• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.560-564
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• 2007

Korea Basic Science Institute(KBSI) has three general electron microscopes including High Voltage Electron Microscope(HVEM) which is the only one in Korea. Observed images through an electron microscope are what they are tilted by each step and saved, offering the more better circumstances for observers, a reconstruction to 3D could be a essential process. In this process, a warping method decreases distortions maximumly of avoided parts of a camera's focus. All these image treatment processes and 3D reconstruction processes are based on an accompaniment of a highly efficient computer, a number of Grid Node Personal computers share this process in a short time and dispose of it. Grid Node Personal computers' purpose is to make an owner can share different each other and various computing resources efficiently and also Grid Node Personal computers is applying to solve problems like a role scheduling needed for a constructing system, a resource management, a security, a capacity measurement, a condition monitoring and so on. Grid Node Personal computers accomplish roles of a highly efficient computer that general individuals felt hard to use, moreover, a image treatment using the warping method becomes a foundation for reconstructing to more closer shape with an real object of observation. Construction of the electron microscope volume 랜더링 system based on Grid Node Personal computer through the warping process can offer more convenient and speedy experiment circumstances to observers, and makes them meet with experiment outcome that is similar to real shapes and is easy to understand.