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Approach to Identification of Changes from Local Surface Normal Analysis of RTI Data in Application to Cultural Heritage 基于局部表面法向分析的RTI数据变化识别方法在文物研究中的应用
Sunita Saha, David Bruce Lewis, R. Sitnik
Identification of changes from cultural heritage (CH) surfaces incor- porates several factors like noise from the surface, error from the acquisition system, and alignment of the two phases of information in a one-time frame. In the post-processing pipeline for change iden- tification, the alignment always generates a bias in calculating the changes. This work proposes a pipeline for processing the surface normal calculated from a simulated Reflectance Transformation Imaging (RTI) acquisition. In this work, we have proposed a normal distribution analysis of the neighboring pixels to give more confi- dence to the change detection method. To claim the ground truth of the segmentation method based on a normal distribution, we have decided to work on the simulated RTI acquisitions. This will help us eliminate the mentioned errors and noises and check their validity. We have considered a visual inspection of the normal distribution of the neighboring pixels and set several parameters to group the several behaviors of the surface changes. From the segmentation, a semi-quantitative change calculation is also possible based on the segmented pixel count in each surface stage. The considered parameters were normalized to make the method independent of the acquisition parameters such as camera and light positions and magnification.
文化遗产(CH)表面变化的识别包括几个因素,如来自表面的噪声,来自采集系统的误差,以及在一次框架中两个阶段信息的对齐。在变更识别的后处理流程中,对齐总是会在计算变更时产生偏差。本文提出了一种处理从模拟反射变换成像(RTI)获取的表面法线的管道。在这项工作中,我们提出了相邻像素的正态分布分析,以提高变化检测方法的可信度。为了证明基于正态分布的分割方法是正确的,我们决定对模拟RTI采集进行研究。这将有助于我们消除上述错误和噪音,并检查其有效性。我们考虑了对相邻像素的正态分布进行视觉检查,并设置了几个参数来分组表面变化的几个行为。从分割中,还可以根据每个表面阶段的分割像素计数进行半定量变化计算。将考虑的参数归一化,使该方法独立于诸如相机和光源位置以及放大倍数等采集参数。
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引用次数: 0
A Methodological Approach for Multi-Temporal Tracking of Silver Tarnishing 银镀层多时间跟踪方法研究
A. Siatou, Y. Castro, M. Nurit, H. Chatoux, Gaëtan Le Goïc, C. Degrigny, L. Brambilla, A. Mansouri
Silver tarnish manifests by changes in the optical properties of the material. Documenting these changes creates many challenges for imaging techniques. This paper proposes a methodological approach based on processing Reflectance Transformation Imaging (RTI) data for tracking multi-temporal changes on such surfaces. Through the statistical analysis of the surface's angular reflectance, information related to the appearance attributes can be evaluated and visualized by maps. Thus, this paper explores the global surface change of the reflectance response of silver tarnishing as a function of time. A qualitative and semi-quantitative evaluation is based on multivariate distance measurements at different time intervals. The results are compared to surface change evaluation by visual inspection, photographic documentation, and colourimetry, practices traditionally used in conservation documentation to monitor surface changes over time. The outcome of this research illustrates the possibilities of RTI data analysis as a tool for accurate multi-temporal documentation of the optical properties changes on specular surfaces.
银的暗淡表现为材料光学性质的变化。记录这些变化给成像技术带来了许多挑战。本文提出了一种基于处理反射变换成像(RTI)数据的方法来跟踪此类表面的多时相变化。通过对表面角反射率的统计分析,可以通过地图对与外观属性相关的信息进行评估和可视化。因此,本文探讨了银光泽的反射响应随时间的全球表面变化。定性和半定量评价是基于不同时间间隔的多变量距离测量。将结果与通过目视检查、摄影记录和比色法进行的表面变化评估进行比较,这些方法传统上用于保护文件中监测表面随时间的变化。本研究的结果说明了RTI数据分析作为一种精确记录镜面光学特性变化的工具的可能性。
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引用次数: 1
Building Blocks for a Virtual Time Machine: From Book CT to Automated Art Understanding 虚拟时间机器的构建模块:从书本CT到自动艺术理解
Andreas K. Maier
An abstract is usually brief, it must do almost as much work as Time travel is an old dream of mankind that is fueled by fascination and curiosity. Of course, such a journey through time goes far beyond our physical possibilities today. Historical science largely recapitulates the past using text, while the creative industry reproduces it as a more or less well-researched fiction. The Time Machine Initiative has now taken on the task of digitizing and processing the cultural heritage on a large scale in order to create new virtual accesses to the past, which - taking into account the fragmentary tradition - come close to a journey through time. In a large-scale interdisciplinary and trans-European research project, a kind of edition of European history is to be created which, as a data-saturated reconstruction, can create a new form of comprehensibility and experience. The time machine would therefore be a virtual research environment. In order to reach this ambitious goal, digitization and automated analysis of history and art has to be taken one step at a time. In the presentation, we shortly describe the project and present concrete research results that have been obtained in this direction ranging from book CT, i.e., the scanning of a whole book in a single scan, over writer and font identification up to first results on automated art analysis and understanding.
摘要通常是简短的,它必须做的工作几乎和时间旅行一样多,时间旅行是人类的一个古老的梦想,是由迷恋和好奇心推动的。当然,这样的穿越之旅远远超出了我们今天的物理可能性。历史科学在很大程度上是用文字来概括过去,而创意产业则将其复制为或多或少经过充分研究的小说。时间机器计划现在承担了大规模数字化和处理文化遗产的任务,以便创建新的虚拟访问过去,考虑到支离破碎的传统,这接近于穿越时间的旅行。在一个大规模的跨学科和跨欧洲的研究项目中,一种欧洲历史的版本将被创造出来,作为一种数据饱和的重建,它可以创造一种新的可理解性和经验形式。因此,时间机器将是一个虚拟的研究环境。为了实现这一雄心勃勃的目标,历史和艺术的数字化和自动化分析必须一步一步地进行。在演讲中,我们简要地描述了这个项目,并介绍了在这个方向上取得的具体研究成果,从书籍CT,即在一次扫描中扫描整本书,到作者和字体识别,再到自动艺术分析和理解的第一个结果。
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引用次数: 0
Data-driven Automatic Attribution of Azerbaijani Flat Woven Carpets 数据驱动的阿塞拜疆平织地毯自动归属
Rashid Bakirov, Roya Taghieva, Nigar Eyvazli, Umay Mammadzada
Carpet attribution is an important task for studying the carpets and textiles, and more generally the history and culture of the communities producing these carpets. However, this is not an easy task, often relying on experts' subjective opinion or complex chemical or radiographical analysis, often not available to many practitioners. In this work, building on the success of applying machine learning and artificial intelligence methods in different fields, we present another, data-driven approach for carpet attribution. Based on a large dataset of Azerbaijani flat woven carpets we have developed a novel machine learning based data-driven carpet attribution system, which successfully determines their types, schools and weaving century, achieving up to 98% accuracy of the attribution.
地毯归属是研究地毯和纺织品的重要任务,更广泛地说,是研究生产这些地毯的社区的历史和文化的重要任务。然而,这并不是一项容易的任务,通常依赖于专家的主观意见或复杂的化学或放射学分析,许多从业者通常无法获得。在这项工作中,基于机器学习和人工智能方法在不同领域的成功应用,我们提出了另一种数据驱动的地毯归因方法。基于阿塞拜疆平面编织地毯的大型数据集,我们开发了一种新颖的基于机器学习的数据驱动地毯归属系统,该系统成功地确定了它们的类型、学校和编织世纪,实现了高达98%的归属准确率。
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引用次数: 0
Contributions of Photometry to the 3D-digitization of Heritage 光度法对文物3d数字化的贡献
A. Laurent, J. Mélou, Thomas Sagory, C. Fritz, Jean-Denis Durou
The nature of archaeological research implies documenting and recording the remains or structures uncovered in the most precise and objective way possible. Archaeologists use digital tools precisely because they meet the challenges of their discipline. The creation of digital twins thus actively contributes to the study, protection and dissemination of archaeological heritage. From the study of a territory to the analysis of a trace left by a tool, archaeology reasons at different scales and combines analyses and multi-scalar approaches. This represents a challenge in itself. The development of an open-source photometric stereo suite makes it possible to respond in part to this work by taking into account the great diversity of archaeological remains while producing models that combine volume accuracy and color reliability.
考古研究的本质就是要尽可能以最精确和客观的方式记录和记录发现的遗迹或结构。考古学家之所以使用数字工具,正是因为他们面临着学科的挑战。因此,数字双胞胎的创建积极地促进了考古遗产的研究、保护和传播。从对一块土地的研究到对一件工具留下的痕迹的分析,考古学在不同的尺度上进行推理,并将分析和多尺度方法相结合。这本身就是一个挑战。开发一个开源的光度立体套件,在生产结合体积精度和颜色可靠性的模型的同时,考虑到考古遗迹的巨大多样性,可以在一定程度上响应这项工作。
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引用次数: 1
Deep Level Annotation for Painter Attribution on Greek Vases utilizing Object Detection 基于对象检测的希腊花瓶画家归属深度标注
Marta Kipke, L. Brinkmeyer, Souaybou Bagayoko, L. Schmidt-Thieme, Martin Langner
Painter attribution is based on a variety of factors, oftentimes deeply buried in the details such as the brushstrokes of the ears or the eyes, which a painter might paint in a specific way. To get to this details, the images have to be examined carefully and intensively. Our work is focused on this phenomenon of painter attribution, investigating those details using supervised machine learning methods for image recognition that rely on a set representation. In this paper however, we are going to focus on one step of our work specifically: The annotation process. With such a focus on details, a dense and detailed, but also transparent annotation of the images is necessary. On one hand this is essential for our research, on the other hand however, it is very time consuming and requires a lot of human resources. Therefore we developed an ontology for the annotation of the images and a semi-automated workflow with object detection component using YOLOv3 and closely tied to our ontology. This way we were able to automate our processes as efficiently as possible while maintaining the complexity of our annotations.
画家的归属是基于多种因素的,这些因素往往深埋在画家可能以特定方式画出的耳朵或眼睛的笔触等细节中。为了获得这些细节,必须仔细而深入地检查这些图像。我们的工作集中在这种画家归属现象上,使用依赖于集合表示的图像识别的监督机器学习方法来研究这些细节。然而,在本文中,我们将特别关注我们工作的一个步骤:注释过程。在这样注重细节的情况下,对图像进行密集、细致但又透明的注释是必要的。一方面,这对我们的研究是必不可少的,但另一方面,这是非常耗时的,需要大量的人力资源。因此,我们使用YOLOv3开发了一个用于图像注释的本体和一个带有对象检测组件的半自动工作流,并与我们的本体紧密相关。通过这种方式,我们能够尽可能高效地自动化流程,同时保持注释的复杂性。
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引用次数: 0
Creating a Time Machine of Future Pasts: Data Integration and Interoperability for Cross-disciplinary Research on Urban Heritage Clusters 创建未来过去的时间机器:城市遗产集群跨学科研究的数据集成与互操作性
G. Artopoulos
Historic clusters of heritage buildings comprise the core of a great number of European cities and represent the fabric based on which today's municipalities have developed historically. The sustainable development of these environments is often threatened by urbanization, gentrification or depopulation phenomena. These urban environments should not be studied and analysed as static formations disconnected from the contemporary fabric of a city, but rather as an assemblage of tangible and intangible assets subjected to dynamic pressures of economic, environmental, and social activities. The value of the historic built environment for local communities, as a tangible result of the cultural heritage of a place, does not only lie in preserving a continuity with past societies, but it can become important in achieving more resilient futures for the city [1]. The cross-disciplinary nature of the pressing challenges posed by said phenomena requires the development of novel data-driven methods [2] for the re-use, regeneration and safeguarding of neglected areas of our cities' existing building stock. Digitisation of the construction industry [3] and urban data analytics [4] offer new opportunities for historic cities that undergo transformations. The presentation will discuss about the methodological and technical framework required for the creation of a platform that will function as a time machine of our cities in the future. A time machine that does not aim only at representing how our cities used to be in the past, but rather one that curates and stores current transformations of our built environment, with the objective to enable dynamic observation of the existing building stock at neighborhood scale in present and future times. In this context, the presentation will be occupied with the significance of bringing the building scale (architectural) data together with neighbourhood scale (environmental) data in the same digital environment to enable deeper and cross-disciplinary insights of built heritage assets' conditions. This data-driven study is enabled by the use of Building Information Modelling (BIM) tools for the common management of multi-scale and multi-discipline datasets generated by the 3D documentation, non-destructive testing and metadata integration of conservation state analyses and historic architecture information of building assets. In this context, the presentation will be occupied with the significance of bringing the building scale (architectural) data together with neighbourhood scale (environmental) data in the same digital environment to enable deeper and cross-disciplinary insights of built heritage assets' conditions. This data-driven study is enabled by the use of Building Information Modelling (BIM) tools for the common management of multi-scale and multi-discipline datasets generated by the 3D documentation, non-destructive testing and metadata integration of conservation state analyses and historic architecture inform
历史遗产建筑群构成了许多欧洲城市的核心,代表了当今城市历史发展的基础。这些环境的可持续发展往往受到城市化、高档化或人口减少现象的威胁。这些城市环境不应该作为与当代城市结构脱节的静态结构来研究和分析,而应该作为受经济、环境和社会活动动态压力影响的有形和无形资产的集合。作为一个地方文化遗产的有形结果,历史建筑环境对当地社区的价值不仅在于保持与过去社会的连续性,而且对于实现城市更有弹性的未来也很重要。上述现象所带来的紧迫挑战的跨学科性质要求开发新的数据驱动方法,以再利用、再生和保护我们城市现有建筑存量中被忽视的区域。建筑业的数字化和城市数据分析为经历转型的历史城市提供了新的机遇。该报告将讨论创建一个平台所需的方法和技术框架,该平台将在未来充当我们城市的时间机器。这是一台时间机器,它的目的不仅仅是代表我们的城市过去的样子,而是策划和存储我们建筑环境的当前变化,目的是在现在和未来的时间里,在社区尺度上对现有建筑存量进行动态观察。在这种背景下,本次演讲将重点讨论将建筑规模(建筑)数据与社区规模(环境)数据结合在同一个数字环境中的重要性,从而对建筑遗产资产的状况进行更深入和跨学科的了解。这项数据驱动的研究是通过使用建筑信息模型(BIM)工具来实现多尺度和多学科数据集的共同管理,这些数据集由3D文档、无损检测和保存状态分析的元数据集成以及建筑资产的历史建筑信息产生。在这种背景下,本次演讲将重点讨论将建筑规模(建筑)数据与社区规模(环境)数据结合在同一个数字环境中的重要性,从而对建筑遗产资产的状况进行更深入和跨学科的了解。这项数据驱动的研究是通过使用建筑信息模型(BIM)工具来实现多尺度和多学科数据集的共同管理,这些数据集由3D文档、无损检测和保存状态分析的元数据集成以及建筑资产的历史建筑信息产生。最后,报告将描述将这些数据集集成到在线存储库中的要求,以供公众和相关利益相关者开放访问空间数据分析,这些数据分析可用于领土规划、能源监测、教育目的和智慧历史城市应用[5]。本研究针对当前遗存建筑异构数据的存储、访问、分析和更新需求,这些数据主要存在于非结构化的数据库或分散的、难以访问的数据库中。
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Proceedings of the 4th ACM International workshop on Structuring and Understanding of Multimedia heritAge Contents 第四届ACM多媒体遗产内容的构建与理解国际研讨会论文集
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Proceedings of the 4th ACM International workshop on Structuring and Understanding of Multimedia heritAge Contents
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