KEYWORDS: 3D modeling, Optical properties, Optical surfaces, RGB color model, Light sources and illumination, Neural networks, Visual process modeling, Reflection
This work presents a workflow to automatically calculate optimized scanning trajectories for industrial robot system using the estimation of a surface reflectance model of 3-D shape and parameters from multiple views. To solve the problem of determining the views without Lambert's surface, a 3-D reconstruction algorithm based on a convolutional neural network is proposed. In the first step, the encoder is trained for the descriptor description of the input image. In the second step, a fully connected neural network is added to the encoder for regression for choosing the best views. The coder is trained using the generative adversarial methodology to construct a descriptor description that stores spatial information and information about the optical properties of surfaces in different areas of the image. The codec network is trained to recover the defect map (depends directly on the sensor and scene properties) from RGB image. As a result, this method uses nonLambertian properties, and it can compensate for triangulation reconstruction errors caused by view-dependent reflections. Experimental results on both synthetic and real objects show that the proposed method automatically finds trajectories that enable 3-D reconstructions, with a significant reduction of scanning time.
An image haze removal algorithm based on multiscale block-rooting processing has been developed for removing haze/fog from an image based on frequency-domain coefficient correction of a set of images followed by their fusion based on the Laplacian pyramid. A new stage is proposed in obtaining a local-global estimate of high-contrast images, which are also used in the general fusion model. The proposed block-based multiscale enhancement method base on 3-D block-rooting multiscale transform domain technique, comprising: finding similar blocks in the image by block-matching; block-grouping for different block sizes; applying 3-D block-matching parametric image enhancement; calculating the quality measure of enhancement; optimizing parameters of image enhancement method through the quality measure of enhancement; fusing different enhanced images. To test the performance of the proposed algorithm, the public database O-HAZE is used.
Currently, VR and AR headsets are becoming widespread. In addition to entertainment purposes, these technologies are increasingly being used in education, science, medicine, and engineering. The remote maintenance monitoring technologies make it possible to significantly expand the possibilities of using services for remote maintenance and repair complex technical systems by highly qualified specialists. However, the problems of implementing such systems in a wide range of tasks are complicated by the presence of a wide variety of solutions of this kind and the high price of such models. In this paper, we investigate a new smartphone-based augmented reality device for industrial tasks. The article describes augmented reality glasses based on a mobile phone (system "DAR"), which combines the functions of VR and AR technologies and a low cost of the final product. The proposed solution combines a helmet with a smartphone, which transmits information about the surrounding space and connects the augmented reality elements built on this image. Information about the surrounding space comes to the smartphone screen from stereo cameras equipped with autofocus. Images captured in such a system suffer from low contrast and faint color. We present a new image enhancement algorithm based on multi-scale block-rooting processing. This solution makes it possible to expand AR technology scope for remote maintenance of complex technical systems by highly qualified specialists at remote sites since using a smartphone and a DAR headset will be sufficient. Some experimental results are presented to illustrate the performance of the proposed algorithm on the real and synthesized image datasets.
Currently, VR and AR headsets are becoming widespread. Such technologies make it possible to significantly expand the possibilities of using services for remote maintenance and repair complex technical systems by highly qualified specialists. During the COVID-19 pandemic, the need for service representatives of manufacturing enterprises from foreign countries using such funds has increased significantly. Restrictive measures on movement between states limit the possibility of interaction between manufacturers' representatives (without losing the quality of work performed), so AR technology has become virtually uncontested. The article describes augmented reality glasses based on a mobile phone (system "DAR"), which combines the functions of VR and AR technologies and a low cost of the final product. The proposed solution combines a helmet with a smartphone, which is used to transmit information about the surrounding space and connect the augmented reality elements built on this image. Information about the surrounding space comes to the smartphone screen from stereo cameras equipped with autofocus. It allows the user to transmit the picture with a minimum delay and high quality. The low cost of the final device is ensured by stereo cameras, a module with sensors, and housing for attaching to the user's head. Processing of information about movement, sound transmission, and superposition of augmented reality elements is done using a smartphone. This solution makes it possible to expand AR technology scope for remote maintenance of complex technical systems by highly qualified specialists at remote sites since using a smartphone, and a DAR headset will be sufficient. The device's proposed technical solutions allow providing a high IP class, which is necessary for industrial use.
The COVID-19 pandemic has unexpectedly transformed the access and the organization of repair services for industrial equipment. Operation or maintenance and a breakdown of industrial equipment require interaction with the specialists of the equipment manufacturer. The personal presence of a specialist repairman at an industrial facility leads to high financial costs, which consist of losses from prolonged downtime of equipment and production in general and transportation costs. A way out in such situations can be remote work of enterprise engineers and an expert of an equipment supplier, organized using a remote assistant's hardware and software complex. The article compares AR systems by numerous parameters in the following groups: software functionality, technical features for software operation, data security, compatibility requirements. This analysis will allow potential users of such systems to determine the optimal implementation approach in production based on the required parameters. The correct choice of such systems will ensure that employees can work safely and efficiently in production, reduce the risk of incorrect work and reduce production downtime.
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