Method for Simulating User Perception for Providing 360-Degree Images and Apparatus for Implementing the Same

Abstract

The present invention relates to a user perception simulation method for providing a 360-degree image and an apparatus for performing such a method. The user perception simulation method for providing a 360-degree image may include the step of an anamorphic image generating unit of a spherical display device generating an anamorphic image that provides a sense of depth to a user at a specific location, and the step of an anamorphic image simulation unit of a spherical display device receiving projection environment information and simulating the anamorphic image by calculating a retinal image according to the movement of the viewer.

Description

Technology Field

[0001] The present invention relates to a user perception simulation method for providing 360-degree images and an apparatus for performing such a method. More specifically, the invention relates to a user perception simulation method for providing 360-degree images and an apparatus for performing such a method, for making anamorphic content or perspective projection-based content appear natural and immersive from multiple viewer viewpoints as well as from a specific viewer's viewpoint. Background Technology

[0002] Recently, complex immersive media environments combining spherical or hemispherical LED displays, projection mapping, holograms, and anamorphic content are rapidly spreading in digital theme parks, multi-cultural spaces, and immersive exhibition halls to provide visitors with realistic experiences. Unlike simple flat images, these complex contents project images onto three-dimensional structures and irregular spaces or map along LED pixel arrays; therefore, it is very important to accurately predict the content output results in advance.

[0003] Conventionally, simulations were provided that merely previewed projection results on a 2D screen based on conditions such as the projector's position, brightness, throw ratio, warping, and blending. However, accurate result prediction was impossible for environments such as theme parks and exhibition spaces where complex sculptures, curved structures, and spherical / hemisphere LEDs are mixed, and there was a limitation in that it could not reflect the actual visual experience that varies depending on the visitor's viewpoint.

[0004] For example, in the case of spherical LED displays, because LED pixels are arranged along the curved surface, problems arise where content is excessively distorted or compressed in certain areas. In particular, when a viewer moves to the center, side, or bottom, the same content appears in a completely different form, and conventional technology has not been able to provide a function to simulate this in real time.

[0005] In addition, even in projection mapping environments, shadows or brightness imbalances occur due to the shape of 3D structures, projection angles, and changes in ambient lighting, but existing tools lacked the ability to precisely predict these physical changes or visualize changes in lighting, sound, and special effects over time (time-based cue).

[0006] In the case of anamorphic content, it is viewed normally only at a specific viewing point (Hot Spot) and is perceived as a distorted scene at other locations. Therefore, simulation technology is essential to recreate the on-site environment in 3D and check in advance how the scene will look from various viewer perspectives before content production. However, conventional technology has not been able to provide scene prediction based on off-axis projection using the actual location coordinates of the viewers.

[0007] Therefore, there is a growing need for user perception-based simulation technology capable of precisely predicting actual output results in immersive media environments that combine complex spatial structures, spherical / hemispherical LED displays, multiple projectors, and lighting and sound systems. This technology comprehensively considers scene perception results from various viewer viewpoints, changes in content, lighting, and special effects based on time-based cues, variations in projector and LED hardware specifications, the anamorphic scene generation process, and physical characteristics such as shadows, luminance, and distortion. The problem to be solved

[0008] The present invention aims to solve all of the aforementioned problems.

[0009] In addition, the present invention allows for cost and time savings through pre-installation verification, and enables the verification of the actual output characteristics of spherical / hemi-spherical curved LED displays prior to on-site installation, thereby significantly reducing unnecessary equipment movement, calibration work, and content modification costs. Furthermore, by simulating distortion, clarity, brightness, color reproduction, and pixel exposure that will be seen by actual people from various viewing positions through accurate perception quality prediction based on the viewer's viewpoint, optimal content production and LED placement strategies can be established.

[0010] In addition, the present invention enables the optimization of resolution / distortion of 360-degree content, facilitates advanced production such as the creation of anamorphic content based on a specific point (sweet spot) through spherical mapping and off-axis distortion correction simulation, and ensures image contrast and readability by reviewing in advance the effects of light shielding from surrounding light sources, reflectors, and structures through the optimization of actual production through lighting and environmental reflection simulation. means of solving the problem

[0011] A representative configuration of the present invention for achieving the above objective is as follows.

[0012] According to one embodiment of the present invention, a user perception simulation method for providing a 360-degree image may include the step of an anamorphic image generating unit of a spherical display device generating an anamorphic image that provides a sense of depth to a user at a specific location, and the step of an anamorphic image simulation unit of the spherical display device receiving projection environment information and simulating the anamorphic image by calculating a retinal image according to the movement of the viewer.

[0013] Meanwhile, the anamorphic image generation unit can determine a viewer standard based on spherical display hardware information and spatial information, and generate the anamorphic image.

[0014] In addition, the anamorphic image simulation unit receives the projection environment information and models the direction, intensity, and color of light emitted by the light-emitting unit of the projection surface of the spherical display, thereby simulating the image formed on the retina of the viewer depending on the viewer's stationary or moving state.

[0015] According to another embodiment of the present invention, a spherical display device for performing a user perception simulation for providing a 360-degree image may include an anamorphic image generation unit implemented to generate an anamorphic image that provides a sense of depth to a user at a specific location, and an anamorphic image simulation unit implemented to receive projection environment information and calculate a retinal image according to the movement of the viewer to simulate the anamorphic image.

[0016] Meanwhile, the anamorphic image generation unit can determine a viewer standard based on spherical display hardware information and spatial information, and generate the anamorphic image.

[0017] In addition, the anamorphic image simulation unit receives the projection environment information and models the direction, intensity, and color of light emitted by the light-emitting unit of the projection surface of the spherical display, thereby simulating the image formed on the retina of the viewer depending on the viewer's stationary or moving state. Effects of the invention

[0018] According to the present invention, costs and time can be reduced through pre-installation verification, and the actual output characteristics of spherical / hemisphere curved LED displays can be confirmed prior to on-site installation, thereby significantly reducing unnecessary equipment movement, calibration work, and content modification costs. Furthermore, by simulating distortion, clarity, brightness, color reproduction, pixel exposure, etc., that will be seen by actual people from various viewing positions through accurate perception quality prediction based on the viewer's viewpoint, optimal content production and LED placement strategies can be established.

[0019] In addition, according to the present invention, the resolution / distortion of 360-degree content can be optimized, and through spherical mapping and off-axis distortion correction simulation, advanced production such as the creation of anamorphic content based on a specific point (sweet spot) can be facilitated, and through the optimization of actual production through lighting and environmental reflection simulation, the effects of light blocking by surrounding light sources, reflectors, and structures can be reviewed in advance to ensure image contrast and readability. Brief explanation of the drawing

[0020] FIG. 1 is a conceptual diagram showing a device for performing 360-degree image mapping on a spherical display according to an embodiment of the present invention. FIG. 2 is a conceptual diagram showing the operation of an unstructured pixel map generation module according to an embodiment of the present invention. FIG. 3 is a conceptual diagram showing the operation of a content characteristic analysis module according to an embodiment of the present invention. FIG. 4 is a conceptual diagram showing the operation of an adaptive 360-degree mapping engine according to an embodiment of the present invention. FIG. 5 is a conceptual diagram showing the operation of a display structure-based correction and actual measurement feedback module according to an embodiment of the present invention. FIG. 6 is a conceptual diagram illustrating a method for providing content by performing user perception simulation on a spherical display according to an embodiment of the present invention. FIG. 7 is a conceptual diagram showing the operation of an anamorphic image generation unit according to an embodiment of the present invention. FIG. 8 is a conceptual diagram showing the operation of an anamorphic image simulation unit according to an embodiment of the present invention. FIG. 9 is a conceptual diagram showing a spherical display implemented through 360-degree image mapping according to an embodiment of the present invention. Specific details for implementing the invention

[0021] The following detailed description of the invention refers to the accompanying drawings, which illustrate specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that various embodiments of the invention are different but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be modified from one embodiment to another without departing from the spirit and scope of the invention. It should also be understood that the location or arrangement of individual components within each embodiment may be modified without departing from the spirit and scope of the invention. Accordingly, the following detailed description is not meant to be limiting, and the scope of the invention should be understood to encompass the scope claimed by the claims and all equivalents thereof. Similar reference numerals in the drawings indicate identical or similar components across various aspects.

[0022] Hereinafter, in order to enable a person skilled in the art to easily practice the present invention, various preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0024] Hereinafter, the term "spherical display" used in the embodiments of the present invention may be interpreted to include displays of various shapes having curvature, even if they are not spherical.

[0025] In addition, the term "360-degree image" can be interpreted to mean an image output on a spherical display, and includes images output on displays of various shapes that have some curvature, even if they are not 360 degrees.

[0026] In addition, for the sake of convenience of explanation, it is assumed that the spherical display emits light based on LEDs; however, various modules that can be utilized as displays other than LEDs may be used, and such embodiments may also be included within the scope of the present invention.

[0027] FIG. 1 is a conceptual diagram showing a device for performing 360-degree image mapping on a spherical display according to an embodiment of the present invention.

[0028] FIG. 1 discloses a spherical display device for performing mapping of a 360-degree image on a spherical display.

[0029] Referring to FIG. 1, the spherical display device may include a spherical display (100) and a 360-degree image generation unit (110), and the 360-degree image generation unit (110) may include a spherical coordinate-based irregular pixel map generation module (120), a content characteristic analysis module (130), an adaptive 360-degree mapping engine (140), a display structure-based correction and actual measurement feedback module (150), and a real-time rendering and output control unit (160).

[0030] The spherical display (100) is a spherical display and can be implemented so that a user can view the output image from any direction by implementing a plurality of LED modules in the spherical shape. The spherical display (100) can output input 360-degree image data through a plurality of LED modules.

[0031] A 360-degree image generation unit (110) can be implemented to generate 360-degree image data that can be output to a spherical display (100). A 360-degree image generation unit (110) can be implemented to generate an original image into a 360-degree image that can be output to a spherical display (100) based on the hardware structure of the spherical display (100).

[0032] A non-uniform pixel map generation module (120) based on spherical coordinates can be implemented to generate a non-uniform pixel map table (or non-uniform pixel map) based on hardware information of a spherical display (100). The hardware information of the spherical display (100) may include information such as the actual LED module arrangement, spacing between LEDs, and radius of the sphere of the spherical display (100) for generating a non-uniform pixel map table. The non-uniform pixel map table is a table for mapping pixels of the spherical display (100) to a generated 360-degree image, and can reflect actual manufacturing errors and LED arrangement deviations, rather than a simple mathematical spherical model.

[0033] The content characteristic analysis module (130) can be implemented to analyze the characteristics of the original video. In order to generate a 360-degree video based on the original video, an analysis of the original video characteristics can be performed. The original video characteristic information may include characteristics that must be considered when converting to a 360-degree video, such as whether text is included, pattern structure, whether person / background is separated, and spatial frequency characteristics. By considering these original video characteristics, distortion sensitivity (weight) can be calculated and the weight of the mapping algorithm can be adjusted.

[0034] The adaptive 360-degree mapping engine (140) can be implemented to apply different correction filters to content types to minimize local distortion that occurs when outputting 360-degree images to a spherical display (100). For example, a distortion minimization priority algorithm may be used as a correction filter for text or UI images, and a uniform distribution algorithm may be used as a correction filter for pattern images. If necessary, a non-linear region-based correction filter may also be used as a correction filter.

[0035] A display structure-based correction and actual measurement feedback module (150) can be implemented to perform calibration shooting on a spherical display (100), calculate the error between the mapping result and the target image, and automatically update the correction parameters. Through this method, shooting data for a 360-degree image output on an actual spherical display (100) is received as feedback data, and correction is performed on the 360-degree image data input to the spherical display, and an image correction table, such as an unstructured pixel map table, can be updated.

[0036] The real-time rendering and output control unit (160) can be implemented to output a 360-degree image to a spherical display (100) in real-time or near-real-time based on 360-degree image data generated based on a spherical coordinate-based irregular pixel map generation module (120), a content characteristic analysis module (130), and an adaptive 360-degree mapping engine (140). The real-time rendering and output control unit (160) can uniformly control the entire 360-degree image by processing multiple LED module zones located on the spherical display (100) in parallel.

[0037] The components according to the embodiments of the present invention may be implemented based on hardware (e.g., a computer server), and the operation of the components described above may be performed on the hardware (e.g., a computer server). Although referred to as components for convenience of explanation, the operations of the components may perform an automated process that did not exist before using computer program code based on hardware components such as a CPU (central processing unit), a GPU (graphic processing unit), and memory.

[0038] More specifically, the operation process of the components performed in the present invention is performed based on the control unit and arithmetic logic unit (ALU) of a processing unit such as a CPU. The operation process of the components can be performed through fetch, decode, and execute performed on hardware such as a CPU.

[0039] In addition, various memory structures (registers, cache memory, main memory, auxiliary memory) may be used for the operation of the operation process of the components according to the embodiment of the present invention, and computer program code using various memory hierarchies may be used for the efficiency of the operation process of the components.

[0040] By performing this computer program code-based automation through hardware, previously unknown processes are automated, and compared to non-automated procedures, image distortion reduction and visual quality improvement can be achieved based on the operation of spherical display devices. It is possible to effectively reduce severe image distortion caused by the spherical structure, enabling more natural and immersive 360-degree video expression.

[0041] Furthermore, optimal mapping is provided for each content type, and compatibility with various spherical LED structures can be ensured. By analyzing the characteristics of the content and applying a mapping algorithm suitable for each type, information loss is minimized even in distortion-sensitive content such as text, patterns, and human images. Additionally, since corrections based on hardware characteristics such as LED arrangement, spacing, and curvature are possible, mapping results of the same quality can be provided even with spherical LEDs from different manufacturers and specifications.

[0042] In addition, real-time mapping is possible, and non-uniformity of the installation environment can be corrected. Through a lightweight mapping engine and parallel processing technology, stable 360-degree mapping can be performed even in real-time or near-real-time environments, and visual consistency in the field can be significantly improved by automatically correcting deviations of the spherical displays actually installed.

[0044] FIG. 2 is a conceptual diagram showing the operation of an unstructured pixel map generation module according to an embodiment of the present invention.

[0045] In FIG. 2, an operation is initiated to generate a non-uniform pixel map table by creating a coordinate system suitable for a spherical display in a non-uniform pixel map generation module based on spherical coordinates.

[0046] Referring to FIG. 2, the unstructured pixel map generation module may include a data input unit (210), a spherical coordinate transformation unit (220), an LED density determination unit (230), a distortion correction weight determination unit (240), and an unstructured pixel map table generation unit (250).

[0047] The data input unit (210) may be implemented to receive data for generating an unstructured pixel map. The data input unit (210) may receive spherical display information and LED module information located on the spherical display. The spherical display information may include the radius of the sphere of the display and information regarding the hardware design structure of the spherical display. The LED module information may receive information regarding the actual 3D coordinates of each LED module, the distance between LED pixels, the boundaries of the LED modules, etc.

[0048] A spherical coordinate transformation unit (220) can be implemented to correspond each LED pixel to each spherical coordinate and transform it. The spherical coordinate transformation unit (220) corresponds each LED pixel to a spherical coordinate system, but the spherical coordinate transformation can be performed by reflecting the actual design of a spherical display that is not a perfect sphere. For example, spherical displays may differ from the ideal spherical shape because the LED module thickness varies and the LED module may protrude or recede slightly. Additionally, differences from the ideal spherical shape may exist due to errors caused by the frame structure and panel bending. Therefore, if spherical coordinate transformation is performed assuming an ideal spherical shape and assuming that the spherical coordinate exists at radius R, straight lines may appear curved, text may be distorted, or patterns may be misaligned. Therefore, in the case of the present invention, a spherical coordinate system is used, but by creating a difference in r (distance from the origin) within the spherical coordinate system to reflect the actual shape of the spherical display, mapping coordinates that reflect the actual depth difference can be generated.

[0049] The LED density determining unit (230) can determine the LED density based on the distance between LED pixels. LED pixels on a spherical display may be arranged unevenly in the latitude and longitude directions. In particular, the number of LED pixels in the same area may vary, such that LED pixels are clustered together near the poles and spread out near the equator. A determination of the LED density can be made by taking these characteristics into account. Neighboring LED pixels within a certain radius around a target LED pixel can be determined based on a target LED pixel for determining the LED density. The distance in three dimensions can be determined as the actual surface distance between the target LED pixel and the neighboring LED pixel. The reciprocal of the actual surface distance can be determined as the LED density.

[0050] If LED density is not reflected during output, the following problems may occur. In cases where LED density is relatively high, such as in older displays, there are too many LEDs but insufficient information, causing multiple LEDs to copy the same pixel, resulting in blurring or smudging. Conversely, if LED density is relatively low, there may be too few LEDs but too much information, causing intermediate information to disappear, which can lead to broken lines and distorted text.

[0051] To address these issues, information regarding LED density is reflected; when LED density is relatively high, blurring and smudging can be prevented through image processing that samples by cropping the original more finely. When LED density is relatively low, smoothing image processing is performed by averaging the original more broadly to prevent broken lines and distorted text.

[0052] The distortion correction weighting determination unit (240) can be implemented to perform image processing with enlargement weighting applied to areas with relatively low LED density and image processing with compression weighting applied to areas with relatively high LED pixel density, taking into account the LED density determined by the LED density determination unit. That is, when the LED density is relatively low, since there are fewer LEDs, one LED must cover a wider area, so the image space can be expanded by applying enlargement weighting. The enlargement weighting may be a weight to relatively widen the expression area of ​​the original image covered by one LED pixel. Conversely, when the LED density is relatively high, since there are more LEDs, one LED must cover a narrower area, so the image space can be reduced by applying reduction weighting. The reduction weighting may be a weight to relatively reduce the expression area of ​​the original image covered by one LED pixel.

[0053] The irregular pixel map table generating unit (250) can generate an irregular pixel map table. The irregular pixel map table may be a table containing information such as where each LED pixel is located in a spherical space, how densely the LED pixels are arranged, and how a specific LED pixel is connected to surrounding LED pixels.

[0054] The unstructured pixel map table may include LED identifier information, LED 3D position information, spherical orientation information, radius information, local pixel density information, distortion correction weight information, neighbor relationship information, module information, etc.

[0055] LED identifier information may include information about an identifier for identifying LED pixels.

[0056] LED 3D position information may include information about the position of LED pixels in 3D on a spherical display.

[0057] Spherical orientation information is information about the direction the LED pixel is facing, and can be used to determine which direction of the scene in the original image should be displayed.

[0058] Radius information, which is information about how far an LED pixel is from the center of a sphere, can be used to reflect the spherical structure of a spherical display that is not an ideal sphere, as mentioned above.

[0059] Local pixel density information may include information about LED density.

[0060] As described above, distortion correction weight information may include information on enlargement weights and reduction weights as information on spatial scale correction coefficients calculated using LED density, radius information, curvature, etc.

[0061] Neighbor relationship information may include information about neighbor LEDs that are actually adjacent to a target LED based on a specific LED (e.g., target LED). Neighbor relationship information can be used for interpolation, boundary correction, and maintaining pattern continuity.

[0062] Module information is information about the internal coordinates of the LED module and can be used to correct seams occurring at the module boundaries.

[0064] FIG. 3 is a conceptual diagram showing the operation of a content characteristic analysis module according to an embodiment of the present invention.

[0065] In FIG. 3, the operation of a content characteristic analysis module for analyzing content and performing mapping in the content characteristic analysis module is initiated.

[0066] Referring to FIG. 3, the content characteristic analysis module may include a region division unit (310), a visual feature extraction unit (320), a distortion sensitivity calculation unit (330), and a content map generation unit (340).

[0067] The content characteristic analysis module creates a content map by quantifying the parts of the video that must not be distorted, and generates a content recognition-based weighted field that takes user perception into account.

[0068] The region division unit (310) can be implemented to divide a video frame into multiple blocks or segments. Content characteristic analysis can be performed based on the divided blocks, and the video frame can be divided into multiple blocks to analyze the characteristics of the content.

[0069] A visual feature extraction unit (320) may be implemented to extract visual features on a block. Visual features are features for calculating the distortion sensitivity of content and may be basic information for determining the distortion sensitivity felt by a user when viewing an image. Visual features may include information regarding edge density (text / contour), directional pattern (pattern / grid), face / person probability, spatial frequency, etc. Each of the edge density, directional pattern, face / person probability, and spatial frequency may be defined as a sub-visual feature.

[0070] Edge density (text / outline) can be density information about edges within a block. The more edges there are within a block, the more sensitive it can be to distortion. If the content is text, outline, or user interface, there are many edges and it can be very sensitive to distortion. To determine edge density (text / outline), an edge filter is applied and the edge pixel ratio can be calculated.

[0071] Directional patterns (patterns / grids) are used to calculate the intensity of repeating directions (grids, stripes) within a block. The more patterns there are, the more noticeable characteristics become even with slight distortion. Directional patterns (patterns, grids) can be determined through frequency domain (FFT) analysis.

[0072] Face / person probability refers to the probability that a face or person exists within a block. The person region is an area extremely sensitive to shape distortion. Face / person probability can be determined using a face / person detection network.

[0073] Spatial frequency refers to the amount of pixel variation within a block and can be used to detect fine details (hair, textures, characters, etc.). The higher the high frequency, the more susceptible the area may be to resolution loss.

[0074] A distortion sensitivity calculation unit (330) may be implemented to calculate the distortion sensitivity for each block. The distortion sensitivity of a specific block may be a numerical representation of how noticeable a distortion is when it occurs in a specific block. The greater the distortion sensitivity, the more necessary it may be to preserve the shape.

[0075] Distortion sensitivity can be determined by considering the visual characteristics of each block.

[0076] Distortion sensitivity may be determined through the setting of weights for sub-visual characteristics, and multiple visual distortion scores may be defined to determine the risk of visual distortion for semantic-based scoring that considers visual features per block.

[0077] Multiple visual distortion scores for determining the risk of visual distortion can be classified into a first visual distortion score to a third visual distortion score.

[0078] The first visual distortion score is a distortion score for face precision risk, which may be a score regarding the probability of distortion occurring for blocks containing figures and high-frequency blocks. The figure / high-frequency block may be a block containing eyes, mouths, etc., as content.

[0079] The second visual distortion score is a text readability risk score that may be a score regarding the likelihood of distortion occurring that lowers the readability of the text. The second visual distortion score may be a score regarding the likelihood of distortion occurring for a block containing text.

[0080] The third visual distortion score may be a pattern distortion risk score, which is a score regarding the probability of distortion occurring for the pattern. The third visual distortion score may be a score regarding the probability of distortion occurring for the block containing the pattern.

[0081] In the present invention, at least one output mode is set according to the content output from the spherical display, and image correction can be performed and output according to the output mode.

[0082] Output modes may include face mode, text mode, and pattern mode. If correction for distortion is required at the block or block set level, at least one output mode may be set at the block or block set level to perform correction on the image. Whether correction for distortion is required at the block or block set level may be determined according to the set first visual distortion score threshold, second visual distortion score threshold, and third visual distortion score threshold.

[0083] The first visual distortion score threshold, the second visual distortion score threshold, and the third visual distortion score threshold can be set by feedback values ​​generated by a display structure-based correction and actual measurement feedback module, and can be set differently depending on the position of the LED module on the spherical display. That is, in the present invention, different visual distortion score thresholds can be set by considering not only the blocks and block sets corresponding to the content output from the LED module, but also the position where the user views the LED module.

[0084] A visual distortion score threshold that considers the position where the user views the LED module is set as a default threshold, and a threshold that considers the characteristics of the content output from the LED module is set as an adaptive threshold that changes adaptively, so that the visual distortion score threshold can be determined by changing according to the output of the content.

[0085] The content map generation unit (340) may include information regarding visual distortion scores for each block. The content map may include information regarding visual distortion scores for each block that change according to changes in time due to content output. That is, the content map may include scored information regarding the possibility of distortion for each block according to the content output according to changes in time.

[0087] FIG. 4 is a conceptual diagram showing the operation of an adaptive 360-degree mapping engine according to an embodiment of the present invention.

[0088] In FIG. 4, the operation of a 360-degree mapping engine is initiated to determine the image sample location of each pixel by considering the LED structure on the spherical display and the analysis results of the content characteristic analysis module.

[0089] Referring to Fig. 4, an unstructured pixel map table generated by an unstructured pixel map generation module, a content map generated by a content characteristic analysis module, and an original image can be input into an adaptive 360-degree mapping engine.

[0090] The adaptive 360-degree mapping engine can calculate the first image coordinate position of each LED pixel based on an unstructured pixel map table (step S410).

[0091] The first image coordinate position is about how the corresponding LED pixel represents the position corresponding to which pixel in the original image. The original image is usually composed of planar coordinates (u, v), which are 360° panoramas (equirectangular), cubemaps, or general 2D images, and it can be determined which information a specific LED pixel represents in the image based on an unstructured pixel map table. The adaptive 360-degree mapping engine can calculate the first image coordinate position of each LED pixel based on information about the actual position of the LED on the unstructured pixel map table and information about the spherical display geometry model.

[0092] The adaptive 360-degree mapping engine can determine the second image coordinate position by performing hardware distortion correction (step S420).

[0093] The adaptive 360-degree mapping engine can correct the first image coordinate position output by the LED pixel by moving it to the second image coordinate position by considering structural errors, local pixel density information and distortion correction weight information in an unstructured pixel table.

[0094] The adaptive 360-degree mapping engine can determine the third image coordinate position by reflecting content sensitivity (step S430).

[0095] The adaptive 360-degree mapping engine can correct the second image coordinate position to the third image coordinate position by considering the generated content map and the set visual distortion score threshold. If the visual distortion score based on the content map is within the visual distortion score threshold according to the output mode, the second image coordinate position can be set as the third image coordinate position. Conversely, if the visual distortion score based on the content map exceeds the visual distortion score threshold according to the output mode, the second image coordinate position can be changed to the third image coordinate position, which is a position to reduce distortion. That is, based on the position changed through this method, if distortion occurs, a procedure to reduce distortion by considering the characteristics of the content is finally performed, and output based on the third image coordinate can be achieved.

[0097] FIG. 5 is a conceptual diagram showing the operation of a display structure-based correction and actual measurement feedback module according to an embodiment of the present invention.

[0098] FIG. 5 discloses a method for correcting an image output from a spherical display in a display structure-based correction and actual measurement feedback module.

[0099] Referring to FIG. 5, the display structure-based correction and actual measurement feedback module can capture a reference image output from a spherical display (step S510).

[0100] The reference image is an image having a specific pattern, such as a latitude / longitude grid, radial lines, or circular rings, and may be an image where it is possible to confirm normal operation if a specific pixel of the reference image is output to a specific LED pixel. Capture can be performed by capturing the output results of the spherical display using multiple external cameras or a mobile scanning camera.

[0101] The display structure-based correction and actual measurement feedback module can calculate the error field (step S520).

[0102] The error field is calculated by comparing the reference image and the actual image to determine the error vector, and in this way, a distortion vector field for the entire spherical display can be generated as the error field.

[0103] The display structure-based correction and actual measurement feedback module transmits an error field, and an unstructured pixel map table can be updated based on the error field (step S530).

[0104] Information about the error vectors included in these error fields is accumulated in the LED mapping coordinates, and the unstructured pixel map table can be updated.

[0106] FIG. 6 is a conceptual diagram illustrating a method for providing content by performing user perception simulation on a spherical display according to an embodiment of the present invention.

[0107] FIG. 6 discloses a method for providing an image that provides a sense of depth to the user, such as an anamorphic image.

[0108] Referring to Fig. 6, anamorphic images are produced to maximize the sense of depth when viewed from a specific angle. Anamorphic images are produced to blur the boundary between the screen and real space, providing the user with a sense of immersion similar to 3D images.

[0109] A spherical display device according to an embodiment of the present invention may include an anamorphic image generation unit (610) and an anamorphic image simulation unit (620) for providing such an anamorphic image.

[0110] The anamorphic image generation unit (610) can be implemented to generate an anamorphic image that provides a sense of depth to a user at a specific location.

[0111] The anamorphic image generation unit (610) can generate an anamorphic image based on anamorphic image input data. The anamorphic image input data may include spherical display hardware information (e.g., LED module placement, spacing between LED pixels, radius of a sphere, etc.), spatial information (e.g., projection surface 3D shape information), viewer reference point information, original image information, etc. The spatial information may include structural information and geometric information for reproducing the actual physical space where the anamorphic image is implemented on a three-dimensional coordinate system. The anamorphic image generation unit can generate a viewer reference, calculate a scene in reverse direction relative to the viewer reference, and thereby generate an anamorphic image.

[0112] A specific method for generating an anamorphic image of the anamorphic image generation unit (610) will be described later.

[0113] The anamorphic image simulation unit (620) can be implemented to pre-calculate how the generated anamorphic image is perceived by the viewer in the actual space.

[0114] The anamorphic image simulation unit (620) can simulate whether a sense of depth is felt, simulate the perception of users from various angles, and perform image mapping by taking this into account. The anamorphic image simulation unit (620) can receive actual projection environment information and evaluate and optimize the quality of the anamorphic image by calculating the retinal image according to the viewer's movement.

[0115] The specific anamorphic image simulation operation of the anamorphic image simulation unit (620) will be described later.

[0116] The anamorphic image simulation unit (620) and the anamorphic image generation unit (610) according to an embodiment of the present invention may be implemented based on hardware (e.g., a computer server), and the operation of the components described above may be performed on hardware (e.g., a computer server). Although expressed as components for convenience of explanation, the operations of the components may perform an automated process that did not exist before using computer program code based on hardware components such as a CPU (central processing unit), a GPU (graphic processing unit), and memory.

[0117] More specifically, the operation process of the components performed in the present invention is performed based on the control unit and arithmetic logic unit (ALU) of a processing unit such as a CPU. The operation process of the components can be performed through fetch, decode, and execute performed on hardware such as a CPU.

[0118] In addition, various memory structures (registers, cache memory, main memory, auxiliary memory) may be used for the operation of the operation process of the components according to the embodiment of the present invention, and computer program code using various memory hierarchies may be used for the efficiency of the operation process of the components.

[0119] By performing such computer program code-based automation through hardware, previously unknown processes are automated. Compared to non-automated procedures, costs and time can be reduced through pre-installation verification. Furthermore, the actual output characteristics of spherical / hemi-spherical curved LED displays can be verified prior to on-site installation, thereby significantly reducing unnecessary equipment movement, calibration work, and content modification costs. Additionally, by accurately predicting perceptual quality based on the viewer's viewpoint, distortion, clarity, brightness, color reproduction, and pixel exposure that a person will actually see from various viewing positions can be simulated, thereby establishing optimal content production and LED placement strategies. Moreover, according to the present invention, resolution and distortion optimization of 360-degree content is possible. Through spherical mapping and off-axis distortion correction simulation, advanced production such as anamorphic content production based on a specific point (sweet spot) becomes easier. Additionally, through the optimization of actual production via lighting and environmental reflection simulation, the effects of light blocking by surrounding light sources, reflectors, and structures can be reviewed in advance to ensure image contrast and readability.

[0121] FIG. 7 is a conceptual diagram showing the operation of an anamorphic image generation unit according to an embodiment of the present invention.

[0122] FIG. 7 discloses a specific method for generating an anamorphic image in an anamorphic image generation unit.

[0123] Referring to FIG. 7, the amorphous image generation unit may include a data input unit (710), a projection space setting unit (720), a viewer reference setting unit (730), a viewer reference scene calculation unit (740), a multi-surface and irregular structure corresponding unit (750), and an image generation unit (760).

[0124] The data input unit (710) can be implemented to receive anamorphic image input data. As data for generating an anamorphic image, the anamorphic image input data may include spherical display hardware information (e.g., LED module placement, spacing between LED pixels, radius of a sphere, etc.), spatial information (e.g., projection surface 3D shape information), viewer reference point information, original image information, etc.

[0125] The projection space setting unit (720) can set the projection space. The projection space is a three-dimensional shape of the actual surface on which the anamorphic image is projected or displayed, and the projection space can be set based on projection space information (e.g., walls, floors, curved surfaces, stairs, LED panels, etc.).

[0126] More specifically, the projection space setting unit (720) can be implemented not merely to model the surface, but to create an anamorphic-only projection space model.

[0127] The projection space setting unit (720) can set the projection space through the following four steps.

[0128] In the first step, the projection space setting unit (720) can first define multiple surfaces integrally as a projection space. For example, multiple surfaces having different positions, directions, and curvatures, such as walls, floors, curved surfaces, stairs, LED panels, etc., can be defined integrally as one continuous projection space.

[0129] In the second step, the projection space setting unit (720) can generate a surface unit division structure. The projection space setting unit (720) can divide the projection surface into pixel units, LED module units, or polygon units, and define each division unit as an independent light-emitting unit.

[0130] In the third step, the projection space setting unit (720) can assign surface attributes for viewer reference calculation. For each division unit, spatial position, surface orientation, curvature information, and surface attributes can be included as metadata.

[0131] In the fourth step, the projection space setting unit (720) can generate boundary continuity information between surfaces. The projection space setting unit (720) defines boundary relationships between adjacent surfaces and can prevent visual discontinuity based on the boundary continuity information between surfaces when an anamorphic image is connected across multiple surfaces.

[0132] That is, the projection space setting unit (720) can be configured into an integrated projection space based on light-emitting units so that a plurality of irregular surfaces can be calculated in reverse direction relative to the viewer.

[0133] The viewer reference setting unit (730) can be implemented to set a coordinate system with the viewer's location as the origin. In this case, the viewer reference in the viewer reference setting unit (730) can be set as a visual reference coordinate system that includes not just a simple point, but also the height of the eyes, the direction of the field of view, and the distance between the left and right eyes.

[0134] The viewer standard setting unit (730) can set the viewer standard through the following four steps.

[0135] In the first step, a visual center coordinate system can be generated. The viewer reference setting unit (730) can set a visual center coordinate system with the viewer's eye position as the origin and link it with an absolute coordinate system that reflects the floor reference and gravity direction.

[0136] In the second stage, a binocular-based visual model may be applied to establish a viewer standard. The viewer standard setting unit (730) can reflect the relative positions of the left and right eyes to enable perception based on both disparities rather than monocular perception.

[0137] In the third step, modeling of the field of view and gaze direction can be performed. The viewer reference setting unit (730) can model the viewer's basic gaze direction and horizontal / vertical / field of view angle ranges.

[0138] In the fourth step, multiple viewer reference candidate generation can be performed. The viewer reference setting unit (730) can simultaneously set not only one reference point but also multiple candidate viewer locations, and based on this, the optimal viewing location can be searched.

[0139] The viewer-based scene calculation unit (740) divides the projection surface (e.g., LED, wall, structure) into multiple pixels or polygons, views each position of the projection surface as a single light-emitting point, and can virtually track the line of sight entering the viewer's eye from that point.

[0140] The viewer-based scene calculation unit (740) can calculate which part of the original scene the viewer sees for every projection surface position when light is emitted from a pixel of the projection surface and enters the viewer's eye. Through this, color and depth information of the original scene corresponding to each position of the projection surface is determined, and the result can be recorded at that position. The image generated by this process can be recognized as a normal 3D scene when the viewer stands at a designated position, as the distortion is automatically visually corrected.

[0141] The viewer-based scene calculation unit (740) can calculate the viewer-based scene through the following four steps.

[0142] In the first step, gaze tracking can be performed for each projection surface light-emitting unit. The viewer-reference scene calculation unit (740) can virtually track the gaze directed toward the viewer's eyes from the corresponding location for each light-emitting unit defined in the projection space setting unit.

[0143] In the second step, the original scene correspondence relationship can be calculated. The viewer-based scene calculation unit (740) can calculate which location in the original 3D scene corresponds to the tracked gaze and obtain color, depth, and shape information.

[0144] More specifically, the line-projection plane intersection point can be calculated to determine which projection plane the line intersects with and at what location. The intersection point may be a perceptible point on the actual output surface. Additionally, through backtracking the corresponding location on the original 3D scene, the position corresponding to that point in the original 3D scene coordinate system before distortion can be calculated based on the intersection point. In this case, instead of simple coordinate mapping, a visual correspondence relationship reflecting the viewer's line direction and distance relationship may be used.

[0145] In the third stage, off-axis perception correction can be performed. The viewer-reference scene calculation unit can calculate distortion relationships so that a normal stereoscopic shape is perceived from the viewer's perspective even when the center axis of the viewer and the projection plane do not coincide.

[0146] First, the state of misalignment between the viewer and the projection plane axis can be determined. The angle and positional deviation between the viewer's center of sight axis and the projection plane's reference axis can be calculated.

[0147] Next, a virtual reference axis is established as a perception standard, allowing for the setting of a virtual reference axis perceived as frontal from the viewer's perspective, rather than the actual center axis of the projection plane. Although the virtual reference axis does not physically exist, it can serve as a frontal reference from the viewer's perspective.

[0148] Next, through the recalculation of distortion relationships based on the virtual reference axis, recalculation of the distortion relationships can be performed so that the depth, size, and shape of the original scene are perceived normally based on the virtual reference axis.

[0149] In the fourth step, the maintenance of continuity between surfaces can be calculated. The viewer-based scene calculation unit (740) can be adjusted so that scene information calculated on different surfaces is perceived as one continuous scene from the viewer's perspective.

[0150] The multi-surface and irregular structure corresponding unit (750) can be implemented to generate anamorphic images simultaneously on multiple irregular surfaces, such as walls at different angles, floors, inclined structural curves, or spherical displays, rather than on a single plane. The multi-surface and irregular structure corresponding unit (750) can generate different distorted images for each surface by considering both the position and orientation of each surface so that a consistent three-dimensional scene is formed from the perspective of a single viewer.

[0151] The multi-surface and amorphous structure corresponding part (750) can operate in the following four steps.

[0152] In the first step, independent distortion patterns for each surface can be generated. The multi-surface and amorphous structure corresponding part (750) can generate individual distortion patterns for each surface, taking into account position / direction / curvature.

[0153] Spaces where anamorphic content is applied typically feature walls at different angles, a mixture of vertical, horizontal, and inclined surfaces, and the simultaneous presence of flat and curved surfaces. In such spaces, applying a single global distortion method may result in form collapse or depth discontinuity on other surfaces, even if the three-dimensionality is correct on specific surfaces. Therefore, the present invention allows surfaces to be treated as independent distortion targets.

[0154] The multi-surface and irregular structure corresponding unit (750) generates individual distortion patterns for each projected surface in the following order. First, the multi-surface and irregular structure corresponding unit (750) can separate and identify surfaces by unit. Each surface within the projection space can be classified as flat / curved and vertical / horizontal / slanted, and a unique identifier can be assigned to each surface.

[0155] Next, the multi-surface and irregular structure corresponding unit (750) can extract surface-specific geometric information. Position information, direction information, and curvature information are individually obtained for each surface. Information such as position information (relative position in a viewer-reference coordinate system), direction information (normal direction and inclination of the surface), and curvature information (whether it is flat or changes in radius and curvature of the curved surface) is obtained, and this information can be applied differently for each surface in subsequent distortion calculations.

[0156] Next, the multi-surface and irregular structure corresponding part (750) can calculate the viewer's line of sight relationship for each surface. For each surface, the line of sight relationship between the viewer's eye position and each light-emitting point on the corresponding surface can be calculated individually. At this time, even for the same viewer, the angle of sight incidence and distance relationship differ depending on the direction and curvature of the surface.

[0157] Next, the multi-surface and amorphous structure corresponding part (750) can generate a surface-only distortion pattern. Based on the calculation result of a surface-only viewer line of sight relationship, a distorted texture or image pattern based on a surface-only coordinate system valid only on that surface can be generated.

[0158] In the second stage, integrated correction based on the viewer's perspective can be performed. The multi-surface and irregular structure corresponding unit (750) can integrate the distortion patterns generated for each surface into a single scene based on the viewer's perspective.

[0159] For integrated viewer-based correction, viewer-based reprojection of surface-specific distortion results can be performed. The distortion patterns generated on each surface are converted back to the viewer-based coordinate system, and the actual shape visible from the viewer's line of sight can be virtually reconstructed. Additionally, depth continuity matching between surfaces can be performed for integrated viewer-based correction. Even if distortion results belong to different surfaces, objects that should be at the same depth from the viewer's perspective are adjusted to be perceived as having the same depth, allowing them to be recognized as a single object even when extending beyond surface boundaries. Furthermore, boundary region shape correction can be performed for integrated viewer-based correction. Distortion patterns can be fine-tuned to minimize contour breaks, size discontinuities, and tilt inconsistencies that may occur at the boundary regions where surfaces meet, from a viewer-based perspective.

[0160] In the third step, boundary area correction may be performed. The multi-surface and irregular structure corresponding part (750) may perform boundary correction to mitigate breaks and depth discontinuities that may occur at the surface boundary.

[0161] In the fourth step, heterogeneous output device mixing response can be performed. The multi-surface and amorphous structure response unit (750) can perform correction so that the same perception result appears even between surfaces having different output characteristics.

[0162] The image generation unit (760) can generate an anamorphic image in which a consistent stereoscopic scene is formed from the perspective of a single viewer by considering the position and direction of each surface through the above processing.

[0164] FIG. 8 is a conceptual diagram showing the operation of an anamorphic image simulation unit according to an embodiment of the present invention.

[0165] FIG. 8 discloses a specific method for simulating an anamorphic image in an anamorphic image simulation unit to calculate how the anamorphic image is perceived by a viewer in real space.

[0166] Referring to FIG. 8, the anamorphic image simulation unit may include a projection environment information input unit (810), a viewer retinal image calculation unit (820), and an anamorphic image evaluation unit (830).

[0167] The projection environment information input unit (810) can be implemented to receive projection environment information, which is information for reflecting the projection environment of the actual anamorphic image. The projection environment information may include information such as the resolution, brightness, viewing angle, reflection characteristics of the projection surface, ambient lighting, and shadows caused by structures of the spherical display.

[0168] The viewer retinal image calculation unit (820) can be implemented to calculate the image formed on the viewer's retina depending on whether the viewer is stationary or moving. The viewer retinal image calculation unit (820) can be implemented to continuously calculate how light from the projection surface of the spherical display enters the viewer's eye and forms on the retina, not only when the viewer is stationary but also whenever the viewer walks or changes position. The viewer retinal image calculation unit (820) can analyze the area where the anamorphic effect is maintained, the area where it breaks, and the area where the stereoscopic effect is strongest.

[0169] The viewer retinal image calculation unit (820) can receive viewer position and movement path information, viewer field of view information (direction of gaze, field of view, eye spacing, etc.), projection surface shape information (position, direction, curvature), anamorphic image data, and projection environment information (brightness, resolution, field of view, reflection characteristics, ambient lighting).

[0170] The viewer retinal image calculation unit (820) can model the projection surface emission and consider each pixel or emission unit of the projection surface as a single light source element. The viewer retinal image calculation unit (820) can model which direction each light source element emits light with what intensity and color. That is, the viewer retinal image calculation unit (820) can perform modeling of the image based on a set of light sources.

[0171] The viewer retinal image calculation unit (820) can calculate the light rays reaching the viewer's eyes. It calculates which of the viewer's left or right eyes the light emitted from each light-emitting element reaches through which path, and in this process, can reflect limitations on the viewing angle, occlusion, and shadows of structures.

[0172] Additionally, the viewer retinal image calculation unit (820) can generate separate retinal images for the left and right eyes to generate different retinal images for the left and right eyes, respectively, and reflect the difference in eye spacing and viewing angle so that a fine parallax is naturally formed. Additionally, the viewer retinal image calculation unit (820) can calculate continuous retinal images according to the viewer's movement to analyze sections where the stereoscopic effect is maintained, sections where it collapses, and transition areas.

[0173] The viewer retinal image calculation unit (820) can generate a retinal-based cognitive image and integrate the calculated left and right retinal images based on the viewer's perception standard to generate a cognitive image that will actually be seen by a person.

[0174] The anamorphic image evaluation unit (830) can be implemented to perform an evaluation of the anamorphic image. The anamorphic image evaluation unit (830) can evaluate the stereoscopic effect at a specific location, the shape error with respect to the original scene, the range of the viewer's position where it appears most natural, and the degree of collapse that occurs when the image is out of sight. The anamorphic image evaluation unit (830) can form a closed-loop structure that feeds back the evaluation results to adjust the viewer's reference position or modify the distortion pattern so that the image in which the anamorphic effect is best displayed is automatically regenerated.

[0175] More specifically, the anamorphic image evaluation unit (830) can evaluate the anamorphic image by analyzing the area that maintains a sense of depth. The area that maintains a sense of depth can be calculated by distinguishing between areas where depth perception is clear and areas that are perceived as flat, depending on the viewer's position.

[0176] Additionally, the anamorphic image evaluation unit (830) can perform an evaluation of shape consistency. The anamorphic image evaluation unit can perform a shape recognition standard comparison rather than a pixel comparison by comparing the outline of an object appearing in the retinal image with the outline of the original scene to evaluate the degree of shape distortion.

[0177] Additionally, the anamorphic image evaluation unit (830) can perform an evaluation of the degree of collapse of the non-axial structure. By evaluating at what point and in what direction the three-dimensional structure collapses when a viewer moves away from the reference position, it can distinguish between an allowable viewing range and a dangerous viewing area.

[0178] Additionally, the anamorphic image evaluation unit (830) can perform surface boundary recognition continuity evaluation. The anamorphic image evaluation unit (830) can evaluate whether an object appears broken or whether depth appears discontinuous at different projection surface boundaries.

[0180] FIG. 9 is a conceptual diagram showing a spherical display implemented through 360-degree image mapping according to an embodiment of the present invention.

[0181] Referring to FIG. 9, a 360-degree image mapped and output through a spherical display device is disclosed as an example.

[0182] Through the aforementioned mapping algorithm, a naturally mapped image can be provided to the user on a spherical display.

[0183] A spherical display according to an embodiment of the present invention can provide a continuous experience in which a story that begins on the street is completed inside by transmitting connectivity between the outside and the inside. As a detail of the exterior wall media facade, the exterior wall is composed of a pitch of approximately 2023 m² and can function as a 360° media canvas that wraps around the city sky.

[0184] The exterior media facade can serve as a digital canvas that simultaneously reflects the city's identity and the emotions of its citizens, rather than being a simple visual device. More specifically, the interior is a fully immersive theater consisting of 890㎡ of 4mm pitch ultra-high-resolution LEDs, where the ceiling and walls are connected as one, allowing the audience to experience a sense of space as if they are standing at the center of the immersive media.

[0186] The device described above may be implemented as a hardware component, a software component, and / or a combination of a hardware component and a software component. For example, the device and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0187] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or instruct the processing unit independently or collectively. Software and / or data may be embodied in any type of machine, component, physical device, computer storage medium, or device so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0188] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. In this case, the medium may continuously store a program executable by a computer, or temporarily store it for execution or download. Additionally, the medium may be various recording or storage means in the form of a single or several hardware combined, and may not be limited to a medium directly connected to a computer system but may exist distributed over a network. Examples of media may include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and media configured to store program instructions, including ROM, RAM, and flash memory. Additionally, other examples of media may include recording or storage media managed by app stores that distribute applications or sites and servers that supply or distribute various other software.

[0189] Although the embodiments have been described above with reference to limited examples and drawings, those skilled in the art can make various modifications and variations from the description above. For example, suitable results can be achieved even if the described techniques are performed in a different order than described, and / or the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0190] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

Claim 1 A user perception simulation method for providing 360-degree images comprises the step of an anamorphic image generating unit of a spherical display device generating an anamorphic image that provides a sense of depth to a user at a specific location; The anamorphic image simulation unit of the spherical display device includes the step of receiving projection environment information and calculating a retinal image according to viewer movement to simulate the anamorphic image, and the anamorphic image generation unit includes a data input unit that receives anamorphic image input data; when setting the projection space, the projection space is set based on projection space information including walls, floors, curved surfaces, stairs, and LED panels, which is a three-dimensional shape of an actual surface on which the anamorphic image is projected or displayed in the projection space; first, when defining multiple surfaces integrally as the projection space, a plurality of surfaces having different positions, directions, and curvatures, including the walls, floors, curved surfaces, stairs, and LED panels, are defined as one continuous projection space; when creating a surface unit division structure, the projection surface is divided into pixel units, LED module units, or polygon units, and each division unit is defined as an independent light-emitting unit; when assigning surface attributes for viewer-based calculation, spatial position, surface direction, curvature information, and surface attributes are included as metadata for each division unit; and when generating boundary continuity information between surfaces, adjacent to each other A projection space setting unit that defines boundary relationships between surfaces and prevents visual discontinuity based on boundary continuity information between surfaces when the anamorphic image is connected across multiple surfaces; and a viewer reference setting unit that, when setting a coordinate system with the viewer's position as the origin, sets the viewer reference to a visual reference coordinate system including eye height, field of view direction, and left-right eye spacing.A method characterized by comprising: a viewer-reference scene calculation unit that divides the projection surface, including an LED, a wall, and a structure, into a plurality of pixels or polygons, views each position of the projection surface as a single light-emitting point, and virtually tracks the line of sight entering the viewer's eye from the light-emitting point; a multi-surface and irregular structure correspondence unit that, when simultaneously generating the anamorphic image on a plurality of irregular surfaces including a wall, a floor, a tilted structural curved surface, or a spherical display at different angles, generates different distorted images for each surface by considering all positions and orientations of each surface to form a consistent stereoscopic scene from a single viewer-reference; and an image generation unit that generates the anamorphic image in which a consistent stereoscopic scene is formed from a single viewer-reference by considering all positions and orientations of each surface. Claim 2 A method according to claim 1, wherein the viewer-reference scene calculation unit performs gaze tracking for each projection surface light-emitting unit when calculating the viewer-reference scene to virtually track the gaze directed toward the viewer's eyes from a corresponding location for each light-emitting unit defined in the projection space setting unit, calculates which location in the original 3D scene the tracked gaze corresponds to when calculating the original scene correspondence and obtains color, depth, and shape information, calculates a distortion relationship so that when the center axis of the viewer and the projection surface do not coincide, the viewer perceives it as a normal three-dimensional form, and when calculating the maintenance of continuity between surfaces, adjusts the scene information calculated on different surfaces so that it is perceived as one continuous scene from the viewer's perspective. Claim 3 A method according to paragraph 2, wherein the anamorphic image simulation unit receives the projection environment information and models the direction, intensity, and color of light emitted by the light-emitting unit of the projection surface of the spherical display, and simulates the image formed on the retina of the viewer according to the viewer's stationary or moving state. Claim 4 A spherical display device that performs user perception simulation for providing 360-degree images includes an anamorphic image generating unit that generates an anamorphic image providing a sense of depth to a user at a specific location; It includes an anamorphic image simulation unit that receives projection environment information and calculates retinal images based on viewer movement to simulate the anamorphic image, and the anamorphic image generation unit includes a data input unit that receives anamorphic image input data; when setting a projection space, it is set based on projection space information including walls, floors, curved surfaces, stairs, and LED panels, which are three-dimensional shapes of actual surfaces on which the anamorphic image is projected or displayed in the projection space; first, when defining multiple surfaces integrally as the projection space, a plurality of surfaces having different positions, directions, and curvatures, including the walls, floors, curved surfaces, stairs, and LED panels, are defined as one continuous projection space; when creating a surface unit division structure, the projection surface is divided into pixel units, LED module units, or polygon units, and each division unit is defined as an independent light-emitting unit; when assigning surface attributes for viewer-based calculation, spatial position, surface direction, curvature information, and surface attributes are included as metadata for each division unit; and when generating boundary continuity information between surfaces, the boundary relationship between adjacent surfaces A projection space setting unit that defines and ensures that no visual discontinuity occurs based on boundary continuity information between surfaces when the anamorphic image is connected across multiple surfaces; a viewer reference setting unit that, when setting a coordinate system with the viewer's position as the origin, sets the viewer reference to a visual reference coordinate system including eye height, field of view direction, and left-right eye spacing; and a viewer reference scene calculation unit that divides the projection surface, including LEDs, walls, and structures, into multiple pixels or polygons, views each position of the projection surface as a single light-emitting point, and virtually tracks the line of sight entering the viewer's eyes from the light-emitting point.A spherical display device characterized by comprising: a multi-surface and irregular structure corresponding unit that generates different distorted images for each surface to form a consistent stereoscopic scene from a single viewer's perspective by considering all the positions and orientations of each surface when simultaneously generating the anamorphic image on a plurality of irregular surfaces including walls, floors, inclined structural curved surfaces, or spherical displays at different angles; and an image generating unit that generates the anamorphic image in which a consistent stereoscopic scene is formed from a single viewer's perspective by considering all the positions and orientations of each surface. Claim 5 In claim 4, the viewer-reference scene calculation unit performs gaze tracking for each projection surface light-emitting unit when calculating the viewer-reference scene to virtually track the gaze directed toward the viewer's eyes from a corresponding location for each light-emitting unit defined in the projection space setting unit, calculates which location in the original 3D scene the tracked gaze corresponds to when calculating the original scene correspondence and obtains color, depth, and shape information, calculates a distortion relationship so that when the center axis of the viewer and the projection surface do not coincide, the viewer perceives it as a normal three-dimensional form, and when calculating the maintenance of continuity between surfaces, adjusts the scene information calculated on different surfaces so that it is perceived as a single continuous scene from the viewer's perspective. Claim 6 A spherical display device according to claim 5, characterized in that the anamorphic image simulation unit receives the projection environment information and models the direction, intensity, and color of light emitted by the light-emitting unit of the projection surface of the spherical display, thereby simulating the image formed on the retina of the viewer according to the viewer's stationary or moving state.

Images