BEIJING, Aug. 16, 2023 /PRNewswire/ — WiMi Hologram Cloud Inc. (NASDAQ: WIMI) (“WiMi” or the “Company”), a leading global Hologram Augmented Reality (“AR”) Technology provider, today announced that a 3D human behavior recognition algorithm system based on convolutional neural network (CNN), which has the good representational ability, was developed.
Human Behavior Recognition (HBR) is the process of deciphering human behaviors through sophisticated techniques in order to enable machines to understand, analyze, comprehend, and classify these behaviors and give any kind of valid input or stimulus. Deep learning is very effective in solving recognition and classification problems as it performs end-to-end optimization and related tasks can benefit each other (transfer learning).
First, four unique spatio-temporal feature vectors are extracted from the relative motion of the skeletal joints, which are subsequently encoded into images that are then fed into a CNN for deep feature extraction. More specifically, the system is using data for a 3D human behavior recognition task by extracting four types of informative features (distance, distance velocity, angle, and angle velocity features) from the 3D skeleton data and encoding them into an image using a suitable encoding scheme. Additionally, WiMi uses inverse ion optimization to remove redundant and misleading information from the feature space. Finally, WiMi uses classification for the final prediction of operations.
The application process of the system mainly includes data collection, data pre-processing, feature extraction, classification, and prediction decision-making.
The first step is to collect appropriate data for the CNN-based 3D HBR system. An appropriate, structured and correctly labeled dataset is one of the most essential requirements for training the model. The neural network will use the dataset as an example to learn its corresponding feature information, save the memory of the deep neural network training, and use this memory as a basis for predicting other corresponding datasets. Therefore, the quality of the dataset will directly affect the quality of neural network training. A neural network trained on a dataset with wide coverage, full information and high resolution is far better than a network trained on a simple, low-resolution dataset with complex background. The requirements of human behavior recognition networks for the dataset include comprehensive behavioral categories, high-quality of behavior, clear video and so on. The second step is data pre-processing, where feature transformation, feature selection and feature extraction are coupled together, usually called data pre-processing modules. Feature extraction and correct representation are key steps to improve model performance. For high dimensional data, there is a relative increase in the likelihood of model overfitting, and therefore the selection of relevant features is required. Selecting the required features for the classification model is a critical step in getting it right. The next step is to classify, where the extracted features are used to train the model for the task of recognizing and classifying different forms of human behavior. Finally, there is predictive analytics, where more informative features are extracted from the inputs of the convolutional neural network model so that the model can make decisions without considering the visual differences between categories.
WiMi’s 3D HBR algorithm system based on CNN technology can achieve high-precision behavioral identification of individuals and groups, set abnormal behavior prediction and timely warning, which can be widely used in personnel identification, vehicle identification, regional intrusion, target anomaly detection and other application scenarios.
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.
