387 results about "Computer graphics" patented technology

The invention discloses a general nerve drawing method and system based on an illumination function generation model, and belongs to the technical field of computer graphics, and the method comprises the steps: collecting light source information containing multi-view observation data, and collecting scene information; constructing an illumination function generation model comprising a light source coding module and a light source decoding module for converting the light source information into neural illumination representation and performing joint inference based on the neural illumination representation and scene features of the drawing points; and generating a final drawn image conforming to the real illumination distribution based on the inference result. According to the method, generalization neural drawing across light sources and scenes can be achieved, images with off-line rendering quality can be generated at the cost close to real-time calculation, the sense of reality, stability and rendering efficiency are considered, and the method has good expansibility and wide application value.

The invention relates to the field of computer graphics, reverse engineering and additive manufacturing, discloses a multi-modal fusion and physical constraint three-dimensional point cloud geometric modeling system and method, and aims at overcoming the defects that traditional three-dimensional reconstruction entity attributes are missing, key features are prone to being lost, semantic understanding does not exist, and process automation is low. The system comprises a point cloud preprocessing module, a semantic segmentation and recognition module, a mixed geometric reconstruction module, a multi-component assembly and physical constraint solution module and an entity model output module. The method comprises the following steps: denoising and sampling an original point cloud, realizing semantic and instance double segmentation through a Point Net + + network, endowing a geometry-function composite label, completing hybrid reconstruction through improved Poisson reconstruction, parameterized B-Rep fitting and standard component library matching, and outputting a multi-format engineering available model after physical constraint verification and automatic correction of a violation model. According to the method, automatic, high-fidelity and high-practicability conversion from the point cloud to the engineering-level entity model is realized, and the method is adaptive to multiple industrial application scenes.

The invention discloses a virtual space multi-person interaction synchronous control method oriented to an end-cloud collaborative architecture. The invention relates to a computer graphics and three-dimensional modeling technology, and discloses a cross-format lightweight and geometric consistency maintenance method based on a three-dimensional model. Through format-independent geometric representation and a self-adaptive lightweight strategy, efficient compression and precision maintenance of three-dimensional model cross-format conversion are realized. The method specifically comprises the following steps: performing format analysis and geometric feature extraction on an input model, and establishing a unified internal representation; adaptively selecting a multi-level LOD lightweight strategy based on the complexity of the model; the accuracy of key information is ensured through geometric feature keeping and topology consistency detection; the geometric consistency is dynamically maintained by combining error monitoring and an iterative correction mechanism; and generating a target format lightweight model and carrying out quality verification. According to the method, adaptive precision control, multi-level consistency maintenance and format irrelevant processing are combined, the model size and conversion errors are effectively reduced, and cross-platform compatibility and geometric fidelity are improved. The method can be widely applied to the fields of industrial design, game development, virtual reality and the like.

The invention discloses a dynamic rendering method and system for virtual reality, a storage medium and electronic equipment, and relates to the technical field of virtual reality, augmented reality and computer graphics. Therefore, the frequency and time sequence change of the sight focus of the user hitting the surface of the virtual object in the virtual scene are analyzed, so that the relative motion trend and observation intention of the user and the object are pre-judged, predictive and adaptive scheduling of rendering resources is realized, and optical feedback conforming to the physical law, namely, dynamic material, is triggered at the sight focus, so that the real-time performance of the user is improved. Therefore, the interaction fineness in the process of interaction between the user and the VR system is improved.

The invention belongs to the technical field of computer graphic processing, and particularly relates to a computer device for chartlet loading, which comprises a central processing unit provided with a main thread for packaging a chartlet loading request into a task object and pushing the task object into a task queue of the central processing unit; the resource loading thread is used for sequentially pulling the to-be-processed task objects from the task queue in an asynchronous processing mode and reading the mapping files in the task objects through the asynchronous I / O interface; the resource decoding thread is used for decoding the mapping file and uploading texture data obtained by decoding to the graphics processor through an asynchronous interface; a plurality of threads are created in the graphics processor and at least comprise a resource processing thread used for receiving texture data uploaded by a resource decoding thread; and the rendering thread is used for carrying out texture binding on the texture data and carrying out rendering according to an instruction of the main thread after binding so as to draw and generate a corresponding map.

The invention discloses a practical training platform three-dimensional scene mass data loading optimization method, and relates to the technical field of computer graphics and three-dimensional visualization. Passive response of data loading is converted into active pre-judgment through an orbit prediction model and prospective visible area calculation, and the real-time performance of data loading is improved. The rendering lag caused by the rapid change of the satellite track is obviously reduced; the combination of the predicted position and the camera vision cone ensures that the point location is scheduled before the vision field is switched; secondly, GPU resource utilization is optimized through dynamic attribute increment updating and a dirty marking mechanism; static and dynamic attribute buffer areas are separated, only change data are updated, the CPU-GPU communication overhead is reduced, the frame rate fluctuation problem caused by batch updating is solved, and the system is still kept smooth under ten-thousand-level point location dynamic updating; in addition, the collaborative design with terrain rendering eliminates point location dislocation during terrain detail level switching through monitoring and double-buffer correction, and improves visual consistency.

The invention discloses an automatic logistics digital twinning model adaptive precision rendering method and system, and relates to the technical field of computer graphics and automatic logistics digital twinning crossing, in particular to a rendering optimization scheme capable of dynamically adjusting model rendering precision for a large-scale smart factory scene in a Unity engine. Through a dynamic decision-making mechanism based on a use scene and a service factor, in combination with a current use scene, a model with a high service priority in the scene is subjected to refined rendering, and a model with a low current weight in the scene is subjected to simple rendering, so that it is ensured that under each specific scene, the service quality of the scene is improved. And the system can intelligently and accurately guide the computing resources to the object which most needs high-fidelity rendering.

The invention discloses a hierarchical three-dimensional scene generation method and system based on spatial super-division, and belongs to the technical field of computer graphics, and the method comprises the steps: carrying out the preprocessing of a scene image, and obtaining a high-resolution object image; generating initial rough scene voxels for the scene image, and screening rough voxels and structural latent variables aligned with the high-resolution object image from the initial rough scene voxels to construct a hierarchical scene tree; inputting the high-resolution object image and the rough voxel into a voxel super-resolution model, and generating a fine voxel which keeps geometric consistency with the rough voxel; performing scale alignment and attitude registration based on the rough voxels and the fine voxels; and generating fine voxels of the sub-components recursively by taking the rough voxels of the current node as conditions based on the hierarchical scene tree, and finally assembling to generate a high-resolution three-dimensional scene. According to the method, a high-quality three-dimensional scene with high visual fidelity, fine geometric details and global structure consistency can be efficiently and automatically reconstructed from a single RGB image.

The invention provides a three-dimensional part retrieval method based on graph similarity search, relates to the field of computer graphics, and solves the technical problems that in the prior art, geometric and design semantic information of CAD cannot be fully utilized, and a topological relation is difficult to capture and display, so that the retrieval efficiency is low. The method comprises the following steps: acquiring part three-dimensional data of a computer-aided design (CAD) model, and constructing a training data set; constructing an edge-surface connection diagram based on the three-dimensional data of the part; calculating a graph editing distance (GED) matrix of all edge surface connection graphs in the training data set as a supervision signal; based on the GED matrix, training a sorting model, mapping an edge-surface connection graph to a hidden space, and constructing a part vector database according to an output graph-level embedding vector; the sorting model is constructed based on a graph attention network; and inputting a to-be-queried CAD part into the trained sorting model to obtain a feature vector, carrying out nearest neighbor search in the part vector database, and returning a similar part result.

The invention belongs to the technical field of computer vision and computer graphics, and discloses a multi-view three-dimensional reconstruction method and device based on cross-domain feature fusion and a medium, and the method comprises the steps: carrying out the cross-feature-domain coding of an initial feature token generated by a multi-view image, according to the coding, characteristics are decomposed into low-frequency components and high-frequency components through dual-tree complex wavelet transform, amplitude modulation is carried out on the high-frequency components to enhance details, and space-frequency fusion characteristics are generated; variance embedding weighted combination is carried out on the multi-view space-frequency fusion features, the combination generates a weight by calculating the variance of each feature token, adaptive weighted clustering is carried out based on the weight, and fused multi-view features are generated; and performing three-source attention decoding on the fused features, and performing cross-domain attention calculation and up-sampling by taking static embedding as query, taking the space-frequency fused features as keys and taking the fused multi-view features as values, thereby finally generating a three-dimensional voxel reconstruction result of the target object.

The invention relates to the technical field of computer graphics, and particularly discloses a three-dimensional intelligent visualization method and device for multi-source data loading, a medium and equipment.The method comprises the steps that an oblique photography model is loaded and dynamically adjusted, and an oblique photography live-action base is constructed; generating semantic 3D tiles data on the basis of the base; identifying a key entity object, carrying out lightweight processing on a high-precision GLB / GLTF model of the key entity object, and dynamically implanting the high-precision GLB / GLTF model into a scene; performing dynamic analysis and spatial superposition on the KML data associated with the key object, and constructing a multi-level three-dimensional scene information system from entity annotation to macroscopic annotation; dynamically coupling the KML elements with terrain elevation data to form a high-precision digital elevation base supporting visualization; based on a video memory dynamic partitioning mechanism, optimized resource scheduling is performed on a substrate, and adaptive balance of terrain complexity and system load is realized. According to the invention, the precision and efficiency of multi-source heterogeneous data fusion and the system stability can be improved.

The invention discloses a steel structure three-dimensional reconstruction method based on Gaussian splashing, and belongs to the technical field of three-dimensional computer vision and computer graphics, and the method comprises the steps: obtaining a multi-view image of a steel structure scene, and generating a view alignment image sequence and an image quality mask; generating a visibility weight in combination with the appearance stability score and the occlusion estimation; linear, planar and circular geometric features in the image are recognized, spatial registration is carried out on the geometric features and the visibility weight, and registration structure guiding features are generated; initializing a three-dimensional Gaussian set and projecting the structural features to Gaussian parameters to generate structural correlation parameters; the weighted reprojection error and the structural constraint error are fused to form a joint error index, and splitting, merging and optimization of a Gaussian model are guided; and through boundary consistency evaluation and sharpening processing, a steel structure three-dimensional reconstruction model is generated. By fusing the prior features of the geometric structure in the two-dimensional image and the optimization process of the three-dimensional Gaussian model, the structural accuracy and boundary definition of the reconstructed model can be improved.

The invention provides a neural radiation field compression rendering method based on decomposition expression, and relates to the technical field of computer graphics, and the method comprises the steps: inputting a multi-view image and camera internal and external parameters, carrying out the ray sampling, generating a space sampling point, carrying out the mixed feature coding of the space sampling point, and obtaining a multi-view image; obtaining three-dimensional voxel features, aligned and fused three-plane features and position codes, and splicing the three features to form fused features; inputting the fusion features into a factorization neural BRDF rendering network to predict volume density, geometric latent features, material parameters and reflection features, and improving the view angle color under the compression condition through a BRDF modulator; a ray weight is predicted through a plane-ray combined modeling module, and a compressed neural radiation field model is obtained through combined optimization of miniaturized body rendering, weighted reconstruction loss and compression constraint and is used for target view angle image rendering; according to the method, the storage overhead of the neural radiation field model is reduced, and meanwhile, the synthesis quality and rendering consistency of the new view angle under different compression ratios are improved.

The invention belongs to the technical field of crossing of computer graphics and physical simulation, and discloses a furniture material dynamic rendering system based on physical simulation. Comprising a furniture modeling module used for constructing initial scene data of furniture to be analyzed; the physical simulation module is used for constructing a structure physical simulation model of the to-be-analyzed furniture based on the initial scene data and executing simulation to obtain structure response data of each structure position of the to-be-analyzed furniture; the multi-field generation module is used for mapping the structure response data into a three-dimensional geometric model of furniture to be analyzed to form a surface risk field, generating a joint priority field in combination with scene visibility data, and determining a grid reconstruction weight field based on the structure response data and the surface risk field; the texture generation module is used for acquiring physical driving texture data; and the rendering and feedback module is used for carrying out material coloring strategy distribution and outputting a current frame of furniture material dynamic rendering image so as to realize optimal distribution of rendering quality.

The invention relates to the technical field of computer graphics, in particular to a virtual-real fusion method and system based on Gaussian splash live-action reconstruction, and the method comprises the following steps: S1, carrying out the motion recovery structure processing of an obtained target scene image sequence, and generating a sparse point cloud of a target scene; s2, training the sparse point cloud through a Gaussian splashing technology, generating a live-action three-dimensional Gaussian model, carrying out lightweight processing on the live-action three-dimensional Gaussian model, and outputting a lightweight live-action model; and S3, acquiring an internal parameter matrix, an external parameter matrix and a real-time video stream of the physical camera. According to the method, the spatial mapping relation between the live-action reconstruction model and the artificial fine model is established, the user interaction instruction is responded, and the explicit and implicit states of different detail level models in a unified scene are dynamically controlled, so that smooth switching without context loss from macroscopic to microscopic is realized; the problems of visual angle jump and spatial cognition interruption caused by system switching in a traditional scheme are solved.

The invention discloses an immersion type 3D scene intelligent optimization generation system and method based on AIGC, and particularly relates to the crossing field of computer graphics and artificial intelligence technologies. The system comprises a scene analysis and semantic modeling module, a style control module, a semantic interactive editing module, an immersive feedback acquisition module and an intelligent optimization loop module. According to the core method, a scene semantic map is constructed by analyzing user input, and scene visual consistency is guaranteed by using a global style control vector; realizing incremental updating driven by a local instruction through a semantic graph interface; and scene automatic iterative optimization is driven by fusing user behavior data and dominant feedback. According to the method and the system, the full-process intelligentization from generation, editing to optimization is realized, and the efficiency, the consistency and the user intention fitting degree of 3D scene creation are improved.

The invention discloses a strip mine slope weak plane dynamic modeling system based on real-time working condition feedback, and belongs to the technical field of geographic model 3D dynamic modeling of computer graphics. Comprising a data acquisition module, a data preprocessing module, a modeling and updating module, a working condition feedback calculation module and a working condition feedback adjustment module which are connected in sequence, the method comprises the following steps: calculating an overlapping region and an adjacent overlapping region of a working condition operation influence region and a strip mine slope three-dimensional model, and intensity data of coordinate points of a three-dimensional weak surface under the influence of industrial and mining operation, and labeling and dynamically updating to generate inspection information of the overlapping region and the adjacent overlapping region; meanwhile, the three-dimensional model of the strip mine slope with more accurate dangerous area form is reconstructed and updated, the accuracy and timeliness of weak plane stability analysis and early warning are improved, and the problems that in the prior art, serious defects exist in the aspect of associating real-time mining working conditions, weak plane stability analysis lags behind, accuracy is low, and early warning accuracy and timeliness are low are solved.

The invention relates to the technical field of computer graphics and human-computer interaction, in particular to an immersive literature interaction system based on WebGL and 3DGS, which comprises a scene reconstruction and data processing module based on 3DGS, a 3DGS real-time rendering engine based on WebGL and an interaction narration module fused with a 3DGS scene. The 3D GS-based scene reconstruction and data processing module is used for reconstructing a high-precision 3D scene from multi-source data and executing lightweight optimization; the WebGL-based 3DGS real-time rendering engine is used for loading and rendering a 3D Gaussian splash model at a browser end, supporting dynamic illumination, texture and viewpoint switching and realizing low-delay interaction; and the interactive narrative module fusing the 3DGS scene associates literature content through AI driving logic, triggers scene visualization response and integrates a role dialogue system to realize immersive narrative experience. The module realizes seamless fusion of literature interaction logic and a 3DGS scene.

The invention discloses a global neural drawing method and system oriented to hybrid representation optimization, and belongs to the technical field of computer graphics, and the method comprises the steps: dividing a screen into a plurality of tiles, and obtaining a first workload index on each tile in a first drawing stage and a second workload index on each tile in a second drawing stage; generating a cross-tile and cross-stage unified scheduling queue based on the first workload index and the second workload index, and executing the drawing tasks on different tiles in parallel according to the unified scheduling queue; and triggering a subsequent feature fusion and neural global illumination drawing stage when the inter-stage dependency condition is met so as to generate an output image with a global illumination effect. According to the method, the end-to-end frame rate oriented to the modern AI accelerator / AI-GPU can be remarkably improved and the tail delay can be reduced on the premise of ensuring the visual quality and the time sequence stability, and the method is suitable for application scenes such as real-time global illumination, large-scale complex scene drawing and interactive neural rendering.

The invention relates to the technical field of computer graphics, sensor simulation and real-time rendering, in particular to a panoramic laser radar simulation method and system based on a single GPU calculation shader, and the method comprises the steps: receiving simulation parameters of a laser radar sensor, assembling the simulation parameters into a constant buffer area object, and carrying out the simulation of the laser radar sensor on the constant buffer area object; the method comprises the following steps: allocating a structured point cloud buffer area and binding shader resources in a rendering dependency graph framework, scheduling and calculating a shader to generate a two-dimensional thread index, calculating a light beam direction vector corresponding to each thread and constructing a ray descriptor based on the two-dimensional thread index, and obtaining hit information; the method comprises the steps of calculating echo intensity based on hit information according to a preset intensity model, simulating noise, writing point cloud attributes into a structured point cloud buffer area, and asynchronously looking back point cloud data for consumption through the structured point cloud buffer area. And the throughput and the data consistency are improved.

The invention relates to the field of computer graphics and real-time rendering, and discloses a naked eye VR visual angle continuous roaming real-time tracking system, which comprises a multi-source viewpoint acquisition unit, a rendering feedback prediction unit connected with a depth buffer area and a template buffer area, and a viewport consistency arbitration unit. According to the method, motion vectors are purified according to object attributes of a template buffer area, a viewpoint is reversely deduced by means of data hierarchical solution of a depth buffer area, and a viewport consistency arbitration unit compulsively uses the reversely deduced viewpoint to take over rendering when the deviation of external sensing data exceeds a limit. The image visual residual inertia is used for filling the blank of external sensor data, and rendering collapse caused by sensor signal interruption or asynchronization is avoided.

The invention provides a Gaussian neural field dynamic scene reconstruction system based on depth consistency constraint, and relates to the technical field of computer graphics, and the system comprises an estimation module which generates a target frame initial depth map; the calculation module reconstructs the point cloud and obtains a point cloud normal direction and a pixel normal direction; the optimization module is used for iteratively correcting the initial depth based on the two types of normal consistency to obtain an optimized depth map; the alignment module is used for determining a scale parameter through regression by taking the first target frame as a reference, and carrying out scale transformation on the depths of other frames to form a consistent depth sequence; the reconstruction module is used for constructing or training a Gaussian neural field based on the sequence and outputting a three-dimensional representation; in addition, the calculation module can contain multi-dimensional wavelets and sparse reconstruction and is used for multi-scale noise suppression and direction weighted fitting. Reference frame selection is based on frame-level quality, geometry and scale stability indexes; according to the system, the intra-frame geometric credibility and the cross-frame scale consistency are improved, ghosting and tearing are reduced, and the stability and integrity of dynamic scene reconstruction are enhanced.

The invention relates to the technical field of computer graphics and image compression, in particular to a multi-moment illumination chartlet compression and decompression method based on two-dimensional Gaussian representation and a computer device.The method comprises the steps that S1, illumination chartlets at multiple target moments are obtained and preprocessed; s2, constructing a shared two-dimensional Gaussian basis set based on the low-frequency component; s3, extracting a residual error at a multi-target moment and features of a highlight and high-frequency region; s4, multi-layer perceptron network construction and two-dimensional Gaussian attribute offset modeling are carried out; s5, performing compression and storage; and S6, decompressing and rendering. The compression rate is greatly improved, the decompression speed is extremely high, the real-time rendering requirement is met, the rendering quality is higher than that of a traditional compression method, the highlight and high-frequency detail modeling capacity is high, the structure is simple, and integration is easy.

The invention relates to the technical field of computer graphic processing, and discloses a method for automatically drawing a DCS (Distributed Control System) picture into a real-time database picture, which comprises the following steps of: firstly, identifying a DCS source file format, directly analyzing a public text format or intercepting a bottom layer rendering instruction for a private binary format, and extracting standardized discrete data; constructing an intermediate vector model, and performing coordinate normalization and curve smoothing processing on the static primitives by using an affine transformation matrix; meanwhile, syntactic analysis is conducted on the control script to construct an abstract syntax tree, and dynamic logic is converted; then recombining a composite object based on spatial semantics, and repairing pipeline topology connection by utilizing automatic adsorption and an orthogonal routing algorithm; and finally, calling a target system interface to complete object instantiation and persistent storage. According to the invention, the automatic high-fidelity migration of the DCS picture to the real-time database is realized, the labor cost is reduced, and the consistency and accuracy of the monitoring picture are ensured.

The invention provides a camera and illumination combined controllable 4D video generation method, device and equipment, relates to the technical field of computer vision and computer graphics, and aims to solve the problem that an existing model cannot perform combined control on a camera track and an illumination condition at the same time. The method comprises the steps that a dynamic point cloud and a sparse relighting point cloud are generated based on an input video, the dynamic point cloud is used for explicitly representing geometric structure and motion information of a scene in the input video, and the sparse relighting point cloud is used for providing illumination priori of the scene under a target illumination condition; respectively processing the dynamic point cloud and the sparse relighting point cloud according to the target camera track to generate geometric prior information and illumination prior information aligned with the target visual angle; the geometric prior information and the illumination prior information are coded into visual tokens, and an illumination query token is extracted from the relighting key frame; and performing de-noising generation by using the visual token and the illumination query token, and outputting a target video consistent with the target camera track and the target illumination condition.

The invention discloses a text-based human body action content generation method and system, and belongs to the field of computer graphics and artificial intelligence. According to the technical scheme, the method comprises the following steps: constructing a MambaTrans mixed backbone network, and fusing the capability of a Mama model for processing long-sequence data and the capability of a Transform model for capturing a global dependency relationship; a layered adaptive feature enhancement mechanism is introduced, wherein an adaptive frame weighting module dynamically allocates frame weights and a multi-scale feature fusion module fuses different time scale features; the motion is decomposed into layered tokens through a residual vector quantization auto-encoder, a basic token is generated by using a mask Transform, and then a residual token is generated layer by layer by using MambaTrans. According to the method, higher generation quality, higher layered modeling capability and higher reasoning speed are realized, and the method is suitable for virtual reality, augmented reality, movie animation production and game role control.

This invention relates to the fields of computer vision and computer graphics, and provides a method and system for dynamic human body reconstruction from monocular video based on 3D Gaussian splashing. The method includes the following steps: data preprocessing; initialization of the normalized space 3D Gaussian; deformation of the normalized space 3D Gaussian to an intermediate pose space to obtain a non-rigidly deformable 3D Gaussian and pose-related features; transformation of the non-rigidly deformable 3D Gaussian to the observation space using linear blending skinning to obtain the observation space 3D Gaussian; decoding the viewpoint-related color based on Gaussian color features, pose-related features, and viewpoint direction; constructing a total loss function including a normal consistency regularization term to optimize the 3D Gaussian attributes and network parameters; and rendering the target human body image using a differentiable Gaussian splash rasterizer. This invention enables rapid and fully automatic reconstruction from monocular video to a high-fidelity, animable human body model, applicable to fields such as virtual reality and film production.

The application discloses a kind of virtual image model construction method and system based on image clone, it is related to computer graphics field, including: from real-time audio and video stream of real person, the multimodal data of fusion vision, voice and action are obtained;Respectively extract facial expression, voice and action emotional data;Adopt dynamic time warping algorithm to calculate the similarity between each modal emotional data, generate the modal correlation mapping matrix of quantitative modal synchronization relationship;Adopt machine learning model to construct emotional label to limb posture expression action mapping model;According to the deviation of expression and action, the feature is adjusted back;Finally, based on the feature after adjustment, mapping matrix and mapping model, generate the virtual image that expression, voice and action are accurately aligned on time axis.The application establishes the quantitative correlation and feedback adjustment mechanism between modal, significantly improves the real sense and coordination of virtual image when cloning real person in multidimensional emotional expression.

This invention discloses a method, device, medium, and system for generating and using 3D character culling data in computer graphics, belonging to the field of computer graphics. The method includes the following steps: pre-generating frame-level cluster bounding box data corresponding to sampled animation frames; submitting the frame-level cluster bounding box data to the graphics processing unit of the graphics card during initialization; updating the current animation frame using an animation state machine during runtime; during the culling operation, searching for the bounding box data of the cluster in the current animation frame based on the current animation frame and the cluster index, and culling it; if the current animation frame does not match the sampled animation frame, interpolating and calculating the bounding box data corresponding to the current animation frame based on the pre-generated frame-level cluster bounding box data of the animation frames before and after the current animation frame. This invention has advantages such as low overhead, good dynamics, and high culling performance.

An image data generation device includes a target object acquisition unit configured to acquire a learning target object created as computer graphics (CG), a virtual space generation unit configured to generate a virtual space in which the learning target object is disposed, a background setting unit configured to set a background image captured in a physical space as a background in the virtual space, and an image data generation unit configured to generate image data by using a captured image obtained by imaging the learning target object disposed in the virtual space.