090A discloses a design of a human-computer interaction interface, including a design framework and an interface layout, wherein the design framework constitutes the basic structure of the interface, including a one-key function area, a function echo area, a control area, and a miscellaneous area; the interface layout adopts a hierarchical dynamic layout, including a main icon and a status icon, wherein the main icon and the status icon perform circular rotation according to fixed coordinates through a software algorithm and are displayed in layers; the main icon is an operable graphic element on the one-key function area and the control area, and the status icon reflects the status of the functional object and is displayed in the function echo area. Through the present invention, users can directly operate the functional object on the interface through a new design framework, or directly operate the functional object in the storage medium or corresponding to the software algorithm according to certain language habits. This design method is efficient and has a good user experience for users. Summary of the invention

[0004] In order to solve the technical problems in related fields, the present invention provides a human-computer interaction system based on visual big data analysis, which can trigger the side capture device encapsulated in the A-pillar on the left side of the vehicle to perform image data capture actions on the left side traffic environment of the vehicle only when the left turn signal of the vehicle is turned on by the user, and perform real-time warning operations when it is intelligently determined that there are objects too close to the human body in the left side traffic environment of the vehicle, so as to avoid collision accidents with objects too close to the human body in the area where the driver's line of sight is blocked.

[0005] According to the present invention, a human-computer interaction system based on visual big data analysis is provided, the system comprising: A command parsing device connected to a left turn lamp of a vehicle, for issuing a first control command when the left turn lamp is turned on by a user, and for issuing a second control command when the left turn lamp is not turned on by the user; A side capture device, packaged in the A-pillar on the left side of the vehicle and connected to the instruction parsing device, is used to perform an image data capture action on the left side traffic environment of the vehicle when receiving the first control instruction, so as to obtain and output a side capture image; A multi-layer enhancement device, arranged inside a vehicle and comprising a morphological processing device, a bilateral filtering device and a contrast retaining device, wherein the bilateral filtering device is connected to the morphological processing device and the contrast retaining device respectively, and the morphological processing device is also connected to the side capture device, and is used to sequentially perform a morphological processing of first dilation and then corrosion on the received side capture image to obtain and output a corresponding morphologically processed image, the bilateral filtering device is used to perform a bilateral filtering processing on the received morphologically processed image to obtain and output a corresponding bilaterally filtered image, and the contrast retaining device is used to perform a processing of retaining a junction of two parts with obvious color or light-dark contrast in the received bilaterally filtered image to obtain and output a corresponding contrast-retained image; A data analysis mechanism is connected to the multi-layer enhancement device and includes a model training unit, a model application unit and a parameter configuration unit. The parameter configuration unit is respectively connected to the model training unit and the model application unit to complete the parameter configuration of the model training unit and the model application unit. The model training unit is used to perform multiple learning on the BP neural network to obtain the BP neural network that has completed multiple learning and output it as an artificial intelligence model. The model application unit is connected to the model training unit and is used to intelligently analyze the human object existence mark using an artificial intelligence model based on the curvature values ​​of various locations of the standard contour curve corresponding to the human object, the number of pixels of the contrast-preserved image, the clarity and signal-to-noise ratio of the contrast-preserved image, and the color component values ​​of each pixel of the contrast-preserved image. The human object existence mark is used to indicate whether there is a human object that is too close to the contrast-preserved image and whose depth of field is shallower than the set depth of field threshold.

[0006] The human-computer interaction system based on visual big data analysis of the present invention has a compact structure and wide application. Since the side capture device encapsulated in the A-pillar on the left side of the vehicle can be triggered only when the left turn lamp of the vehicle is turned on by the user, it is used to perform image data capture actions on the left side traffic environment of the vehicle, and when it is intelligently determined that there is an object too close to the human body in the left side traffic environment of the vehicle, a real-time warning operation is performed, thereby avoiding collision accidents with objects too close to the human body in the area where the driver's vision is blocked. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Those skilled in the art may better understand the numerous advantages of the present invention by referring to the accompanying drawings.

[0008] Figure 1 It is a structural schematic diagram of a human-computer interaction system based on visual big data analysis according to the primary embodiment of the present invention.

[0009] Figure 2 It is a structural schematic diagram of a human-computer interaction system based on visual big data analysis according to a secondary embodiment of the present invention.

[0010] Figure 3 It is a structural diagram of a human-computer interaction system based on visual big data analysis according to another embodiment of the present invention. DETAILED DESCRIPTION

[0011] The A-pillar, also known as A-pillar in foreign language, is the connecting pillar connecting the roof and the front cabin on the left and right front sides. In car magazines and car buying guides, you will often see terms like "A-pillar", "B-pillar" and "C-pillar". The A-pillar refers to the pillar between the windshield and the left and right front doors. The A-pillar, B-pillar and C-pillar of a car all have their own different functions, but at the same time they have their own contradictions, such as the contradiction between the field of view and rigidity of the A-pillar, and the contradiction between the rigidity and convenience of the B-pillar. The A-pillar is between the engine compartment and the cockpit, above the left and right rearview mirrors, and will block part of the driver's turning field of view, especially when turning left, so there are more points of concern.

[0012] Drivers will have a feeling that the angle of the driver's vision is always blocked to some extent. The feeling of wideness actually indicates a comfort problem, but in the eyes of car designers, this is a contradiction. Under normal circumstances, the driver's vision through the A-pillar has a binocular overlap angle of 5-6 degrees. If we start from the driver's comfort angle, the smaller the overlap angle, the better, and the thinner the A-pillar, the better. However, in the eyes of designers, there is a balance problem. Obviously, the high rigidity of the A-pillar must be guaranteed to reduce safety risks. So from this perspective, the smaller the A-pillar, the better. Therefore, how to use the A-pillar to ensure the safety of the car while supplementing the driver's obstructed field of vision is one of the technical problems that need to be solved at present.

[0013] Figure 1 1 is a schematic diagram of the structure of a human-computer interaction system based on visual big data analysis according to the primary embodiment of the present invention, the system comprising: A command parsing device connected to a left turn lamp of a vehicle, for issuing a first control command when the left turn lamp is turned on by a user, and for issuing a second control command when the left turn lamp is not turned on by the user; For example, the instruction parsing device includes a user input interface, a state detection unit and a main controller, and the state detection unit is used to detect the current turn-on state of the left turn lamp; A side capture device, packaged in the A-pillar on the left side of the vehicle and connected to the instruction parsing device, is used to perform an image data capture action on the left side traffic environment of the vehicle when receiving the first control instruction, so as to obtain and output a side capture image; A multi-layer enhancement device, arranged inside a vehicle and comprising a morphological processing device, a bilateral filtering device and a contrast retaining device, wherein the bilateral filtering device is connected to the morphological processing device and the contrast retaining device respectively, and the morphological processing device is also connected to the side capture device, and is used to sequentially perform a morphological processing of first dilation and then corrosion on the received side capture image to obtain and output a corresponding morphologically processed image, the bilateral filtering device is used to perform a bilateral filtering processing on the received morphologically processed image to obtain and output a corresponding bilaterally filtered image, and the contrast retaining device is used to perform a processing of retaining a junction of two parts with obvious color or light-dark contrast in the received bilaterally filtered image to obtain and output a corresponding contrast-retained image; A data analysis mechanism, connected to the multi-layer enhancement device and comprising a model training unit, a model application unit and a parameter configuration unit, wherein the parameter configuration unit is respectively connected to the model training unit and the model application unit, and is used to complete the parameter configuration of the model training unit and the model application unit, wherein the model training unit is used to perform multiple learning on the BP neural network to obtain the BP neural network that has completed multiple learning and output it as an artificial intelligence model, and the model application unit is connected to the model training unit, and is used to intelligently analyze the existence of a human object using an artificial intelligence model based on the curvature values ​​at various locations of the standard contour curve corresponding to the human object, the number of pixels of the contrast-retained image, the clarity and signal-to-noise ratio of the contrast-retained image, and the color component values ​​of each pixel of the contrast-retained image, wherein the human object existence flag is used to indicate whether there is a too-close human object in the contrast-retained image whose depth of field is shallower than a set depth of field threshold; Wherein, the side capture device is also used to stop executing the image data capture action on the left side traffic environment of the vehicle when receiving the second control instruction.

[0014] Figure 2 It is a structural schematic diagram of a human-computer interaction system based on visual big data analysis according to a secondary embodiment of the present invention.

[0015] and Figure 1 different, Figure 2 The human-computer interaction system based on visual big data analysis can also include the following components: A frequency division communication mechanism, which is arranged near the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device and is connected to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; Among them, the frequency division communication mechanism is arranged near the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device and is respectively connected to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device, including: the frequency division communication mechanism is used to respectively implement parameter configuration services for the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device based on the frequency division communication link.

[0016] Figure 3 It is a structural diagram of a human-computer interaction system based on visual big data analysis according to another embodiment of the present invention.

[0017] and Figure 1 different, Figure 3 The human-computer interaction system based on visual big data analysis can also include the following components: a surface detection device, arranged near the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device and connected to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; Among them, the surface detection device is arranged near the data analysis mechanism, the morphological processing equipment, the bilateral filtering equipment and the contrast retention equipment and is respectively connected to the data analysis mechanism, the morphological processing equipment, the bilateral filtering equipment and the contrast retention equipment, including: the surface detection device is used to detect the surface material uniformity level of the data analysis mechanism, the morphological processing equipment, the bilateral filtering equipment and the contrast retention equipment based on the visual detection mechanism.

[0018] Next, the specific structure of the human-computer interaction system based on visual big data analysis of the present invention is further explained.

[0019] In the human-computer interaction system based on visual big data analysis according to various embodiments of the present invention: Using a content enhancement component to perform image data processing on the output data of the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast preserving device to obtain output processing data corresponding to the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast preserving device respectively; Among them, using the content enhancement component to perform image data processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing bilateral filtering blur on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; Among them, using the content enhancement component to perform image data processing on the output data of the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing USM filter sharpening on the output data of the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; Among them, using the content enhancement component to perform image data processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing high-pass filtering sharpening on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; And wherein, a content enhancement component is used to perform image data processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively, including: performing distortion correction processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively.

[0020] In addition, in the human-computer interaction system based on visual big data analysis, the model training unit is used to perform multiple learning on the BP neural network to obtain a BP neural network that has completed multiple learning and output it as an artificial intelligence model, and the model application unit is connected to the model training unit, and is used to use the artificial intelligence model to intelligently analyze the existence identification of the human object based on the curvature values ​​of the standard contour curve corresponding to the human object, the number of pixels of the contrast-preserved image, the clarity and signal-to-noise ratio of the contrast-preserved image, and the color component values ​​of each pixel of the contrast-preserved image, including: the number of learning times of the BP neural network is monotonically positively correlated with the number of each pixel of the contrast-preserved image.

[0021] The present invention needs to have at least the following important invention points: Firstly, a specially designed artificial intelligence model is used to intelligently analyze the presence mark of the human object based on the curvature values ​​of the standard contour curve corresponding to the human object, the number of pixels of the contrast-preserved image, the clarity and signal-to-noise ratio of the contrast-preserved image, and the color component values ​​of each pixel of the contrast-preserved image. The human object presence mark is used to indicate whether there is a human object too close to the contrast-preserved image with a depth of field shallower than a set depth of field threshold; Secondly: only when the left turn lamp of the vehicle is turned on by the user, the side capture device encapsulated in the A-pillar on the left side of the vehicle is triggered to perform image data capture action on the left side traffic environment of the vehicle; Again: When it is intelligently determined that there is an object too close to a human body in the traffic environment on the left side of the vehicle, real-time warning operations are performed to avoid collision accidents with objects too close to a human body in the area where the driver's vision is blocked.

[0022] The foregoing description of the exemplary embodiments of the present invention is provided for the purpose of illustration and description. It is not intended to be exhaustive or to limit the present invention to the exact form disclosed. Obviously, many modifications and variations are obvious to those skilled in the art. The exemplary embodiments are selected and described in order to best illustrate the principles of the present invention and its practical application, so that other persons skilled in the art can understand the various embodiments and various variations of the present invention applicable to the specific purpose contemplated. It is intended that the scope of the present invention be limited by the appended claims and their equivalents.

Claims

1. A human-computer interaction system based on visual big data analysis, characterized in that: The system comprises: A command parsing device connected to a left turn lamp of a vehicle, for issuing a first control command when the left turn lamp is turned on by a user, and for issuing a second control command when the left turn lamp is not turned on by the user; A side capture device, packaged in the A-pillar on the left side of the vehicle and connected to the instruction parsing device, is used to perform an image data capture action on the left side traffic environment of the vehicle when receiving the first control instruction, so as to obtain and output a side capture image; A multi-layer enhancement device, arranged inside a vehicle and comprising a morphological processing device, a bilateral filtering device and a contrast retaining device, wherein the bilateral filtering device is connected to the morphological processing device and the contrast retaining device respectively, and the morphological processing device is also connected to the side capture device, and is used to sequentially perform a morphological processing of first dilation and then corrosion on the received side capture image to obtain and output a corresponding morphologically processed image, the bilateral filtering device is used to perform a bilateral filtering processing on the received morphologically processed image to obtain and output a corresponding bilaterally filtered image, and the contrast retaining device is used to perform a processing of retaining a junction of two parts with obvious color or light-dark contrast in the received bilaterally filtered image to obtain and output a corresponding contrast-retained image; A data analysis mechanism is connected to the multi-layer enhancement device and includes a model training unit, a model application unit and a parameter configuration unit. The parameter configuration unit is respectively connected to the model training unit and the model application unit to complete the parameter configuration of the model training unit and the model application unit. The model training unit is used to perform multiple learning on the BP neural network to obtain the BP neural network that has completed multiple learning and output it as an artificial intelligence model. The model application unit is connected to the model training unit and is used to intelligently analyze the human object existence mark using an artificial intelligence model based on the curvature values ​​of various locations of the standard contour curve corresponding to the human object, the number of pixels of the contrast-preserved image, the clarity and signal-to-noise ratio of the contrast-preserved image, and the color component values ​​of each pixel of the contrast-preserved image. The human object existence mark is used to indicate whether there is a human object that is too close to the contrast-preserved image and whose depth of field is shallower than the set depth of field threshold.

2. The human-computer interaction system based on visual big data analysis according to claim 1, characterized in that: The side capture device is also used to stop performing image data capture on the left side traffic environment of the vehicle when receiving the second control instruction.

3. The human-computer interaction system based on visual big data analysis as claimed in claim 2, characterized in that: The system further comprises: A frequency division communication mechanism, which is arranged near the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device and is connected to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; Among them, the frequency division communication mechanism is arranged near the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device and is respectively connected to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device, including: the frequency division communication mechanism is used to respectively implement parameter configuration services for the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device based on the frequency division communication link.

4. The human-computer interaction system based on visual big data analysis according to claim 2, characterized in that: The system further comprises: a surface detection device, arranged near the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device and connected to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively; Among them, the surface detection device is arranged near the data analysis mechanism, the morphological processing equipment, the bilateral filtering equipment and the contrast retention equipment and is respectively connected to the data analysis mechanism, the morphological processing equipment, the bilateral filtering equipment and the contrast retention equipment, including: the surface detection device is used to detect the surface material uniformity level of the data analysis mechanism, the morphological processing equipment, the bilateral filtering equipment and the contrast retention equipment based on the visual detection mechanism.

5. The human-computer interaction system based on visual big data analysis according to any one of claims 2 to 4, characterized in that: A content enhancement component is used to perform image data processing on the output data of the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain output processing data corresponding to the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively.

6. The human-computer interaction system based on visual big data analysis as claimed in claim 5, characterized in that: Using a content enhancement component to perform image data processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing bilateral filtering blur on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively.

7. The human-computer interaction system based on visual big data analysis according to claim 5, characterized in that: Using a content enhancement component to perform image data processing on the output data of the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing USM filter sharpening on the output data of the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data parsing mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively.

8. The human-computer interaction system based on visual big data analysis according to claim 5, characterized in that: Using a content enhancement component to perform image data processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing high-pass filtering sharpening on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively.

9. The human-computer interaction system based on visual big data analysis according to claim 5, characterized in that: Using a content enhancement component to perform image data processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively includes: performing distortion correction processing on the output data of the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device to obtain the output processing data corresponding to the data analysis mechanism, the morphological processing device, the bilateral filtering device and the contrast retention device respectively.

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