RETRACTED: Fast 3D image reconstruction algorithm based on artificial intelligence technology

Abstract

In order to improve the 3D reconstruction capability of high-resolution fine-grained 3D images, a fast 3D image reconstruction algorithm based on artificial intelligence technology is proposed. The cross-gradient sharpening detection method is used to collect features and extract information from high-resolution fine-grained three-dimensional images, and establish an edge contour feature detection model for high-resolution fine-grained three-dimensional images. Combining the salient feature analysis method and the subspace feature analysis method to cluster and analyze the high-resolution fine-grained three-dimensional image. In the artificial intelligence environment, the saliency of the three-dimensional image is detected and analyzed, and the multi-dimensional segmentation and gray histogram of the high-resolution fine-grained three-dimensional image are reconstructed through the subspace segmentation method. According to the reconstruction results of the gray histogram, fast 3D image reconstruction and image fusion processing are performed. Finally, the accurate detection and recognition of the reconstructed image is realized. The simulation results show that this method has a good effect on 3D image reconstruction, and the time cost of image reconstruction is relatively short. It improves the recognition and feature analysis capabilities of high-resolution fine-grained 3D images, and has good application value in the reconstruction, detection and recognition of high-resolution fine-grained 3D images.

RETRACTED: Research on the application of 3D reconstruction technology in traditional handicraft design

“…9 As a computer technology for simulating biological vision system, three-dimensional reconstruction technology has a very wide range of application prospects in artificial intelligence (An W and Pan J). 10 Therefore, many countries in the world start to research very early (Emam SM et al). 11 The western countries headed by the United States firstly studied the three-dimensional reconstruction technology through the application of the medical field, while the domestic ones preferred the feature point matching and detection.…”

Construction of medical aromatherapy experimental teaching resources based on digital three-dimensional technology

“…The ORB algorithm determines the direction of the FAST feature point with the help of the method of moments, which is used to calculate the center of mass within a radius of r centered on the feature point, and the vector between the feature point and the center of mass is used as the direction of the feature point [23]. The moments are defined as: , ( , )…”

Rapid construction of indoor and outdoor three-dimensional scenes and augmented reality navigation design and application

“…Currently, mainstream indoor AR navigation is mainly based on two technologies: one is indoor positioning technology, which locates users indoors through Bluetooth positioning navigation [6] , Wi-Fi positioning navigation [7] , UWB (Ultra Wide Band) positioning navigation [8] , etc., and then combines the status information of the user's mobile phone and other devices' sensors to generate AR scenes [9,10] . The other is machine vision-based 3D reconstruction technology [11][12][13] , where cloud-based AI algorithms extract key information from the user's real-time camera image and match it with spatial modeling information to calculate and return the camera's perspective and position, thereby generating AR scenes. Both methods achieve excellent AR effects, but there are limitations in some aspects: indoor positioning technology requires the purchase, installation, and maintenance of a large number of positioning devices, which requires a substantial amount of funding, and some positioning technologies have privacy leakage issues [14,15] ; machine vision-based AR indoor navigation requires the establishment of high-precision indoor maps and the need for high-performance computing devices for scene matching [16] , resulting in higher costs.…”