WiMi Developed DCNN AI Technology Based on N-dimensional Manifold Holographic Technology
WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced the development of a method for creating realistic 3D holographic digital content using deep convolutional neural networks (DCNN) based on N-Dimensional Manifold algorithmic holographic technology. This advancement addresses the significant data processing challenges previously faced in holographic content creation, which typically required high computational power and advanced systems. WiMi's AI-driven model allows for streamlined production of holographic content on standard computing devices. The new system reduces the reliance on expensive hardware by employing intelligent algorithms to minimize data volume, potentially revolutionizing video production and social interaction experiences.
- Development of DCNN AI technology can streamline the creation of 3D holographic content.
- Reduced reliance on expensive computational power may make holographic content more accessible.
- Potential to revolutionize the video production and social interaction experience.
- Technology is still in development and has not been publicly tested yet.
BEIJING, April 19, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that its R&D team had developed a method for creating realistic 3D holographic digital content using deep convolutional neural network AI models based on N-Dimensional Manifold algorithmic holographic technology.
The main difficulty and challenge in producing holographic digital content is the amount of data in holographic digital content. Each holographic digital content contains a large amount of data. These data include a full range of 360-degree digital information such as depth of field and dimension of the holographic digital content. The production of holographic digital content requires a large amount of computing power. Previously, the industry usually used distributed algorithms for computational processing, which required many advanced computers. Therefore, the first holographic digital content was done in-house or in professional holographic digital content research labs, and its natural production is rather costly. The high cost of holographic content and display made it unavailable for ordinary people. However, with the development of AI technology, researchers at the WiMi R&D Center were able to develop DCNN AI technology for solving problems based on N-dimensional manifold holographic technology. This AI-driven model is the best way to generate holographic content from a series of input images.
Traditional holographic content production methods create many holographic blocks and then use specific algorithmic models to synthesize these holographic blocks into a complete hologram, similar to a photo that is not large enough to be stitched together with multiple images. Therefore, each time the production of holographic digital content requires a lot of time and effort, and the requirements for computer graphics processing capabilities are incredibly high. WiMi's technology is different from traditional holographic digital content processing. It uses DCNN AI technology to intelligently discriminate images and identify N-dimensional information, such as objects, depth of field, phase, etc., in digital photos, and then process 3D holographic images pixel-wise and with high precision through complementary difference algorithm control. DCNN AI can replace computer peripherals such as manual or multi-camera LIDAR sensors, significantly reducing image blocks that need to be processed. It can analyze images and categorize them into groups by CNN, considerably reducing the reliance on computer image processing power. In this case, holographic digital content can be processed and generated using ordinary computers or mobile devices like cell phones and tablets. Combined with WiMi's holographic digital content compression processing system, the intelligent algorithm removes coding redundancy, temporal redundancy, spatial redundancy, and irrelevant information desensitization to compress the data volume of holographic content and achieve a lightweight layout of holographic digital content, which is more conducive to the dissemination of holographic content.
WiMi is training this AI model and has yet to test it publicly. This will likely be a disruptive technology application. As this technology further matures, it is likely to revolutionize how people watch and produce video, as well as the experience of social interaction.
About WIMI Hologram Cloud
WIMI Hologram Cloud, Inc. (NASDAQ: WIMI) is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.
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SOURCE WiMi Hologram Cloud Inc.
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