WiMi Hologram Cloud a leading global Hologram Augmented Reality (“AR”) Technology provider announced that a multi-objective 3D modeling and reconstruction system has been developed based on artificial intelligence techniques. The system is able to be trained on large-scale datasets through deep learning algorithms and other advanced techniques, and optimization algorithms are used to improve the accuracy and generalization ability of the network. It also employs a variety of preprocessing and reconstruction algorithms to enable efficient and accurate 3D modeling and reconstruction. The system is characterized by high scalability, ease of use and multifunctionality, and users can select the appropriate functions according to their needs and use them in combination.
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The core module of the system includes point cloud data acquisition, data preprocessing, feature point extraction, and mesh reconstruction. First of all, the fine information of the object surface is captured through various point cloud data acquisition methods, which provides the basis for the later data preprocessing. Point cloud data acquisition is a necessary step for 3D image processing. Then the collected data will be preprocessed, and multiple data preprocessing techniques, such as denoising, smoothing, segmentation, etc., will be utilized to effectively reduce the noise and interference in the point cloud data and highlight the feature information of the object. After this, a convolutional neural network (CNN) will be built to automatically learn the feature information of the point cloud data and extract the most valuable features from it, feature point extraction is a key part of 3D modeling. Finally, mesh reconstruction is performed, which is the key part of converting the point cloud data into a triangular mesh model, using algorithms to convert the point cloud data into a triangular mesh model with surface smoothing and patching to achieve efficient and accurate 3D modeling.
Multi-objective 3D modeling and reconstruction system is a 3D modeling system using advanced algorithms and tools, which has the advantages of multi-objective optimization, automatic reconstruction, intelligent interaction, and high-precision modeling, etc. It can simultaneously consider multiple objective functions such as geometric accuracy, topology, number of surfaces, etc., and generate more compliant 3D models by optimizing these objective functions, and automatically carry out the operations of denoising, smoothing, filling holes, etc., according to the users’ needs. The system also automatically performs operations such as denoising, smoothing and filling holes in the 3D model according to the user’s requirements, which improves the quality and usability of the model. In addition, the system adopts artificial intelligence technology, which can realize intelligent interaction with the user through voice recognition, gesture recognition and other ways, improving the convenience and efficiency of operation.
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WiMi’s multi-target 3D modeling and reconstruction system also supports a variety of functions such as 3D visualization, object recognition, and 3D reconstruction. These functions allow users to process and analyze 3D images more conveniently. For example, in the field of 3D visualization, it can display 3D models through virtual reality technology to achieve a more realistic 3D experience. In the field of object recognition, it can recognize and classify objects in 3D models, thus realizing automated object detection. In the field of 3D reconstruction, it can merge multiple point cloud data sets into a complete 3D model. The system promotes the development and innovation of artificial intelligence technology in the field of 3D image processing, and also brings new opportunities and challenges to many industries.
Multi-target 3D modeling and reconstruction system has a wide range of application prospects, with the development of intelligent technology, the future multi-target 3D modeling and reconstruction system will be more intelligent, and can automatically complete the 3D modeling and reconstruction tasks according to the user’s needs, and improve the work efficiency and quality. Multi-modal input is an important trend in the development of future multi-target 3D modeling and reconstruction system. Users can collect data in multiple ways to generate more realistic and accurate 3D models. In addition, the application of virtual reality and augmented reality technology is also a major trend in the future of multi-target 3D modeling and reconstruction systems. Users can perform 3D modeling, visualization editing and interactive operation in a virtual environment, which improves the user experience and ease of operation.
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