https://mgv.sggw.edu.pl/issue/feed Machine Graphics & Vision 2026-02-16T20:35:57+00:00 Editorial Office mgv@sggw.edu.pl Open Journal Systems <p><strong><em>Machine GRAPHICS &amp; VISION</em></strong> is a refereed international journal, published quarterly by the <a href="https://iit.sggw.edu.pl/?lang=en" target="_blank" rel="noopener">Institute of Information Technology</a> of the <a href="https://www.sggw.edu.pl/en/" target="_blank" rel="noopener">Warsaw University of Life Sciences</a> – <a href="https://www.sggw.edu.pl/en/" target="_blank" rel="noopener">SGGW</a>, in cooperation with the <a href="https://tpo.org.pl/" target="_blank" rel="noopener">Association for Image Processing</a>, Poland – <a href="https://tpo.org.pl/" target="_blank" rel="noopener">TPO</a>.</p> <p><strong><em>MG&amp;V</em></strong> has been published since 1992.</p> <p><strong><em>Machine GRAPHICS &amp; VISION</em></strong> provides a scientific exchange forum and an authoritative source of information in the field of, in general, pictorial information exchange between computers and their environment, including applications of visual and graphical computer systems (<a href="https://czasopisma.sggw.edu.pl/index.php/mgv/about">more</a>).</p> https://mgv.sggw.edu.pl/article/view/10508 Enhancing cultural heritage digitalization through 3D graphics algorithm and immersive visual communication technology 2026-02-16T20:35:57+00:00 Fang Yuan yuanfang16316@163.com <p>With the continuous advancement of digital technology, cultural and creative product design is shifting from static presentation to dynamic immersive experience. The research aims to address the challenges faced by traditional modeling methods in accurately restoring complex textures and cross platform visual communication. The neural radiation field algorithm was enhanced by introducing a multi-level cost volume fusion module and a Gaussian uniform mixture sampling strategy. Furthermore, a collaborative visual communication framework integrating augmented reality and virtual reality was constructed, achieving a transition from single image input to high-precision 3D reconstruction, and then to dynamic interaction. The experiment showed that the improved algorithm achieved peak signal-to-noise ratios of 30.63 and 30.15 on the UoM-Culture3D and Bootstrap 3D synthetic datasets, respectively, with structural similarity indices of 0.88 and 0.89, respectively. Field deployment tests have shown that integrating AR and VR technologies into visual communication strategies significantly improves spatial perception consistency, prolongs user engagement time, and enhances detail recognition accuracy. This research emphasizes the potential of combining deeply coupled 3D graphics algorithms with immersive technology, which can help improve the digital restoration accuracy and cultural dissemination efficiency of cultural and creative products, thereby supporting the modern inheritance of traditional culture.</p> 2026-02-16T00:00:00+00:00 Copyright (c) 2026 Machine Graphics & Vision