WiMi Develops a 3D Object Recognition System Based on Multi-View Feature Fusion

Rhea-AI Summary

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) announced a new 3D object recognition system utilizing multi-view feature fusion. This innovative system employs convolutional neural networks to analyze various viewpoints of 3D objects, optimizing feature extraction and global classification. Key components include:

• Viewpoint Information Selection: Projects 3D objects from multiple angles for improved training data.
• Feature Extraction: Uses CNN to create mapping matrices for generalizing viewpoint relationships.
• Feature Fusion: Combines features through multilayer clustering to enhance explanatory power.

3D object recognition is pivotal for computer vision advancements. WiMi plans to expand the application of this technology across various sectors.

Positive

• Launch of a cutting-edge 3D object recognition system enhances company's technology portfolio.
• Utilizes advanced multi-view feature fusion, positioning WiMi as a leader in AR technology.

Negative

• None.

BEIJING, April 13, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of a 3D object recognition system based on multi-view feature fusion. The system uses convolutional neural networks to analyze different viewpoints of 3D objects and fuse features from multiple views to infer global information about 3D objects, which is fed into a fully connected network for classification and inferring labels of 3D objects from multiple views.

WiMi's 3D object recognition system based on multi-view feature fusion consists of three main parts: viewpoint information selection, feature extraction, and feature fusion.

The viewpoint information module can project 3D objects into the 2D plane from multiple perspectives. Different viewpoints involve different object orientations and structural information. A graph structure can be built between multiple views and clustered into groups based on spatial distribution. A reasonable viewpoint information selection strategy can optimize the training data of the network.

The feature extraction module is to extract features using convolutional neural networks. After the convolutional layer, the feature mapping module can act on the view feature response map. Multiple mapping matrices are learned using a multilayer perception machine, and multiple matrices map the corresponding views onto an approximate feature space. The mapping matrices can generalize the viewpoint transformation relationships between views and map the feature map to a group-level feature that describes the region.

The feature fusion module focuses on fusing multiple features with a reasonable and effective strategy to achieve multilayer fusion based on clustering. The convolution operation weighs the high-dimensional view features and encodes the weight information between different views. CNN deals with feature response maps with spatial data. Features are extracted from the convolutional layer of CNN after using maximum value pooling to obtain the maximum response on the feature map. The system learns the correlation between adjacent views to generate global features with more explanatory power and fuse them into feature maps.

After all view features are fused into global features, the system inputs the global features into the fully connected layer, mines the high-dimensional features in the fused features with spatial information, and completes the classification and output results.

3D object recognition technology is one of the core technologies of computer vision and the critical technology for 3D scene understanding. WiMi will continue to expand the application of its multi-view feature fusion-based 3D object recognition algorithm based.

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.

Safe Harbor Statements

This press release contains "forward-looking statements" within the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates," and similar statements. Statements that are not historical facts, including statements about the Company's beliefs and expectations, are forward-looking statements. Among other things, the business outlook and quotations from management in this press release and the Company's strategic and operational plans contain forward−looking statements. The Company may also make written or oral forward−looking statements in its periodic reports to the US Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K, in its annual report to shareholders, in press releases, and other written materials, and in oral statements made by its officers, directors or employees to third parties. Forward-looking statements involve inherent risks and uncertainties. Several factors could cause actual results to differ materially from those contained in any forward−looking statement, including but not limited to the following: the Company's goals and strategies; the Company's future business development, financial condition, and results of operations; the expected growth of the AR holographic industry; and the Company's expectations regarding demand for and market acceptance of its products and services.

Further information regarding these and other risks is included in the Company's annual report on Form 20-F and the current report on Form 6-K and other documents filed with the SEC. All information provided in this press release is as of the date of this press release. The Company does not undertake any obligation to update any forward-looking statement, except as required under applicable laws.

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SOURCE WiMi Hologram Cloud Inc.

FAQ

What is the recent development by WiMi Hologram Cloud (WIMI)?

WiMi Hologram Cloud announced the development of a 3D object recognition system based on multi-view feature fusion.

What technology does the new 3D object recognition system use?

The system uses convolutional neural networks to analyze multiple viewpoints of 3D objects.

What are the key components of WiMi's 3D object recognition system?

The system consists of viewpoint information selection, feature extraction, and feature fusion.

How will WiMi Hologram Cloud (WIMI) utilize the new technology?

WiMi plans to expand the application of its multi-view feature fusion-based 3D object recognition algorithm across various sectors.

When was the 3D object recognition system announced by WiMi?

The system was announced on April 13, 2023.