Multi-view naked-eye 3D content generation method and device

Abstract

The invention discloses a multi-view naked-eye 3D content generation method and device. The method comprises the steps that to-be-processed data are acquired, the to-be-processed data comprise to-be-processed hardware data and to-be-processed content data, the to-be-processed hardware data are used for representing hardware for three-dimensional content display, and the to-be-processed content data are used for representing content for three-dimensional display; test-based hardware parameter calibration processing is carried out on the to-be-processed hardware data to obtain calibrated hardware parameter data, and the calibrated hardware parameters are parameter data used for representing a pixel and lens mapping relation; performing multi-view generation processing based on virtual acquisition on the to-be-processed content data to obtain multi-view image data; and carrying out image synthesis processing based on pixel mapping on the calibration hardware parameters and the multi-view image data to obtain result three-dimensional content display data. The technical effect of improving the 3D display effect and the hardware mapping adaptability is achieved.

Description

Technical Field

[0001] This application relates to the field of 3D display, and more specifically, to a method and apparatus for generating multi-view naked-eye 3D content. Background Technology

[0002] With the continuous development of technology, naked-eye 3D technology has emerged as an eye-catching technology, allowing users to view 3D images or videos without wearing any glasses or devices. The core principle is to project the images of the left and right eyes onto the corresponding eyeballs through optical elements such as gratings, lens arrays, or parallax barriers, and use the visual difference of the human brain to form a stereoscopic effect.

[0003] In existing technologies, naked-eye 3D display technology still has the following problems: First, naked-eye 3D technology is usually based on the two-view principle, which results in an extremely narrow sweet spot. Users must be in a specific spatial position to observe stereoscopic images. Even a slight head movement can cause a jump in the viewing area or a reverse parallax phenomenon, resulting in a reversal of depth information, which severely limits the user's viewing freedom and immersion. Second, there are many types of naked-eye 3D display devices. The physical parameters such as screen size, resolution, raster tilt angle, and pitch vary greatly. Existing technologies lack a universal parameter adaptive mapping method. For each new hardware, tedious manual calibration and parameter resetting are required, which makes it impossible to achieve "write once, deploy anywhere" (Write Once, Deploy Anywhere) for content.

[0004] Therefore, this application is made in response to the problems existing in the production of naked-eye 3D display content. Summary of the Invention

[0005] The main objective of this application is to provide a multi-viewpoint naked-eye 3D content generation method and apparatus to solve the above-mentioned problems and achieve the technical effect of improving 3D display effect and adaptability to different hardware devices.

[0006] To achieve the above objectives, the first aspect of this application proposes a multi-view naked-eye 3D content generation method, comprising: Acquire data to be processed, wherein the data to be processed includes hardware data to be processed and content data to be processed, wherein the hardware data to be processed is data representing the hardware used to display 3D content, and the content data to be processed is data representing the content used to display 3D content; The hardware data to be processed is subjected to test-based hardware parameter calibration processing to obtain calibrated hardware parameter data, wherein the calibrated hardware parameter data is parameter data used to represent the mapping relationship between pixels and lenses; The content data to be processed is subjected to multi-view generation processing based on virtual acquisition to obtain multi-view image data, wherein the multi-view image data is data used to represent multi-view sequence frames; The calibration hardware parameter data and the multi-view image data are subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data.

[0007] Furthermore, the hardware data to be processed undergoes test-based hardware parameter calibration processing to obtain calibrated hardware parameter data, including: The hardware data to be processed is subjected to a test map generation process based on resolution matching to obtain a hardware test map; The hardware screen is tested according to the hardware test diagram to obtain hardware test result data, wherein the hardware test result data is used to represent the display data of the test diagram on the display hardware; The hardware test result data is subjected to parameter calibration processing based on screen analysis to obtain the calibrated hardware parameter data.

[0008] Furthermore, the hardware test result data undergoes parameter calibration processing based on screen analysis to obtain the calibrated hardware parameter data, including: The hardware test result data is processed by image feature extraction to obtain image feature data, wherein the image feature data is feature data used to represent the contrast and channel separation of the displayed image, and the displayed image is the display of the test image on the display hardware; The image feature data is filtered based on a preset image feature threshold to obtain target image feature data; Determine the hardware parameters corresponding to the target image features to obtain the calibration hardware parameter data.

[0009] Furthermore, the content data to be processed undergoes multi-viewpoint generation processing based on virtual acquisition to obtain multi-viewpoint image data, including: The viewpoint parameter data is calculated and processed on the content data to be processed to obtain virtual viewpoint parameter data; A multi-camera shooting array is constructed based on the virtual viewpoint parameter data to obtain a virtual multi-camera shooting array. The virtual multi-camera array is used to capture and process the content data to be processed, thereby obtaining the multi-viewpoint image data.

[0010] Furthermore, pixel-mapping-based image synthesis processing is performed on the calibration hardware parameter data and the multi-view image data to obtain the resulting 3D content display data, including: The calibration hardware parameter data is processed to construct a pixel mapping model, resulting in a pixel viewpoint mapping model; The multi-viewpoint image data is subjected to mapping and synthesis processing based on the pixel viewpoint mapping model to obtain composite display image data; The composite display image data is subjected to image optimization processing based on display calibration to obtain the resulting three-dimensional content display data.

[0011] Further, the multi-viewpoint image data undergoes mapping and synthesis processing based on the pixel viewpoint mapping model to obtain composite display image data, including: The multi-viewpoint image data is subjected to viewpoint graph segmentation processing to obtain multiple sub-image datasets, wherein the multiple sub-image datasets correspond to the multi-viewpoint image data, and each sub-image dataset includes sub-images segmented by the viewpoint graph. In the plurality of sub-image datasets, sub-images corresponding to screen pixel positions are matched to obtain composite mapping image data, wherein the composite mapping image data is data used to represent the sub-images corresponding to the screen pixel positions; The composite mapped image data is processed based on screen pixel positions to obtain the composite display image data.

[0012] Further, the composite display image data undergoes image optimization processing based on display calibration to obtain the resulting three-dimensional content display data, including: Acquire image display test data, wherein the image display test data includes first test result data and second test result data, wherein the first test result data is data used to represent image ghosting, and the second test result data is data used to represent image depth feedback; Based on the first test result data, the multi-view image data is subjected to a first optimization process to obtain first optimized multi-view image data. The first optimized multi-view image data is then subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data. Based on the second test result data, the multi-view image data is subjected to a second optimization process to obtain second optimized multi-view image data. The second optimized multi-view image data is then subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data.

[0013] According to a second aspect of this application, a data processing apparatus for multi-viewpoint 3D content display is provided, comprising: The data acquisition module is used to acquire data to be processed, wherein the data to be processed includes hardware data to be processed and content data to be processed, wherein the hardware data to be processed is data representing the hardware for displaying 3D content, and the content data to be processed is data representing the content for displaying 3D content; The hardware parameter calibration module is used to perform test-based hardware parameter calibration processing on the hardware data to be processed to obtain calibrated hardware parameter data, wherein the calibrated hardware parameter data is parameter data used to represent the mapping relationship between pixels and lenses. A multi-view image generation module is used to perform multi-view generation processing based on virtual acquisition on the content data to be processed to obtain multi-view image data, wherein the multi-view image data is data used to represent multi-view sequence frames; The pixel mapping synthesis module is used to perform pixel mapping-based image synthesis processing on the calibration hardware parameters and the multi-view image data to obtain the resulting three-dimensional content display data.

[0014] According to a third aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing the computer to perform the above-described multi-view naked-eye 3D content generation method.

[0015] According to a fourth aspect of this application, an electronic device is proposed, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the above-described multi-view naked-eye 3D content generation method.

[0016] The technical solutions provided by the embodiments of this application may include the following beneficial effects: In this application, data to be processed is acquired, including hardware data to be processed and content data to be processed. The hardware data to be processed represents the hardware used to display 3D content, and the content data to be processed represents the content to be displayed in 3D. The hardware data to be processed undergoes test-based hardware parameter calibration to obtain calibrated hardware parameter data, which represents the pixel-lens mapping relationship. The content data to be processed undergoes multi-viewpoint generation based on virtual acquisition to obtain multi-viewpoint image data, which represents multi-viewpoint sequence frames. The calibrated hardware parameters and the multi-viewpoint image data undergo pixel-mapping-based image synthesis to obtain the resulting 3D content display data. By performing pixel-mapping processing on the multi-viewpoint images obtained from virtual acquisition and the calibrated hardware parameters to obtain the resulting 3D display data, the technical effect of improving 3D display effect and hardware mapping adaptability is achieved. Attached Figure Description

[0017] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings: Figure 1 A flowchart of a multi-view naked-eye 3D content generation method provided in this application; Figure 2 A flowchart of a multi-view naked-eye 3D content generation method provided in this application; Figure 3 A flowchart of a multi-view naked-eye 3D content generation method provided in this application; Figure 4 A schematic diagram of a multi-view naked-eye 3D content generation device provided in this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0019] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0020] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0021] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0022] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linked," and "socketing" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0023] Explanation of related terms Glasses-free 3D (Autostereoscopy): refers to a technology that allows users to perceive stereoscopic depth effects simply by observing a display screen with the naked eye, without needing to wear special glasses or helmets.

[0024] Slant Angle / Slant Factor: The angle between the long axis of the cylindrical lens and the vertical pixel column of the screen.

[0025] Lens Pitch: Refers to the number of screen sub-pixels covered by a single cylindrical lens unit in the horizontal direction.

[0026] Zero Parallax Plane (ZPP): A specific plane defined in a 3D virtual scene. Objects located on this plane will appear to overlap in the rendered left and right views (without parallax). On the display screen, objects on this plane appear to be pasted onto the screen glass; objects before ZPP will appear "out of screen," while objects after ZPP will appear "in-screen" with a deep, immersive effect.

[0027] Crosstalk and ghosting: Crosstalk refers to the left eye accidentally seeing image information that should be seen by the right eye (or the overlapping of information from adjacent viewpoints). When crosstalk is too large, the human eye cannot fuse the images, and the image will appear ghosted or blurry.

[0028] In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed. Figure 1 A flowchart of a multi-view naked-eye 3D content generation method provided in this application is shown below. Figure 1 As shown, the method includes the following steps: S101: Obtain the data to be processed; The data to be processed includes hardware data to be processed and content data to be processed. Hardware data to be processed is data representing the hardware used to display 3D content, and content data to be processed is data representing the content to be displayed in 3D. The hardware used to display 3D content includes a screen, a lenticular lens, etc. Hardware data to be processed is data representing the parameters of the screen and the lenticular lens. 3D content is the 3D content to be displayed, such as 3D character models, 3D building models, etc. Content data to be processed is the data of the above-mentioned 3D content.

[0029] S102: Perform test-based hardware parameter calibration processing on the hardware data to be processed to obtain calibrated hardware parameter data; The calibration hardware parameters are parameter data used to represent the mapping relationship between pixels and lenses; the calibration hardware parameters are also used to represent the correspondence between screen pixels and grating lenses, including lens pitch, offset, and slant. Based on the parameters obtained after calibration, the above-mentioned calibration hardware parameters are used for video 3D display processing during 3D video production.

[0030] In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed to achieve hardware parameter calibration. Figure 2A flowchart of a multi-view naked-eye 3D content generation method provided in this application is shown below. Figure 2 As shown, the method includes the following steps: S201: Perform resolution-matching-based test map generation processing on the hardware data to be processed to obtain the hardware test map; The physical resolution of the screen in the 3D display hardware is identified, and the pixel density and total number of pixels of the screen are determined. The test image resolution is determined based on the physical resolution of the hardware screen, and the test image resolution is the same as the physical resolution of the hardware screen. A pattern is designed for the test image, generating a side view containing vertical RGB lines, with each color channel displayed independently. Specifically, red lines represent test R subpixel alignment; green lines represent test G subpixel alignment; and blue lines represent test B subpixel alignment. The test image is then generated based on the above test image resolution and pattern, using tools such as Photoshop, GIMP, or Calman.

[0031] S202: Perform hardware screen testing based on the hardware test diagram to obtain hardware test result data; The hardware test result data is used to represent the display data of the test diagram on the display hardware; the above test diagram is displayed in full screen on the hardware screen, and the observation data of the display screen is obtained. The display screen observation data can be the image captured by the high-resolution industrial camera on the above full-screen display screen, or it can be the feedback data observed by the human eye, such as the feedback of the human eye from different angles at the preset optimal viewing distance. S203: Perform parameter calibration processing on the hardware test result data based on screen analysis to obtain calibrated hardware parameter data.

[0032] In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed to perform parameter calibration processing on hardware test result data based on image analysis, including: The hardware test result data is processed by image feature extraction to obtain image feature data. The image feature data is used to represent the contrast and channel separation of the displayed image. The displayed image is the image of the test image displayed on the display hardware. Further, the image feature data is processed by recognition to obtain first image feature data and second image feature data. The first image feature data is used to represent the contrast of the image of the test image displayed on the display hardware, and the second image feature data is used to represent the channel separation of the image of the side view displayed on the display hardware. The image feature data is filtered based on a preset image feature threshold to obtain target image feature data. The Slant, Pitch, and Offset values ​​are iteratively fine-tuned using software to obtain the RGB line contrast corresponding to different Slant, Pitch, and Offset parameter groups. The RGB line contrast is highest and the crosstalk value is lowest within a specific viewing area, thus selecting the point with the least crosstalk. The Pitch and Offset are iteratively fine-tuned, with Pitch adjustment adjusting the lens pitch within ±5% to determine line alignment. Offset adjustment adjusts the horizontal / vertical offset to compensate for manufacturing errors, using the formula: Offset = (Viewing Angle - Ideal Angle) × Pitch / 2. When the RGB lines are clearly separated in all viewing areas without cross-color mixing, the Slant, Pitch, and Offset values ​​are determined. Based on these values, a pixel-lens alignment standard is established, and the hardware parameters are calibrated according to this standard, resulting in calibrated hardware parameter data.

[0033] Determine the hardware parameters corresponding to the target image features to obtain calibration hardware parameter data.

[0034] S103: Perform multi-viewpoint generation processing on the content data to be processed based on virtual acquisition to obtain multi-viewpoint image data; Multi-view image data is data used to represent a sequence of multi-view images; In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed to achieve multi-view image generation, including: The viewpoint parameters of the 3D content data to be processed are calculated to obtain virtual viewpoint parameter data; a multi-camera shooting array is constructed based on the virtual viewpoint parameter data to obtain a virtual multi-camera shooting array; the content data to be processed is captured and processed based on the virtual multi-camera shooting array to obtain multi-viewpoint image data.

[0035] A virtual environment scene is constructed, and the 3D content to be processed is imported into this virtual environment. Software such as UE5 (Unreal Engine 5), Unity, Maya, or C4D can be used to construct the virtual environment scene and import the 3D content to be processed into it. Reference plane data and baseline length data are determined based on the 3D content data. The reference plane data is obtained by calculating the scene depth of the 3D content; the reference plane data is the average depth of the scene. Calculate the baseline length, where Baseline is the baseline length and Viewing Distance is the viewing distance; Based on the virtual viewpoint parameter data, including the aforementioned reference plane data and baseline length data, a multi-camera shooting array is constructed in this virtual environment. The virtual viewpoint parameters are the parameters of the aforementioned multi-camera shooting array, including: field of view (FOV), zero parallax plane (ZPP), focal length, position (Position X), rotation, etc. For example, to build a nine-camera shooting array, the FOV of the nine cameras must be completely consistent, the focal plane distance of the nine cameras must be consistent, the focal length of the nine cameras must be consistent, the positions of the nine cameras must be evenly arranged on the X-axis according to the aforementioned baseline length, and the rotation angle of the nine cameras must be determined according to the mode. Among them, it can be an off-axis mode, in which the nine cameras are parallel, or a toe-in mode, in which the nine cameras are slightly rotated towards the center. Based on the above multi-camera shooting array, 3D content is acquired. All cameras in the multi-camera shooting array share the same animation timeline, resulting in a multi-viewpoint sequence frame acquired by the multi-camera shooting array.

[0036] In an optional embodiment of this application, by constructing the aforementioned multi-camera shooting array to capture 3D content, such as the aforementioned 9-camera shooting array, the range of the optimal viewing area is increased, thereby enhancing the user's viewing freedom and immersion. S104: Perform pixel-mapping-based image synthesis processing on the calibrated hardware parameters and multi-view image data to obtain the resulting 3D content display data.

[0037] In this embodiment, the multi-view image data is segmented to obtain segmented sub-images. The sub-images are then matched to the positions of the sub-pixels on the screen according to the calibration hardware parameters, thereby realizing the segmentation and synthesis processing of the multi-view image based on pixel mapping to obtain a composite image suitable for hardware display.

[0038] In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed. Figure 3 The flowchart of a multi-view naked-eye 3D content generation method proposed in this application is as follows: Figure 3 As shown, the method includes the following steps: S301: Perform pixel mapping model construction processing on the calibration hardware parameter data to obtain the pixel viewpoint mapping model; Based on the above-mentioned calibrated hardware parameter data, a pixel mapping model is constructed, M(x, y, Pitch, Offset, Slant), where x and y are the coordinate positions of the sub-pixels on the screen. This pixel viewpoint mapping model is used to represent the mapping relationship between sub-pixels and viewpoints.

[0039] S302: Perform mapping and synthesis processing on multi-viewpoint image data based on a pixel viewpoint mapping model to obtain composite display image data; In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed to achieve the mapping and synthesis of multi-view images, including: Viewpoint map segmentation is performed on the multi-viewpoint image data to obtain multiple sub-image datasets, each corresponding to the multi-viewpoint image data and including sub-images segmented from the viewpoint map. Sub-images corresponding to screen pixel positions are matched among these datasets to obtain composite mapped image data, which represents the sub-images corresponding to screen pixel positions. Image synthesis based on screen pixel positions is then performed on the composite mapped image data to obtain composite display image data. Based on the display screen sub-pixels and the aforementioned pixel viewpoint mapping model, the viewpoint corresponding to each sub-pixel is determined. Pixel color is extracted from the viewpoint map corresponding to that viewpoint to obtain the color of the sub-pixel. The above mapping process is then applied to all sub-pixels in the display screen to obtain the mapped and synthesized image.

[0040] S303: Perform image optimization processing based on display calibration on the composite display image data to obtain the resulting three-dimensional content display data.

[0041] In some optional embodiments of this application, a multi-view naked-eye 3D content generation method is proposed to iteratively optimize the display effect of the above-mentioned composite mapping image, including: Acquire image display test data, which includes first test result data and second test result data, wherein the first test result data is used to represent image ghosting, and the second test result data is used to represent image depth feedback; In an optional embodiment of this application, the image display test data is diagnostic data obtained by observing the aforementioned composite mapped image on a real device screen, including ghosting detection and depth comfort feedback data. Further, the aforementioned ghosting detection includes: taking the aforementioned 9-camera shooting array as an example, by rapidly switching between camera 4 viewpoints and camera 5 viewpoints, abrupt changes or remnants at object edges can be detected; if present, the composite mapped image exhibits ghosting; alternatively, it can be observed by the human eye, observing with one eye in front of the screen, slightly moving the head left and right; if the image suddenly becomes blurry and ghosting appears when the eye transitions from one viewpoint to the next, and then becomes clear again, it indicates crosstalk between adjacent viewpoints. The aforementioned depth comfort feedback includes the depth of objects outside the screen observed on a real device screen, obtained through audience feedback and 3D content type.

[0042] Based on the first test result data, the multi-view image data is subjected to a first optimization process to obtain the first optimized multi-view image data. The first optimized multi-view image data is then subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data. In an optional embodiment of this application, when the composite mapped image has the above-mentioned ghosting, the above-mentioned multi-camera shooting array constructed in the virtual environment is optimized, including: reducing the baseline length and reducing the spacing between cameras in the multi-camera shooting array; the rendering process in step S103 can also be adjusted by adjusting the rendering contrast pair and increasing the brightness difference to reduce crosstalk; the above steps S301 to S303 are executed iteratively until the crosstalk in the optimized image display test data is lower than the preset crosstalk threshold, and the result is output as three-dimensional content display data.

[0043] Based on the second test result data, the multi-view image data is subjected to a second optimization process to obtain second optimized multi-view image data. The second optimized multi-view image data is then subjected to pixel-mapping-based image synthesis processing to obtain the resulting 3D content display data.

[0044] In an optional embodiment of this application, a depth comfort zone is set, wherein the comfort limit is set to the out-of-screen object not exceeding 20%-30% of the screen width, wherein the out-of-screen object is defined as an object whose depth is less than the depth ZPP of the screen plane; audience feedback is obtained, and it is determined that the out-of-screen depth corresponding to the audience feedback is too large, and the multi-camera shooting array constructed in the virtual environment is optimized, including: adjusting the zero-time-difference plane, moving the multi-camera shooting array forward as a whole or moving the scene objects backward as a whole to reduce the depth of the screen plane; reducing the baseline length, reducing the spacing between cameras in the multi-camera shooting array; after completing the above optimization; iteratively executing the above steps S301~S303 until the audience is within the comfort limit, and outputting the result 3D content display data.

[0045] In this embodiment of the application, by performing optimization processing on the above images based on crosstalk cancellation and deep comfort zone control, ghosting is reduced, and viewer dizziness and visual fatigue are reduced.

[0046] In some optional embodiments of this application, a multi-view naked-eye 3D content generation device is proposed. Figure 4 A schematic diagram of a multi-view naked-eye 3D content generation device provided in this application is shown below. Figure 4 As shown, it includes: The data acquisition module 41 is used to acquire data to be processed, wherein the data to be processed includes hardware data to be processed and content data to be processed, the hardware data to be processed is data representing the hardware for displaying three-dimensional content, and the content data to be processed is data representing the content for displaying three-dimensional content. The hardware parameter calibration module 42 is used to perform test-based hardware parameter calibration processing on the data to be processed to obtain calibrated hardware parameter data, wherein the calibrated hardware parameters are parameter data used to represent the mapping relationship between pixels and lenses. The multi-view image generation module 43 is used to perform multi-view generation processing based on virtual acquisition on the three-dimensional content data to be processed to obtain multi-view image data, wherein the multi-view image data is data used to represent multi-view sequence frames; The pixel mapping synthesis module 44 is used to perform pixel mapping-based image synthesis processing on the calibration hardware parameters and the multi-view image data to obtain the resulting three-dimensional content display data.

[0047] The specific methods of execution of each unit in the above embodiments have been described in detail in the embodiments of the method, and will not be elaborated here.

[0048] In summary, this application involves acquiring data to be processed, which includes hardware data to be processed and content data to be processed. The hardware data to be processed represents the hardware used for displaying 3D content, and the content data to be processed represents the content to be displayed in 3D. The data to be processed undergoes test-based hardware parameter calibration to obtain calibrated hardware parameter data, which represents the mapping relationship between pixels and lenses. The 3D content data to be processed undergoes multi-viewpoint generation based on virtual acquisition to obtain multi-viewpoint image data, which represents multi-viewpoint sequence frames. The calibrated hardware parameters and the multi-viewpoint image data undergo pixel-mapping-based image synthesis to obtain the resulting 3D content display data. By performing pixel-mapping processing on the multi-viewpoint images obtained from virtual acquisition and the calibrated hardware parameters to obtain the resulting 3D display data, the technical effect of improving 3D display effect and hardware mapping adaptability is achieved.

[0049] It should be noted that the steps shown in the flowchart in 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 may be executed in a different order than that shown here.

[0050] Obviously, those skilled in the art should understand that the various units or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0051] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for generating multi-view naked-eye 3D content, characterized in that, include: Acquire data to be processed, wherein the data to be processed includes hardware data to be processed and content data to be processed, wherein the hardware data to be processed is data representing the hardware used to display 3D content, and the content data to be processed is data representing the content used to display 3D content; The hardware data to be processed is subjected to test-based hardware parameter calibration processing to obtain calibrated hardware parameter data, wherein the calibrated hardware parameter data is parameter data used to represent the mapping relationship between pixels and lenses; The content data to be processed is subjected to multi-view generation processing based on virtual acquisition to obtain multi-view image data, wherein the multi-view image data is data used to represent multi-view sequence frames; The calibration hardware parameter data and the multi-view image data are subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data.

2. The multi-viewpoint naked-eye 3D content generation method according to claim 1, characterized in that, The hardware data to be processed is subjected to test-based hardware parameter calibration processing to obtain calibrated hardware parameter data, including: The hardware data to be processed is subjected to a test map generation process based on resolution matching to obtain a hardware test map; The hardware screen is tested according to the hardware test diagram to obtain hardware test result data, wherein the hardware test result data is used to represent the display data of the test diagram on the display hardware; The hardware test result data is subjected to parameter calibration processing based on screen analysis to obtain the calibrated hardware parameter data.

3. The multi-viewpoint naked-eye 3D content generation method according to claim 2, characterized in that, The hardware test result data is subjected to parameter calibration processing based on screen analysis to obtain the calibrated hardware parameter data, including: The hardware test result data is processed by image feature extraction to obtain image feature data, wherein the image feature data is feature data used to represent the contrast and channel separation of the displayed image, and the displayed image is the display of the test image on the display hardware; The image feature data is filtered based on a preset image feature threshold to obtain target image feature data; Determine the hardware parameters corresponding to the target image features to obtain the calibration hardware parameter data.

4. The multi-viewpoint naked-eye 3D content generation method according to claim 1, characterized in that, The content data to be processed is subjected to multi-viewpoint generation processing based on virtual acquisition to obtain multi-viewpoint image data, including: The viewpoint parameter data is calculated and processed on the content data to be processed to obtain virtual viewpoint parameter data; A multi-camera shooting array is constructed based on the virtual viewpoint parameter data to obtain a virtual multi-camera shooting array. The virtual multi-camera array is used to capture and process the content data to be processed, thereby obtaining the multi-viewpoint image data.

5. The multi-viewpoint naked-eye 3D content generation method according to claim 1, characterized in that, The calibration hardware parameter data and the multi-view image data are subjected to pixel-mapping-based image synthesis processing to obtain the resulting 3D content display data, which includes: The calibration hardware parameter data is processed to construct a pixel mapping model, resulting in a pixel viewpoint mapping model; The multi-viewpoint image data is subjected to mapping and synthesis processing based on the pixel viewpoint mapping model to obtain composite display image data; The composite display image data is subjected to image optimization processing based on display calibration to obtain the resulting three-dimensional content display data.

6. The multi-viewpoint naked-eye 3D content generation method according to claim 5, characterized in that, The multi-viewpoint image data is subjected to mapping and synthesis processing based on the pixel viewpoint mapping model to obtain composite display image data, including: The multi-viewpoint image data is subjected to viewpoint graph segmentation processing to obtain multiple sub-image datasets, wherein the multiple sub-image datasets correspond to the multi-viewpoint image data, and each sub-image dataset includes sub-images segmented by the viewpoint graph. In the plurality of sub-image datasets, sub-images corresponding to screen pixel positions are matched to obtain composite mapping image data, wherein the composite mapping image data is data used to represent the sub-images corresponding to the screen pixel positions; The composite mapped image data is processed based on screen pixel positions to obtain the composite display image data.

7. The multi-viewpoint naked-eye 3D content generation method according to claim 5, characterized in that, The composite display image data is subjected to image optimization processing based on display calibration to obtain the resulting three-dimensional content display data, which includes: Acquire image display test data, wherein the image display test data includes first test result data and second test result data, wherein the first test result data is data used to represent image ghosting, and the second test result data is data used to represent image depth feedback; Based on the first test result data, the multi-view image data is subjected to a first optimization process to obtain first optimized multi-view image data. The first optimized multi-view image data is then subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data. Based on the second test result data, the multi-view image data is subjected to a second optimization process to obtain second optimized multi-view image data. The second optimized multi-view image data is then subjected to pixel-mapping-based image synthesis processing to obtain the resulting three-dimensional content display data.

8. A multi-viewpoint naked-eye 3D content generation device, characterized in that, include: The data acquisition module is used to acquire data to be processed, wherein the data to be processed includes hardware data to be processed and content data to be processed, wherein the hardware data to be processed is data representing the hardware for displaying 3D content, and the content data to be processed is data representing the content for displaying 3D content; The hardware parameter calibration module is used to perform test-based hardware parameter calibration processing on the hardware data to be processed to obtain calibrated hardware parameter data, wherein the calibrated hardware parameter data is parameter data used to represent the mapping relationship between pixels and lenses. A multi-view image generation module is used to perform multi-view generation processing based on virtual acquisition on the content data to be processed to obtain multi-view image data, wherein the multi-view image data is data used to represent multi-view sequence frames; The pixel mapping synthesis module is used to perform pixel mapping-based image synthesis processing on the calibration hardware parameter data and the multi-viewpoint image data to obtain the resulting three-dimensional content display data.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the multi-view naked-eye 3D content generation method according to any one of claims 1-7.

10. An electronic device, characterized in that, include: At least one processor; The at least one processor is also connected in communication with a memory, wherein the memory stores a computer program that can be executed by the at least one processor to cause the at least one processor to perform the multi-view naked-eye 3D content generation method according to any one of claims 1-7.

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