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Accurate 3d model of venice: Preserving historical data and introducing slam imms for change detection and updating procedures 10

Accurate 3d model of venice: Preserving historical data and ...

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10th International Workshop 3d-ARCH "3d virtual reconstruction and visualization of complex architectures"

作者： Vassena, G.P.M. Fellin, A. Mainardi, A. Perfetti, L. Cavallari, L. Sgrenzaroli, M. Roggeri, S. Fassi, F. DICATAM Civil Engineering Architecture Territory Environment and Mathematics Università Degli Studi di Brescia Italy Gexcel.srl Brescia Italy Acoma Srl Monza Italy ABC Architecture Built Environment and Construction Engineering Politecnico di Milano Italy

The Municipality of Venice, through Insula srl (Insula, 2024), started the RAMSES (Rilievo Altimetrico, Modellazione Spaziale E Scansione 3d) project in 2005 with the unprecedented intention of conducting a static laser scanner survey of an entire city. The authors of this paper, who have been involved in the project on behalf of the client, including drafting general contract technical specifications, wished to revisit the survey's findings nearly two decades later. This contribution illustrates the procedures implemented to guarantee the future accessibility of the surveyed data. It is interesting to highlight how the detailed technical specifications outlined in the general technical contract section have facilitated the retrieval of the historical three-dimensional laser scanner measurements archive. Tests have been conducted to determine how the existing mobile mapping technologies may be utilised to update the three-dimensional historical data obtained in the Ramses project efficiently. Furthermore, the paper describes the surveying approach that has never been adequately described in the literature. The surveying and geo-referencing methodologies continue to have several interesting and relevant aspects, especially regarding how the topographic network has been implemented. The Ramses three-dimensional model represents an extraordinary, valuable digital archive containing portraits of the city's conditions at the time of the mapping. Ramses 3d model, when enriched with field activities conducted using more updated technologies, can provide interesting and unique evaluations of the evolution of Venice's landscape. © Author(s) 2024.

关键词： Mapping

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Neural Implicit Surfaces Learning for Multi-view reconstruction

Neural Implicit Surfaces Learning for Multi-view Reconstruct...

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2023 International conference on Mechatronic Engineering and Artificial Intelligence, MEAI 2023

作者： Zhang, Yingyu Qin, Bin Xiao, Hao Yang, Wenjun College of Electronics and Information Enginnering ShenZhen University ShenZhen China Information Center ShenZhen University ShenZhen University ShenZhen China

ISBN: (纸本)9781510674608

Neural Radiance Field (NeRF), a compelling technique in the field of Computer Vision, represents a novel approach to view synthesis using implicit scene representation. By learning to represent 3d scenes from images, its goal is to render photorealistic images of the scene from unobserved viewpoints, showcasing the immense potential of neural volumetric representations. As a novel view synthesis and 3d reconstruction method, NeRF models find applications in robotics, urban mapping, autonomous navigation, virtual reality augmented reality, and more. In this article, we introduce a new 3d surface representation method called Signed distance Function Field (SdF). We have developed a new volume rendering technique for training a neural SdF representation. In our research process, we noticed that traditional volume rendering methods have poor imaging performance in complex structures and self occluding images during surface reconstruction. Therefore, we have designed a new neural network to reduce the impact of complex structures and self occluding objects on 3d reconstruction. This results in more precise surface reconstruction, even in the absence of mask supervision. Our experiments, conducted on both the dTU dataset, demonstrate that this superiority is particularly evident when dealing with objects and scenes characterized by intricate structures and self-occlusion. © 2024 SPIE.

关键词： Augmented reality

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developing enhanced and enriched 3d models of cultural heritage assets as part of the eu co-funded 5dculture project 10

Developing enhanced and enriched 3d models of cultural herit...

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10th International Workshop 3d-ARCH "3d virtual reconstruction and visualization of complex architectures"

作者： Corns, Anthony davidson, Lesley Namberi, Siva O Reilly, Rebecca Shaw, Robert The Discovery Programme: Centre for Archaeology and Innovation Ireland Unit 2 Merchants House 27-30 Merchants Quay Dublin 8 D08 K3KD Ireland

5dculture is a 24-month collaborative project co-funded by the European Union. It includes twelve partners from diverse sectors of cultural heritage, including archaeology, museums and fashion. It aims to enrich the offer of European 3d digital cultural heritage assets in the data space and fosters their reuse in important domains such as education, tourism and the wider cultural and creative sectors towards socially and economically sustainable outcomes. In particular, the project will deliver high-quality 3d content by identifying and engaging existing datasets from partners collections focusing on topics of fashion, archaeology and architecture, all of which occupy a central place in the vast cultural heritage of Europe. It will also develop several reuse scenarios, which will experiment with the aforementioned assets in their complexity (from high-quality to derivatives). The discovery Programme has a long research interest in 3d digital documentation and has participated in collaborative projects in the past, notably 3d-ICONS. However, opportunities and challenges in the reuse of 3d archaeological content exist, including the reuse of 3d content to enhance visitors experience at archaeological sites and the ability to exploit 3d surrogates for different sectors (tourism, education, gaming, the arts, conservation and heritage management). This paper will present the research that has been undertaken in this context, through the development of an enhanced processing pipeline to improve the quality of 3d models of cultural heritage assets, resulting in their improved re-use. It will present the approaches to improving model geometry, generating and applying enhanced textures, creating rich and functional metadata and strategies for persistence and archiving. A core component of our research has been the development of the processing pipeline to improve 3d model appearance through the application of parametric materials in the development of synthetic textures whic

关键词： Pipelines

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Strategies and experiments for massive 3d digitalization of the remains after the notre dame de paris fire 10

Strategies and experiments for massive 3d digitalization of ...

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10th International Workshop 3d-ARCH "3d virtual reconstruction and visualization of complex architectures"

作者： Comte, Florent Pamart, Anthony Réby, Kévin de Luca, Livio UPR CNRS 2002 MAP Marseille13402 France

After the catastrophic fire at Notre dame de Paris, a significant challenge was presented by the numerous lead-contaminated remnants. To address this, a detailed digitization strategy was devised and executed, tailored to the unique needs of this extensive and diverse corpus. This strategy involved the development and customization of both hardware and software tools, ensuring their effectiveness throughout the digitization process from initial data acquisition to data dissemination. Central to our approach was the alignment of our methods with the distinct characteristics of each artifact, facilitating their effective preservation and future utility. Our strategy's adaptability was key, allowing us to incorporate advanced deep learning techniques into various aspects of our workflow. Notably, this included the implementation of the Segment Anything Model for automatic image segmentation, enhancing our image-based modeling capabilities. We also ventured into pioneering methods like 3d Gaussian Splatting and the exploration of radiance field methods for visualization. Moreover, the project has been mindful of data responsibility, aiming to make all digital data openly accessible beyond 2025. We have placed a strong emphasis on harmonizing and managing data, minimizing redundancies, and ensuring efficient storage, all while maintaining transparency about the limitations and errors in our methodologies. This holistic approach to digitization, balancing technological innovation with responsible data management, aims to preserve and make accessible the digital heritage of Notre dame de Paris for future generations. © 2024 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： data acquisition

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MVSBoost: An Efficient Point Cloud-Based 3d reconstruction 26

MVSBoost: An Efficient Point Cloud-Based 3D Reconstruction

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26th International conference of the Catalan Association for Artificial Intelligence, CCIA 2024

作者： Haroon, Umair Almughrabi, Ahmad Marques, Ricardo Radeva, Petia Universitat de Barcelona Spain Computer Vision Center Spain Institut de Neurosciències Spain

ISBN: (纸本)9781643685434

Efficient and accurate 3d reconstruction is crucial for various applications, including augmented and virtual reality, medical imaging, and cinematic special effects. While traditional Multi-View Stereo (MVS) systems have been fundamental in these applications, using neural implicit fields in implicit 3d scene modeling has introduced new possibilities for handling complex topologies and continuous surfaces. However, neural implicit fields often suffer from computational inefficiencies, overfitting, and heavy reliance on data quality, limiting their practical use. This paper presents an enhanced MVS framework that integrates multi-view 360-degree imagery with robust camera pose estimation via Structure from Motion (SfM) and advanced image processing for point cloud densification, mesh reconstruction, and texturing. Our approach significantly improves upon traditional MVS methods, offering superior accuracy and precision as validated using Chamfer distance metrics on the Realistic Synthetic 360 dataset. The developed MVS technique enhances the detail and clarity of 3d reconstructions and demonstrates superior computational efficiency and robustness in complex scene reconstruction, effectively handling occlusions and varying viewpoints. These improvements suggest that our MVS framework can compete with and potentially exceed current state-of-the-art neural implicit field methods, especially in scenarios requiring real-time processing and scalability. © 2024 The Authors.

关键词： Stereo image processing

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Classification and object detection for architectural pathology: Practical tests with training set 10

Classification and object detection for architectural pathol...

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10th International Workshop 3d-ARCH "3d virtual reconstruction and visualization of complex architectures"

作者： Zhang, Kai Mea, Chiara Fiorillo, Fausta Fassi, Francesco 3D Survey Group ABC Department Politecnico di Milano Via Ponzio 31 Milano20133 Italy

Image classification and object detection techniques have been widely discussed and developed in recent years;they are the basis of various prosperous applications, for example, real-Time mapping. Promising as it is, the practical test in the cultural heritage field encountered multiple problems. In this paper, the authors attempt to share the research experimentations and the empirical knowledge focusing on the classification and detection of architectural pathology. The tests are built on elaborated training sets annotated with analysed and in-Advance defined categories. The trained models were examined from the perspective of evaluation sets, model explanation and unseen datasets. The outcomes indicated the mistakes and confusions behind things and stuff in the object detection efforts, to which cultural heritage and architectural field are closely related. The model also reveals specific visual patterns for recognition from thousands of instances in the training set. By digging into different aspects of model performance, the potential and limitations of these techniques in practical applications can be better understood. © Author(s) 2024.

关键词： Object detection

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AURORA: Automated Unleash of 3d Room Outlines for VR Applications 19

AURORA: Automated Unleash of 3D Room Outlines for VR Applica...

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19th ACM SIGGRAPH International conference on virtual-Reality Continuum and its Applications in Industry, VRCAI 2024

作者： Han, Huijun Liang, Yongqing Zhou, Yuanlong Wang, Wenping Rojas-Muñoz, Edgar J. Li, Xin Computer Science and Engineering Texas A and M University College StationTX United States College of Performance Visualization and Fine Arts Texas A and M University College StationTX United States

ISBN: (纸本)9798400713484

Creating realistic VR experiences is challenging due to the labor-intensive process of accurately replicating real-world details into virtual scenes, highlighting the need for automated methods that maintain spatial accuracy and provide design flexibility. In this paper, we propose AURORA, a novel method that leverages RGB-d images to automatically generate both purely virtual reality (VR) scenes and VR scenes combined with real-world elements. This approach can benefit designers by streamlining the process of converting real-world details into virtual scenes. AURORA integrates advanced techniques in image processing, segmentation, and 3d reconstruction to efficiently create realistic and detailed interior designs from real-world environments. The design of this integration ensures optimal performance and precision, addressing key challenges in automated indoor design generation by uniquely combining and leveraging the strengths of foundation models. We demonstrate the effectiveness of our approach through experiments, both on self-captured data and public datasets, showcasing its potential to enhance virtual reality (VR) applications by providing interior designs that conform to real-world positioning. © 2024 ACM.

关键词： virtual environments

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Multi View reconstruction Algorithm of Subway Space design Based on virtual Reality Fusion Technology 1

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13th International conference on Frontier Computing, FC 2023

作者： Ye, Shen Wang, Quannan School of Environmental Design Wu Han Institute of Design and Sciences Hubei Wuhan430205 China

ISBN: (数字)9789819994168

ISBN: (纸本)9789819994151

Multi view reconstruction algorithm of subway spatial design based is a new method of 3d model visualization simulation. The application program is used to simulate the construction process of underground space (such as tunnel, station, platform, etc.). The technology can be applied to a variety of situations, including urban planning and architecture. It can better understand how the underground space is built by using different methods such as traditional computer aided design (CAd), computer drawing and even 3d printing. In this paper, we will discuss the application of multi view reconstruction algorithm in Kanpur IIT subway space design project. digital media art is involved in the subway space, breaking through the traditional art form of subway space, and embodying the interactive, interesting and novel art, which makes the research in the design and research of subway space artistry of the times significant. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： virtual reality

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A CNN-based Multi-Task Regressor Network for Three-dimensional reconstruction From 3d Point Cloud 1

A CNN-based Multi-Task Regressor Network for Three-dimension...

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1st International conference on Global Aeronautical Engineering and Satellite Technology, GAST 2024

作者： Hassnae, Remmach driss, Essabbar Raja, Mouachi Yasser, Chadli Saad Mohamed, Sadgal Lamigep Laboratory Emsi Marrakesh Marrakesh Morocco Cadi Ayyad University Computer Systems Engineering Laboratory Departement of Computer Science Marrakesh Morocco

ISBN: (纸本)9798350371598

The field of three-dimensional reconstruction plays a pivotal role across diverse domains such as computer graphics, virtual reality, robotics, archaeology, and medical imaging. This paper presents a novel deep learning framework for three-dimensional object reconstruction utilizing 3d point clouds, specifically focusing on a Multi-Task Regressor within a Convolutional Neural Network (CNN) architecture. Acknowledging the challenges associated with applying convolutions directly to point clouds, we adopt an innovative approach by building upon the PointNet architecture. Our adaptation integrates a Multi-Task Regressor to achieve highly accurate reconstructions of Supershapes from 3d point clouds. Our methodology involves employing PointNet to extract features from the input 3d point cloud. Subsequently, these features are inputted into a Multi-Task Regressor, which simultaneously predicts multiple outputs. In the context of Supershape reconstruction, the Multi-Task Regressor predicts the essential parameters needed to faithfully recreate the intricate shape. Unlike traditional single-output regressors, our approach considers and predicts multiple facets of the reconstruction process concurrently, enhancing the overall efficiency and accuracy of the model. The results of our experiments surpassed expectations, demonstrating notable improvements in precision and predictive cost. This research not only contributes to the advancement of three-dimensional reconstruction techniques but also highlights the efficacy of employing a Multi-Task Regressor for handling diverse regression objectives within the context of complex shape reconstruction from 3d point clouds. © 2024 IEEE.

关键词： Convolution

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virtual restoration of Buddha statues based on high-precision 3d models 4

Virtual restoration of Buddha statues based on high-precisio...

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4th International conference on Geoscience and Remote Sensing Mapping, GRSM 2022

作者： Wang, Fei Hou, Miaole School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture Beijing100044 China Beijing Key Laboratory For Architectural Heritage Fine Reconstruction & Health Monitoring No.15Yongyuan Road Daxing District Beijing100044 China

ISBN: (数字)9781510662179

ISBN: (纸本)9781510662162

With the development of new technologies such as 3d laser scanning, 3d reconstruction and virtual reality, digital conservation of cultural relics has been widely applied and has become an important way to record, display, monitor, digitally restore, study and protect cultural relics. Aiming at the repair of the damaged chignon of the Big Buddha in Tongnan, a virtual restoration method based on the geometric feature information of the 3d point cloud model is proposed. This method is based on the high-precision 3d model obtained by 3d laser scanning, combined with close-range photogrammetry and computer virtual reality technology, and integrates historical evidence data and statistical analysis of the 3d model data of the Buddha's chignon to carry out a variety of virtual restoration effects on the Buddha's chignon in the computer, and the experimental The results show that the virtual restoration based on the high-precision 3d model is practical and feasible, and has a certain guiding significance for the actual restoration of the chignon of the Buddha. © 2023 SPIE.

关键词： 3d modeling

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