Image processing method, device and system

Abstract

The present invention discloses an image processing method, device and system. The method comprises: obtaining image information in a scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a feature identifier; identifying the feature identifier on the wearable device; obtaining the position of the feature identifier in the image information and the three-dimensional model corresponding to the object; and calibrating the three-dimensional model according to the position of the feature identifier in the image information during the rendering of the three-dimensional model. The present invention solves the technical problem in the prior art that drift is easily generated during the rendering of digital twin action models, resulting in poor display effects.

Description

Technical Field

[0001] The present invention relates to the field of image processing, and in particular to an image processing method, device and system. Background Art

[0002] The concept of digital twins and augmented reality technology is gaining popularity, supporting demonstration projects, smart healthcare, sports, and other professional applications. However, current technologies related to augmented reality devices and wearables are difficult to use for human motion recognition. The film and television industry uses green screen technology to capture actor movements and convert them into 3D special effects, enabling motion recognition. However, green screen technology and other technologies can only be used in specific, laboratory-like environments and cannot be reused in professional scenarios. Modules equipped with depth recognition cameras can achieve human motion recognition in non-experimental environments, but external cameras based on computer vision are significantly affected by the environment and are prone to drift and other issues in demonstration projects.

[0003] Figure 1 It is a schematic diagram showing the drift of the digital twin motion model, combined with Figure 1 As shown in the figure, in the initial state, there is a certain deviation in the matching between the model and the user. When the user moves, due to the delay caused by the rendering process, the model and the user become disconnected, that is, drift occurs. Only when the user is fixed can the model catch up and remain consistent.

[0004] There is currently no effective solution to the problem that drift is easily generated during the rendering process of digital twin action models in existing technologies, resulting in poor display effects. Summary of the Invention

[0005] The embodiments of the present invention provide an image processing method, device and system to at least solve the technical problem in the prior art that drift is easily generated during the rendering process of digital twin action models, resulting in poor display effects.

[0006] According to one aspect of an embodiment of the present invention, there is provided an image processing method, comprising: acquiring image information in a scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, the wearable device having a feature identifier; identifying the feature identifier on the wearable device; acquiring a position of the feature identifier in the image information and a three-dimensional model corresponding to the object; and during rendering of the three-dimensional model, calibrating the three-dimensional model according to the position of the feature identifier in the image information.

[0007] According to another aspect of an embodiment of the present invention, a method for processing an image is also provided, including: sending a model display request to a rendering processor, wherein the rendering processor obtains image information in a scene, the image information including at least a wearable device and an object carrying the wearable device, identifies a feature identifier on the wearable device, obtains a position of the feature identifier in the image information, and calibrates the three-dimensional model according to the position of the feature identifier in the image information during rendering of a three-dimensional model corresponding to the object; and receives and displays a rendering result of the three-dimensional model rendered by the rendering processor.

[0008] According to another aspect of an embodiment of the present invention, an image processing system is also provided, including: a wearable device, wherein the wearable device has a feature identifier; an image acquisition device, used to acquire image information in a scene and send the image information to a rendering processor, wherein the image information includes at least the wearable device and the object carrying the wearable device; the rendering processor, which identifies the feature identifier on the wearable device, obtains the position of the feature identifier in the image information, and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the process of rendering the three-dimensional model corresponding to the object; and a display device, which is used to display the rendering result of rendering the three-dimensional model.

[0009] According to another aspect of an embodiment of the present invention, an image processing device is also provided, including: a first acquisition module for acquiring image information in a scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a feature identifier; an identification module for identifying the feature identifier on the wearable device; a second acquisition module for acquiring the position of the feature identifier in the image information and a three-dimensional model corresponding to the object; and a calibration module for calibrating the three-dimensional model according to the position of the feature identifier in the image information during the rendering of the three-dimensional model.

[0010] According to another aspect of an embodiment of the present invention, a storage medium is provided. The storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the above-mentioned image processing method.

[0011] According to another aspect of the embodiment of the present invention, a processor is provided, which is used to run a program, wherein the program executes the above-mentioned image processing method when it is run.

[0012] In an embodiment of the present invention, by setting a feature identifier on a wearable device and rendering the three-dimensional model, the three-dimensional model is calibrated according to the position of the feature identifier in the image information, thereby eliminating the need to locate the bones, contours and other parameters of the worn object in the image to match the worn object with the three-dimensional model. Therefore, the matching of the worn object and the three-dimensional model can be completed directly through the feature identifier, thereby improving the matching efficiency, reducing the time required for calculation, and further reducing the delay in displaying the three-dimensional model, weakening the drift effect caused by excessive delay in the rendering process, and solving the technical problem in the prior art that drift is easily generated during the rendering process of the digital twin action model, resulting in poor display effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0014] Figure 1 It is a schematic diagram showing the drift generated when the digital twin motion model is displayed;

[0015] Figure 2 A hardware structure block diagram of a computer terminal (or mobile device) for implementing an image processing method is shown;

[0016] Figure 3 is a flowchart of an image processing method according to Example 1 of the present application;

[0017] Figure 4 is a schematic diagram of reducing rendering accuracy according to an embodiment of the present application;

[0018] Figure 5 is a flowchart of an image processing method according to Example 2 of the present application;

[0019] Figure 6 is a schematic diagram of an image processing system according to an embodiment of the present application;

[0020] Figure 7 is a schematic diagram of an image processing device according to embodiment 4 of the present application;

[0021] Figure 8 is a schematic diagram of an image processing device according to embodiment 5 of the present application; and

[0022] Figure 9 This is a structural block diagram of a computer terminal according to Example 6 of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] First, some nouns or terms that appear in the description of the embodiments of the present application are subject to the following interpretations:

[0026] Digital twin: It makes full use of physical models, sensor updates, operation history and other data, integrates multi-disciplinary, multi-physical quantity, multi-scale, and multi-probability simulation processes, completes mapping in virtual space, and constructs a virtual entity that can accurately reflect the status of physical equipment, thereby reflecting the entire life cycle process of the corresponding physical equipment.

[0027] Augmented Reality: Augmented Reality (AR) technology is a technology that cleverly integrates virtual information with the real world. It widely uses a variety of technical means such as multimedia, three-dimensional modeling, real-time tracking and registration, intelligent interaction, and sensing. It simulates computer-generated virtual information such as text, images, three-dimensional models, music, and videos, and applies them to the real world. The two types of information complement each other, thereby achieving "enhancement" of the real world.

[0028] Wearable device: A wearable device is a portable device that is worn directly on the body or integrated into the user's clothing or accessories.

[0029] Example 1

[0030] According to an embodiment of the present invention, an embodiment of a method for processing an image is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 2 FIG1 shows a hardware structure block diagram of a computer terminal (or mobile device) for implementing an image processing method. Figure 2 As shown, the computer terminal 20 (or mobile device 20) may include one or more (shown as 202a, 202b, ..., 202n in the figure) processors 202 (the processor 202 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 204 for storing data, and a transmission module 206 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 2 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 2 More or fewer components than shown, or with Figure 2 Different configurations shown.

[0032] It should be noted that the one or more processors 202 and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single, independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 20 (or mobile device). As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0033] The memory 204 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the image processing method in the embodiments of the present invention. The processor 202 executes the software programs and modules stored in the memory 204 to perform various functional applications and data processing, thereby implementing the aforementioned image processing method. The memory 204 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 204 may further include memory remotely located relative to the processor 202, and such remote memory may be connected to the computer terminal 20 via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0034] Transmission device 206 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of computer terminal 20. In one embodiment, transmission device 206 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, transmission device 206 may be a radio frequency (RF) module configured to communicate with the Internet wirelessly.

[0035] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 20 (or mobile device).

[0036] It should be noted that, in some optional embodiments, the above Figure 2 The computer device (or mobile device) shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. Figure 2 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the aforementioned computer device (or mobile device).

[0037] Under the above operating environment, this application provides Figure 3 The image processing method shown. Figure 3 This is a flowchart of an image processing method according to Example 1 of the present application.

[0038] Step S31: Acquire image information in a scene, wherein the image information at least includes a wearable device and an object carrying the wearable device, and the wearable device has a characteristic identifier.

[0039] Specifically, the image information in the above-mentioned scene can be 2D image information captured by a conventional camera. The above-mentioned object carrying the wearable device can be a person, an animal, or a bionic device such as a robot. For example, the person carrying the wearable device can be a speaker at a press conference, a teacher in a remote classroom, or a speaker in a remote conference; the animal carrying the wearable device can be a laboratory animal under medical observation, a rare animal injured and requiring treatment, etc.; the bionic device carrying the wearable device can be a bionic robot, a bionic animal, a bionic plant, etc.

[0040] In an optional embodiment, using a press conference as an example, the press conference can be viewed in person or via a live webcast. In the case of live viewing, audience members can obtain image information of the scene using their own terminal devices; in the case of a live webcast, cameras deployed at the press conference site can capture image information of the scene. Multiple cameras can be deployed at the site to capture image information of the scene from different angles.

[0041] The wearable device can be a wristband, glasses, or other device, and the wearer can be a user wearing the wristband or glasses. In a press conference scenario, a presenter can wear a wristband while demonstrating a product on the podium. The image information captured by the camera includes at least the presenter and the wristband they are wearing. It should be noted that in order to detect the movements of the presenter's arms, the presenter can wear wristbands on both arms.

[0042] The wearable device can also be a helmet, collar, or other device, and the subject wearing the wearable device can be an animal wearing the helmet or collar. In scenarios involving scientific animal observation, the observed animal can wear the helmet or collar and move autonomously. The image information captured by the camera includes at least the observed animal and the helmet or collar it is wearing.

[0043] The object wearing the wearable device can also be a bionic device. For example, a robot can wear a wearable device such as a wristband or helmet to execute preset commands. The acquired image information at least includes the robot wearing the wearable device and the wearable device such as the wristband or helmet it is wearing.

[0044] The characteristic identification on the above-mentioned wearable device can be a characteristic color point or characteristic color block set on the surface of the wearable device. The characteristic identification is allowed to be seen by the user, and can also be hidden from the user through special processing, as long as the image acquisition device can extract its characteristic identification from the surface of the wearable device.

[0045] Step S33: Identify the characteristic identifier on the wearable device.

[0046] After the image acquisition device acquires image information of the scene, it identifies the feature identifier in the image information. Feature information of the feature identifier can be pre-stored, such as the shape, color, and type of the feature identifier, and then the feature identifier is identified based on the feature information.

[0047] In an optional embodiment, the image acquisition device sends the image information to a cloud-based processor, which then identifies the characteristic identifier on the surface of the wearable device. For example, the cloud-based processor may have a pre-stored characteristic identifier that is a QR code of a specific size. When a QR code of a specific size is identified from the image information, the characteristic information is determined to have been identified. For another example, the cloud-based processor may have a pre-stored characteristic identifier that is a color band composed of multiple colors. When a color band composed of multiple colors is identified from the image information, the characteristic information is determined to have been identified.

[0048] Step S35: Obtain the position of the feature identifier in the image information and the three-dimensional model corresponding to the object.

[0049] The location of the aforementioned feature identifier in the image information can be represented by coordinate parameters. After the feature identifier is identified in the acquired image information, the coordinate parameters of the feature identifier can be determined according to the coordinate system in the image information. The aforementioned three-dimensional model can be a preset general model or a three-dimensional model corresponding to the wearable object.

[0050] Step S37: During the rendering of the three-dimensional model, the three-dimensional model is calibrated according to the position of the feature identifier in the image information.

[0051] Rendering the 3D model allows for mapping the wearable object in virtual space and displaying the 3D model on a user's viewing device, which can be an augmented reality device or a mobile terminal device with augmented reality capabilities. Through the viewing device, the user can view a 3D model (virtual entity) that accurately reflects the wearable object. During the 3D model rendering process, the 3D model is calibrated based on the position of the identification information within the image information.

[0052] The above calibration is used to find the object to be simulated, that is, the wearable object, from the image information, and match the wearable object with the three-dimensional model in virtual reality. Only after the two are matched can the corresponding three-dimensional model be displayed based on the movement of the wearable object.

[0053] In the absence of identification information, in order to render the three-dimensional model, it is necessary to locate the skeleton, contour and other parameters of the wearable object in order to find the wearable object from the image information, and match the wearable object in the image information with the wearable object in the three-dimensional model, so that the wearable object can be mapped as a digital twin. In the above scheme, since the position of the feature identifier in the image information is determined, and the position of the wearable device where the feature identifier is located on the wearable object is determined (for example, the bracelet must be worn on the wrist of the wearable object, and the glasses must be worn on the face of the wearable object, etc.), there is no need to match the wearable object with the three-dimensional model by locating the skeleton, contour and other parameters of the wearable object in the image. Therefore, the matching of the wearable object and the three-dimensional model can be completed directly through the feature identifier, thereby improving the matching efficiency, reducing the time required for calculation, and thus reducing the delay in displaying the three-dimensional model, and weakening the drift effect caused by excessive delay during the rendering process.

[0054] The above-mentioned embodiment of the present application sets a feature identifier on the wearable device and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the rendering of the three-dimensional model. Therefore, there is no need to match the worn object with the three-dimensional model by locating the skeleton, contour and other parameters of the worn object in the image. Therefore, the matching of the worn object and the three-dimensional model can be completed directly through the feature identifier, thereby improving the matching efficiency and reducing the time required for calculation, thereby reducing the delay in displaying the three-dimensional model and weakening the drift effect caused by excessive delay in the rendering process, thereby solving the technical problem in the prior art that drift is easily generated during the rendering process of the digital twin action model, resulting in poor display effect.

[0055] As an optional embodiment, during the process of rendering the three-dimensional model, the three-dimensional model is calibrated according to the position of the feature identifier in the image information, including: identifying the object in the image information according to the position of the feature identifier in the image information; using the feature identifier as the origin in the world coordinate system, and rendering the three-dimensional model based on the identified object.

[0056] When determining the position of the feature identifier in the image information, since the position where the object wears the wearable device is known in advance (for example, if the wearable device is a bracelet, it is worn on the wrist; if the wearable device is glasses, it is worn on the face, etc.), combined with the position of the feature identifier in the image information, the position where the object wears the wearable device can be determined, and then the position of the entire object in the image information can be determined.

[0057] The world coordinate system is used to represent the absolute coordinate system of the system when displaying a 3D model. The world coordinate system includes an origin. In the above solution, the feature identifiers identified from the image information are used as the origin of the world coordinate system. Based on the object identified from the image information, the 3D model of the object can be rendered in the world coordinate system.

[0058] Figure 4 This is a schematic diagram of reducing rendering accuracy according to an embodiment of the present application, combined with Figure 1 and Figure 4 As shown, the thicker lines are used to represent the object itself, and the thinner lines are used to represent the imaging of the 3D model (if there are only thicker lines, it means that the object itself is consistent with the 3D model imaging). Figure 1 The subject did not wear a smart bracelet. Figure 1 In the initial state, the object in the image information is determined by identifying each position of the image information, which is not only computationally intensive and time-consuming, but also has certain deviations in the recognition results. Figure 4 In the process, the presenter wears a bracelet on his wrist. In the initial state, the feature markers on the bracelet are used for calibration, so that the three-dimensional model and the presenter can be matched quickly and with a high degree of matching.

[0059] As an optional embodiment, the feature identifier is a color feature point on the surface of the wearable device.

[0060] In the above solution, the feature identifiers are color feature points on the surface of the wearable device. These color feature points can be visible to the user or hidden by the user, and can only be recognized by the image acquisition device. This application does not limit the color feature points to points; they can also be strips or other shapes, as long as the image acquisition device can recognize them from the surface of the wearable device.

[0061] The color feature points can be positioned on the surface of the wearable device so that they face outward when worn by the subject. For example, if the wearable device is a wristband, the color feature points can be positioned on the outward-facing side of the wristband, corresponding to the back of the wrist when worn by the user, so that they are not obscured and the image acquisition device can capture images effectively. The wearable device can also be provided with prompt information to indicate how the subject should wear the wearable device, so that the feature identifiers are not obscured when the subject wears the wearable device.

[0062] As an optional embodiment, the difference between the grayscale value of the color feature point and the grayscale value of the background color of the background where the wearable device is located is within a preset grayscale difference range.

[0063] The background of the wearable device can be the scene of the object. Taking the press conference as an example, the background of the wearable device is the background of the press conference. The background color can be determined by the lighting at the press conference site. In dim light, the background color can be black. In bright light, the background color can be the actual background color.

[0064] The difference between the grayscale value of the color feature point and the grayscale value of the background color of the wearable device is set within a preset grayscale difference range. This is used to make the color feature points on the surface of the wearable device hidden as much as possible in the scene without forming a large color difference with the background that affects the display effect within the scene, thereby achieving the purpose of not being noticed by the viewer and improving the display effect within the scene.

[0065] In an optional embodiment, the above-mentioned preset grayscale difference range can be a value less than 0.5, for example, it can be 0.4. The grayscale value of the color feature point and the grayscale value of the background color can be normalized, and the difference between the two after normalization is obtained. If the difference is less than 0.4, it is determined that the difference between the grayscale value of the color feature point and the grayscale value of the background color of the background where the wearable device is located is within the preset grayscale difference range.

[0066] The above-mentioned embodiment of the present application sets feature markers on the surface of the wearable device, thereby enabling rapid positioning of objects in the image information when rendering a 3D model. This reduces the delay in displaying the 3D model and mitigates the drift effect caused by excessive delays during the rendering process. However, this solution cannot completely eliminate the drift effect, meaning that slight drift may still occur. Therefore, the following solution further addresses the remaining slight drift effect.

[0067] In an optional embodiment, the wearable device includes an acceleration sensor. During the process of rendering the three-dimensional model, the above method also includes: obtaining acceleration data detected by the acceleration sensor; comparing the acceleration data with a preset acceleration threshold; if the acceleration data is greater than the acceleration threshold, reducing the rendering accuracy during the rendering process.

[0068] Drift occurs when the 3D model loses touch with the real object due to delays in rendering and other processes, causing it to lose its alignment with the object. Drift is less likely to occur at slower speeds, but more likely to occur at faster speeds. Therefore, the above solution compares detected acceleration data with a preset acceleration threshold. Further processing is performed only when the detected acceleration exceeds a threshold.

[0069] In an optional embodiment, still taking the example of a presenter wearing a wristband at a press conference, the wristband has an accelerometer that detects the acceleration data of the presenter's wrist in real time and transmits the acceleration data to a cloud server in real time. When any movement of the presenter drives the wrist so that the acceleration data detected by the accelerometer is greater than a preset acceleration threshold, the cloud server reduces the rendering accuracy when rendering the three-dimensional model.

[0070] Lowering the rendering accuracy can reduce the amount of data processing during rendering, further reducing the delay generated during the rendering process, and thus further reducing the drift effect of the 3D model.

[0071] As an optional embodiment, if the acceleration data is greater than the acceleration threshold, the rendering accuracy during the rendering process is reduced, including: rendering the three-dimensional model into a point cloud, wherein the acceleration data is directly proportional to the degree of dispersion of the point cloud.

[0072] In the above solution, the rendering accuracy is reduced by rendering the model in a dotted manner, and the larger the acceleration data, the higher the degree of point cloud dispersion, so that the drift displayed during the displacement process can be hidden, thereby achieving a better display effect.

[0073] Combine Figure 4 As shown, Figure 4 The dotted line in the figure represents the point cloud model. The object wears a wristband on its wrist. In the initial state, the feature markers on the wristband are used for calibration, so that the 3D model and the object can be quickly matched with a high degree of matching. When the acceleration of the object's wrist exceeds the preset acceleration threshold, the intermediate state where the movement is easily disconnected is quickly identified, and the model is rendered into a dotted state, making the model blurred for filling in the gaps. Figure 1 compared to, Figure 4 The degree of tracking in

[15] is high, and since it is rendered as a point, the drift effect can be hidden. When the action is fixed, the rendered model keeps up with the movement of the object and restores the original rendering accuracy.

[0074] As an optional embodiment, during the process of rendering the three-dimensional model, the above method further includes: acquiring physiological parameters of the object; and changing parameter information of the three-dimensional model according to the physiological parameters.

[0075] The aforementioned physiological parameters can still be obtained from wearable devices. These physiological parameters may include the subject's body temperature, heart rate, blood pressure, and other parameters. By obtaining the subject's physiological parameters, it is possible to understand the subject's current physiological state, such as whether they are excited or nervous. Model parameter information that changes based on the physiological parameters may include the model's color, transparency, and other parameters.

[0076] This solution uses wearable devices to detect the subject's physiological parameters and transmits them to a cloud server. The server then adjusts the model's parameters accordingly, enabling the virtual model to interact with the real person, thus increasing the data dimension of the human digital twin.

[0077] In addition, the wearable device can also obtain the location parameters of the object through the GPS (Global Positioning System), thereby changing the parameter information of the model.

[0078] As an optional embodiment, the wearable device also includes: a heart rate sensor, which changes the parameter information of the three-dimensional model according to physiological parameters, including: obtaining heart rate data of the object detected by the heart rate sensor; and adjusting the color information of the three-dimensional model according to the heart rate data.

[0079] In an optional embodiment, when the subject's heart rate data is detected to be greater than a preset threshold, the color of the model can be adjusted to red, or the color of part of the model can be adjusted to red. The proportion of red in the model color can also be adjusted in real time based on the subject's heart rate data. The higher the subject's heart rate, the greater the proportion of red in the model color, and the more red the entire model tends to be.

[0080] The above solution detects the heart rate data of the object through a wearable device, and changes the color of the model according to the heart rate data, so that the three-dimensional model is associated not only with the object's appearance but also with the object's physiological data.

[0081] As an optional embodiment, the wearable device also includes: a skin electrical sensor, which changes the parameter information of the three-dimensional model according to physiological parameters, including: obtaining the sweat rate of the object detected by the skin electrical sensor; and adjusting the transparency information of the three-dimensional model according to the sweat rate.

[0082] Galvanic skin response (GSR) is a physiological indicator of emotion, representing changes in the skin's electrical conduction when stimulated. It is typically expressed as resistance and its logarithm, or conductance and its square root. GSR sensors can measure the sweat rate of a subject's skin surface, thereby determining their emotions. By adjusting the transparency of a 3D model based on the sweat rate, the transparency of the 3D model increases with increasing sweat rate. This allows viewers to perceive the subject's emotions through the interaction between the 3D model and the subject's physiological parameters.

[0083] As an optional embodiment, before collecting image information in the scene, the method also includes: creating a three-dimensional model of the object, wherein creating the three-dimensional model of the object includes: obtaining the object's shape parameters by performing three-dimensional scanning on the object, and creating the three-dimensional model of the object based on the shape parameters; or creating a general model according to preset shape parameters, and modifying the general model according to at least one shape parameter of the object to obtain the three-dimensional model of the object.

[0084] The above scheme provides two ways to create a three-dimensional model of an object. In the first way, the object is directly scanned in three dimensions to obtain the object's appearance parameters, which may include: height parameters, facial contour parameters, body contour parameters, etc. Based on these appearance parameters, a three-dimensional model with a high degree of similarity to the object can be constructed.

[0085] In the second method, a pre-created generic model can be directly obtained and modified based on a small number of the subject's physical parameters to create a 3D model of the subject. These parameters can be obtained without scanning, but simply based on the subject's personal information. For example, if the subject is male, the generic model's height can be increased; if the subject is female, the height can be decreased.

[0086] The aforementioned universal models can be multiple groups. For example, multiple sets of appearance parameters can be set, such as young women, young men, middle-aged women, and middle-aged men and women. Universal models can then be created based on these multiple sets of appearance parameters. After determining the attributes of the object, a corresponding universal model can be selected from the multiple sets. For example, if the object is a young man, a universal model created based on the appearance parameters of a young man can be selected.

[0087] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0088] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0089] Example 2

[0090] According to an embodiment of the present invention, a method for processing an image is also provided. Figure 5 is a flowchart of an image processing method according to embodiment 2 of the present application, such as Figure 5 As shown, the method includes:

[0091] Step S51: Send a model display request to a rendering processor, wherein the rendering processor obtains image information in the scene, the image information including at least the wearable device and the object carrying the wearable device, identifies the feature identifier on the wearable device, obtains the position of the feature identifier in the image information, and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the rendering of the three-dimensional model corresponding to the object.

[0092] The solution in this embodiment can be executed by the user's viewing device. When the user needs to view the digital twin model of the presenter, a model display request can be sent to the rendering processor. In an optional embodiment, taking the application scenario of a press conference as an example, the press conference can be viewed on-site or through a live broadcast. In the case of on-site viewing, the audience can send a model display request to the rendering processor through the terminal device they carry; in the case of watching through a live broadcast, the user can send a model display request to the rendering processor through an augmented reality device.

[0093] Specifically, the image information in the above scenario may be 2D image information collected by an ordinary camera. The above-mentioned wearable device may be a wristband, glasses or other devices, and the object wearing the wearable device may be a user wearing a wristband or glasses. In the scenario of a press conference, the presenter may wear a wristband to demonstrate the product on the main stage. The image information acquired by the camera includes at least the presenter and the wristband he wears. It should be noted that in order to be able to detect the movements of the presenter's arms, the presenter may wear wristbands on both arms. The characteristic identifier on the above-mentioned wearable device may be a characteristic color point or characteristic color block set on the surface of the wearable device. The characteristic identifier is allowed to be seen by the user, and can also be hidden from the user through special processing, as long as the image acquisition device can extract its characteristic identifier from the surface of the wearable device.

[0094] After capturing image information from a scene, the image acquisition device identifies the feature identifiers within the image information. Feature identifier information, such as its shape, color, and type, can be pre-stored. The feature identifiers are then identified based on this feature information. The positions of the feature identifiers within the image information can be represented by coordinate parameters. After identifying the feature identifiers within the acquired image information, the coordinate parameters of the feature identifiers can be determined using the coordinate system within the image information. The three-dimensional model can be a pre-set general model or a three-dimensional model specific to the wearable object.

[0095] By rendering the three-dimensional model, the wearable object can be mapped in virtual space and the three-dimensional model can be displayed on the user's viewing device, which can be an augmented reality device or a mobile terminal device with augmented reality functions. Through the viewing device, a three-dimensional model (virtual entity) that accurately reflects the wearable object can be viewed. During the three-dimensional model rendering process, the three-dimensional model is calibrated according to the position of the identification information in the image information. The calibration is used to find the object to be simulated, i.e., the wearable object, from the image information and match the wearable object with the three-dimensional model in virtual reality. Only after the two are matched can the corresponding three-dimensional model be displayed based on the movement of the wearable object.

[0096] Step S53: receiving and displaying the rendering result of the three-dimensional model rendered by the rendering processor.

[0097] In the absence of identification information, in order to render the three-dimensional model, it is necessary to locate the skeleton, contour and other parameters of the wearable object in order to find the wearable object from the image information, and match the wearable object in the image information with the wearable object in the three-dimensional model, so that the wearable object can be mapped as a digital twin. In the above scheme, since the position of the feature identifier in the image information is determined, and the position of the wearable device where the feature identifier is located on the wearable object is determined (for example, the bracelet must be worn on the wrist of the wearable object, and the glasses must be worn on the face of the wearable object, etc.), there is no need to match the wearable object with the three-dimensional model by locating the skeleton, contour and other parameters of the wearable object in the image. Therefore, the matching of the wearable object and the three-dimensional model can be completed directly through the feature identifier, thereby improving the matching efficiency, reducing the time required for calculation, and thus reducing the delay in displaying the three-dimensional model, and weakening the drift effect caused by excessive delay during the rendering process.

[0098] The above-mentioned embodiment of the present application sets a feature identifier on the wearable device and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the rendering of the three-dimensional model. Therefore, there is no need to match the worn object with the three-dimensional model by locating the skeleton, contour and other parameters of the worn object in the image. Therefore, the matching of the worn object and the three-dimensional model can be completed directly through the feature identifier, thereby improving the matching efficiency and reducing the time required for calculation, thereby reducing the delay in displaying the three-dimensional model and weakening the drift effect caused by excessive delay in the rendering process, thereby solving the technical problem in the prior art that drift is easily generated during the rendering process of the digital twin action model, resulting in poor display effect.

[0099] The rendering server in this embodiment may also execute other steps in embodiment 1 if there is no conflict, which will not be described in detail here.

[0100] Example 3

[0101] According to an embodiment of the present invention, a system for processing an image is also provided. Figure 6 1 is a schematic diagram of an image processing system according to an embodiment of the present application. As shown in the figure, the system includes:

[0102] A wearable device 60, wherein the wearable device has a characteristic identifier.

[0103] The wearable device can be a wristband, glasses, or other device, and the wearer can be a user wearing the wristband or glasses. In a press conference scenario, a presenter can wear a wristband while demonstrating a product on the podium. The image information captured by the camera includes at least the presenter and the wristband they are wearing. It should be noted that in order to detect the movements of the presenter's arms, the presenter can wear wristbands on both arms.

[0104] The wearable device can also be a helmet, collar, or other device, and the subject wearing the wearable device can be an animal wearing the helmet or collar. In scenarios involving scientific animal observation, the observed animal can wear the helmet or collar and move autonomously. The image information captured by the camera includes at least the observed animal and the helmet or collar it is wearing.

[0105] The characteristic identification on the above-mentioned wearable device can be a characteristic color point or characteristic color block set on the surface of the wearable device. The characteristic identification is allowed to be seen by the user, and can also be hidden from the user through special processing, as long as the image acquisition device can extract its characteristic identification from the surface of the wearable device.

[0106] The image acquisition device 62 is used to acquire image information in the scene and send the image information to the rendering processor, wherein the image information at least includes the wearable device and the object carrying the wearable device.

[0107] Specifically, the image information in the above scenario may be 2D image information collected by an ordinary camera.

[0108] In an optional embodiment, using a press conference as an example, the press conference can be viewed in person or via a live webcast. In the case of live viewing, audience members can obtain image information of the scene using their own terminal devices; in the case of a live webcast, cameras deployed at the press conference site can capture image information of the scene. Multiple cameras can be deployed at the site to capture image information of the scene from different angles.

[0109] The rendering processor 64 identifies the feature identifier on the wearable device, obtains the position of the feature identifier in the image information, and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the rendering process of the three-dimensional model corresponding to the object.

[0110] The location of the aforementioned feature identifier in the image information can be represented by coordinate parameters. After the feature identifier is identified in the acquired image information, the coordinate parameters of the feature identifier can be determined according to the coordinate system in the image information. The aforementioned three-dimensional model can be a preset general model or a three-dimensional model corresponding to the wearable object.

[0111] Rendering the 3D model allows for mapping the wearable object in virtual space and displaying the 3D model on a user's viewing device, which can be an augmented reality device or a mobile terminal device with augmented reality capabilities. Through the viewing device, the user can view a 3D model (virtual entity) that accurately reflects the wearable object. During the 3D model rendering process, the 3D model is calibrated based on the position of the identification information within the image information.

[0112] The above calibration is used to find the object to be simulated, that is, the wearable object, from the image information, and match the wearable object with the three-dimensional model in virtual reality. Only after the two are matched can the corresponding three-dimensional model be displayed based on the movement of the wearable object.

[0113] The display device 66 is used to display the rendering result of the three-dimensional model.

[0114] The above-mentioned display device is a viewing device used by viewers for viewing, and can be an augmented reality device or a mobile terminal device with augmented reality function.

[0115] The above-mentioned embodiment of the present application sets a feature identifier on the wearable device and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the rendering of the three-dimensional model. Therefore, there is no need to match the worn object with the three-dimensional model by locating the skeleton, contour and other parameters of the worn object in the image. Therefore, the matching of the worn object and the three-dimensional model can be completed directly through the feature identifier, thereby improving the matching efficiency and reducing the time required for calculation, thereby reducing the delay in displaying the three-dimensional model and weakening the drift effect caused by excessive delay in the rendering process, thereby solving the technical problem in the prior art that drift is easily generated during the rendering process of the digital twin action model, resulting in poor display effect.

[0116] The rendering server in this embodiment may also execute other steps in embodiment 1 if there is no conflict, which will not be described in detail here.

[0117] Example 4

[0118] According to an embodiment of the present invention, there is also provided an image processing device for implementing the image processing method in embodiment 1. Figure 7 is a schematic diagram of an image processing device according to embodiment 4 of the present application, such as Figure 7 As shown, the apparatus 700 includes:

[0119] The first acquisition module 702 is configured to acquire image information in a scene, wherein the image information at least includes a wearable device and an object carrying the wearable device, and the wearable device has a feature identifier.

[0120] The identification module 704 is used to identify the characteristic identifier of the wearable device.

[0121] The second acquisition module 706 is used to acquire the position of the feature identifier in the image information and the three-dimensional model corresponding to the object.

[0122] The calibration module 708 is configured to calibrate the three-dimensional model according to the position of the feature identifier in the image information during the rendering process of the three-dimensional model.

[0123] It should be noted that the first acquisition module 702, identification module 704, second acquisition module 706, and calibration module 708 described above correspond to steps S31 to S37 in Example 1. The examples and application scenarios implemented by these four modules and the corresponding steps are the same, but are not limited to those disclosed in Example 1. It should be noted that the above modules, as part of the apparatus, can be run in the computer terminal 10 provided in Example 1.

[0124] As an optional embodiment, the calibration module includes: an identification submodule, which is used to identify objects in the image information based on the position of the feature identifier in the image information; and a rendering submodule, which is used to use the feature identifier as the origin in the world coordinate system and render the three-dimensional model based on the identified object.

[0125] As an optional embodiment, the feature identifier is a color feature point on the surface of the wearable device.

[0126] As an optional embodiment, the difference between the grayscale value of the color feature point and the grayscale value of the background color of the background where the wearable device is located is within a preset grayscale difference range.

[0127] As an optional embodiment, the above-mentioned device also includes: a third acquisition module, which is used for the wearable device to include an acceleration sensor, and to obtain acceleration data detected by the acceleration sensor during the rendering of the three-dimensional model; a comparison module, which is used to compare the acceleration data with a preset acceleration threshold; and a reduction module, which is used to reduce the rendering accuracy during the rendering process if the acceleration data is greater than the acceleration threshold.

[0128] As an optional embodiment, the reduction module includes: a point-like processing submodule, which is used to render the three-dimensional model into a point-like form, wherein the acceleration data is directly proportional to the degree of dispersion of the point cloud of the point-like form.

[0129] As an optional embodiment, the above-mentioned device further includes: a fourth acquisition module, used to obtain physiological parameters of the object during the rendering of the three-dimensional model; and a change module, used to change parameter information of the three-dimensional model according to the physiological parameters.

[0130] As an optional embodiment, the wearable device also includes: a heart rate sensor, and the change module includes: a first acquisition submodule, used to obtain heart rate data of the object detected by the heart rate sensor; and a first adjustment submodule, used to adjust the color information of the three-dimensional model according to the heart rate data.

[0131] As an optional embodiment, the wearable device also includes: a skin electrical sensor, and the change module includes: an acquisition submodule for acquiring the sweat rate of the object detected by the skin electrical sensor; and an adjustment submodule for adjusting the transparency information of the three-dimensional model according to the sweat rate.

[0132] As an optional embodiment, the above-mentioned device also includes: a creation module, which is used to create a three-dimensional model of the object before collecting image information in the scene, wherein the creation module obtains the object's shape parameters by performing a three-dimensional scan on the object, and creates the three-dimensional model of the object based on the shape parameters; or creates a general model according to preset shape parameters, and modifies the general model according to at least one shape parameter of the object to obtain the three-dimensional model of the object.

[0133] Example 5

[0134] According to an embodiment of the present invention, there is also provided an image processing device for implementing the image processing method in embodiment 2. Figure 8 is a schematic diagram of an image processing device according to embodiment 5 of the present application, such as Figure 7 As shown, the apparatus 800 includes:

[0135] The sending module 802 is used to send a model display request to the rendering processor, wherein the rendering processor obtains image information in the scene, the image information including at least the wearable device and the object carrying the wearable device, identifies the feature identifier on the wearable device, obtains the position of the feature identifier in the image information, and calibrates the three-dimensional model according to the position of the feature identifier in the image information during the process of rendering the three-dimensional model corresponding to the object.

[0136] The receiving module 804 is configured to receive and display the rendering result of the three-dimensional model rendered by the rendering processor.

[0137] It should be noted that the sending module 802 and the receiving module 804 correspond to steps S51 to S53 in Example 2. The examples and application scenarios implemented by the two modules and the corresponding steps are the same, but are not limited to the contents disclosed in Example 1. It should be noted that the above modules, as part of the device, can be run in the computer terminal 10 provided in Example 1.

[0138] Example 6

[0139] The embodiment of the present invention can provide a computer terminal, which can be any computer terminal device in a computer terminal group. Optionally, in this embodiment, the computer terminal can also be replaced by a terminal device such as a mobile terminal.

[0140] Optionally, in this embodiment, the computer terminal may be located in at least one network device among a plurality of network devices of a computer network.

[0141] In this embodiment, the above-mentioned computer terminal can execute the program code of the following steps in the image processing method: obtaining image information in the scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a feature identifier; identifying the feature identifier on the wearable device; obtaining the position of the feature identifier in the image information and the three-dimensional model corresponding to the object; and in the process of rendering the three-dimensional model, calibrating the three-dimensional model according to the position of the feature identifier in the image information.

[0142] Optionally, Figure 9 This is a structural block diagram of a computer terminal according to Example 6 of the present application. Figure 9 As shown, the computer terminal A may include: one or more (only one is shown in the figure) processors 902 , a memory 906 , and a peripheral interface 908 .

[0143] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the image processing method and apparatus in the embodiments of the present invention. The processor executes the software programs and modules stored in the memory to perform various functional applications and data processing, thereby implementing the above-mentioned image processing method. The memory can include high-speed random access memory and can also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory can further include memory remotely located relative to the processor, and these remote memories can be connected to terminal A via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtain image information in the scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a feature identifier; identify the feature identifier on the wearable device; obtain the position of the feature identifier in the image information and the three-dimensional model corresponding to the object; and in the process of rendering the three-dimensional model, calibrate the three-dimensional model according to the position of the feature identifier in the image information.

[0145] Optionally, the processor may also execute the program code of the following steps: identifying an object in the image information according to the position of the feature identifier in the image information; using the feature identifier as the origin in the world coordinate system, and rendering the three-dimensional model based on the identified object.

[0146] Optionally, the feature identifier is a color feature point on the surface of the wearable device.

[0147] Optionally, a difference between a grayscale value of the color feature point and a grayscale value of a background color of a background where the wearable device is located is within a preset grayscale difference range.

[0148] Optionally, the above-mentioned processor can also execute the program code of the following steps: the wearable device includes an acceleration sensor, and during the process of rendering the three-dimensional model, the acceleration data detected by the acceleration sensor is obtained; the acceleration data is compared with a preset acceleration threshold; if the acceleration data is greater than the acceleration threshold, the rendering accuracy during the rendering process is reduced.

[0149] Optionally, the processor may further execute program code of the following steps: rendering the three-dimensional model into a point-like form, wherein the acceleration data is directly proportional to the degree of dispersion of the point cloud of the point-like form.

[0150] Optionally, the processor may further execute program codes of the following steps: obtaining physiological parameters of the object during rendering of the three-dimensional model; and changing parameter information of the three-dimensional model according to the physiological parameters.

[0151] Optionally, the processor may further execute program code of the following steps: the wearable device further includes: a heart rate sensor, which obtains heart rate data of an object detected by the heart rate sensor; and adjusts color information of the three-dimensional model according to the heart rate data.

[0152] Optionally, the processor may further execute program code of the following steps: the wearable device further includes: a skin electrical sensor, which obtains a sweat rate of an object detected by the skin electrical sensor; and adjusts transparency information of the three-dimensional model according to the sweat rate.

[0153] Optionally, the processor may further execute the program code of the following steps: creating a three-dimensional model of the object, wherein the creating the three-dimensional model of the object includes: obtaining the shape parameters of the object by performing a three-dimensional scan on the object, and creating the three-dimensional model of the object based on the shape parameters; or creating a general model according to preset shape parameters, and modifying the general model according to at least one shape parameter of the object to obtain the three-dimensional model of the object.

[0154] An embodiment of the present invention provides an image processing method. By setting a feature identifier on a wearable device and rendering a three-dimensional model, the three-dimensional model is calibrated according to the position of the feature identifier in the image information. This eliminates the need to locate the wearable object's skeleton, outline, and other parameters in the image to match the wearable object with the three-dimensional model. The wearable object and the three-dimensional model can be matched directly using the feature identifier, thereby improving matching efficiency and reducing the time required for calculation. This reduces the delay in displaying the three-dimensional model and weakens the drift effect caused by excessive delays during the rendering process. This solves the technical problem in the prior art of digital twin action models that drift is prone to occur during rendering, resulting in poor display effects.

[0155] It can be understood by those skilled in the art that Figure 9 The structure shown is for illustration only, and the computer terminal may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a handheld computer, a mobile Internet device (MID), a PAD, or other terminal devices. Figure 9 It does not limit the structure of the above electronic device. For example, the computer terminal 90 may also include Figure 9 More or fewer components (such as network interfaces, display devices, etc.) shown in, or with Figure 9 Different configurations shown.

[0156] A person skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0157] Example 7

[0158] The embodiment of the present invention further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the image processing method provided in the first embodiment.

[0159] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0160] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps: obtaining image information in a scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a feature identifier; identifying the feature identifier on the wearable device; obtaining the position of the feature identifier in the image information and the three-dimensional model corresponding to the object; and in the process of rendering the three-dimensional model, calibrating the three-dimensional model according to the position of the feature identifier in the image information.

[0161] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0162] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0163] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0164] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0165] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0166] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0167] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A method for processing an image, characterized in that: include: Acquire image information in a scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a characteristic identifier; Identifying a characteristic identifier on the wearable device, wherein the position of the characteristic identifier on the surface of the wearable device is a position where the wearable device faces outward after the subject wears the wearable device, and setting a prompt message on the wearable device, the prompt message being used to prompt the subject on how to wear the wearable device; Obtaining a position of the feature identifier in the image information and a three-dimensional model corresponding to the object; During the rendering of the three-dimensional model, calibrating the three-dimensional model in augmented reality according to the object corresponding to the position of the feature identifier in the image information, wherein the object is the object to be simulated in the image information; In the process of rendering the three-dimensional model, the method further includes: obtaining acceleration data of the wearable device; in response to the acceleration data being greater than an acceleration threshold, performing padding processing on the object to achieve rendering of the three-dimensional model.

2. The method according to claim 1, characterized in that During the rendering of the three-dimensional model, calibrating the three-dimensional model in the augmented reality according to the object corresponding to the position of the feature identifier in the image information includes: identifying the object in the image information according to the position of the feature identifier in the image information; The feature identifier is used as an origin in a world coordinate system, and the three-dimensional model is rendered based on the identified object.

3. The method according to claim 1, characterized in that The feature identifier is a color feature point on the surface of the wearable device.

4. The method according to claim 3, characterized in that The difference between the grayscale value of the color feature point and the grayscale value of the background color of the background where the wearable device is located is within a preset grayscale difference range.

5. The method according to claim 1, characterized in that The wearable device includes an acceleration sensor. During the process of rendering the three-dimensional model, the method further includes: Acquiring acceleration data detected by the acceleration sensor; Comparing the acceleration data with a preset acceleration threshold; If the acceleration data is greater than the acceleration threshold, the rendering accuracy during the rendering process is reduced.

6. The method according to claim 5, characterized in that If the acceleration data is greater than the acceleration threshold, reducing the rendering accuracy during the rendering process includes: The three-dimensional model is rendered into a point cloud, wherein the acceleration data is directly proportional to the degree of dispersion of the point cloud.

7. The method according to claim 1, characterized in that During the process of rendering the three-dimensional model, the method further includes: obtaining physiological parameters of the subject; The parameter information of the three-dimensional model is modified according to the physiological parameters.

8. The method according to claim 7, characterized in that The wearable device further includes a heart rate sensor, which changes parameter information of the three-dimensional model according to the physiological parameters, including: acquiring heart rate data of the subject detected by the heart rate sensor; Color information of the three-dimensional model is adjusted according to the heart rate data.

9. The method according to claim 7, characterized in that The wearable device further includes: a skin electrical sensor, which changes parameter information of the three-dimensional model according to the physiological parameters, including: obtaining a sweat rate of the subject detected by the galvanic skin sensor; The transparency information of the three-dimensional model is adjusted according to the sweat rate.

10. The method according to claim 1, characterized in that Before collecting image information in the scene, the method further includes: creating a three-dimensional model of the object, wherein creating the three-dimensional model of the object includes: Performing a three-dimensional scan on the object to obtain shape parameters of the object, and creating a three-dimensional model of the object based on the shape parameters; or A general model is created according to preset shape parameters, and the general model is modified according to at least one shape parameter of the object to obtain a three-dimensional model of the object.

11. A method for processing an image, characterized in that: include: Sending a model display request to a rendering processor, wherein the rendering processor obtains image information in a scene, the image information including at least a wearable device and an object carrying the wearable device, the wearable device having a feature identifier, identifying the feature identifier on the wearable device, wherein the position of the feature identifier on the surface of the wearable device is the position of the wearable device facing outward after the object wears the wearable device, and setting a prompt information on the wearable device, wherein the prompt information is used to prompt the object on how to wear the wearable device, obtaining the position of the feature identifier in the image information, and calibrating the three-dimensional model in augmented reality according to the object corresponding to the position of the feature identifier in the image information during rendering of the three-dimensional model corresponding to the object, wherein the object is the object to be simulated in the image information, wherein during rendering of the three-dimensional model, the method further includes: obtaining acceleration data of the wearable device; and in response to the acceleration data being greater than an acceleration threshold, performing position padding processing on the object to achieve rendering of the three-dimensional model; Receive and display the rendering result of the three-dimensional model rendered by the rendering processor.

12. An image processing system, characterized in that: include: A wearable device, wherein the wearable device has a characteristic identifier; An image acquisition device, configured to acquire image information in a scene and send the image information to a rendering processor, wherein the image information includes at least the wearable device and the object carrying the wearable device; The rendering processor identifies a feature identifier on the wearable device, wherein the position of the feature identifier on the surface of the wearable device is the position of the wearable device facing outward after the subject wears the wearable device, and sets a prompt information on the wearable device, wherein the prompt information is used to prompt the subject on how to wear the wearable device, obtains the position of the feature identifier in the image information, and, during a process of rendering a three-dimensional model corresponding to the object, calibrates the three-dimensional model in augmented reality based on the object corresponding to the position of the feature identifier in the image information, wherein the object is the object to be simulated in the image information; Wherein, during the process of rendering the three-dimensional model, the rendering processor is further used to: obtain acceleration data of the wearable device; in response to the acceleration data being greater than an acceleration threshold, perform position filling processing on the object to achieve rendering of the three-dimensional model; A display device is used to display a rendering result of rendering the three-dimensional model.

13. An image processing device, characterized in that: include: A first acquisition module is configured to acquire image information in a scene, wherein the image information includes at least a wearable device and an object carrying the wearable device, and the wearable device has a characteristic identifier; an identification module configured to identify a characteristic identifier on the wearable device, wherein the position of the characteristic identifier on the surface of the wearable device is the position of the wearable device facing outward after the subject wears the wearable device, and to set a prompt message on the wearable device, the prompt message being used to prompt the subject on how to wear the wearable device; A second acquisition module is used to obtain the position of the feature identifier in the image information and the three-dimensional model corresponding to the object; a calibration module, configured to calibrate the three-dimensional model in augmented reality according to the object corresponding to the position of the feature identifier in the image information during rendering of the three-dimensional model, wherein the object is the object to be simulated in the image information; In the process of rendering the three-dimensional model, the calibration module is also used to obtain acceleration data of the wearable device; in response to the acceleration data being greater than an acceleration threshold, the object is padded to achieve rendering of the three-dimensional model.

14. A storage medium, characterized in that The storage medium includes a stored program, wherein when the program is executed, the device where the storage medium is located is controlled to execute the image processing method according to any one of claims 1 to 10.

15. A processor, characterized in that: The processor is configured to run a program, wherein the program, when running, executes the image processing method according to any one of claims 1 to 10.

Images