Realistic Texture Reconstruction Incorporating Spectrophotometric Color Correction

Papachristou, Konstantinos; Dimitriou, Nikolaos; Drosou, Anastasios; Karagiannis, Giorgos; Tzovaras, Dimitrios

doi:10.1109/icip.2018.8451323

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…At this point, it should be noted that the rigorous 3D reconstruction of the artifacts is important for delivering the intended messages and avoiding misinterpretation of the CH content. Additionally, the progress in terms of digitization methods [15][16][17] can respond to the increasing demand for highly detailed and immersive environments. Thus, CH objects and 3D environments need to be delivered using high-quality 3D models.…”

Section: Introductionmentioning

confidence: 99%

A Virtual Reality Museum to Reinforce the Interpretation of Contemporary Art and Increase the Educational Value of User Experience

et al. 2023

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The cultural heritage sector increasingly integrates augmented and virtual reality (VR) solutions to meet dissemination and interpretation needs for its collections. As research in the field grows, the required entertainment and learning impacts of such applications are rising. This study presents a VR museum that aims to facilitate an understanding of cultural heritage. More specifically, an exhibition was designed, curated and developed in a VR environment based on a framework that encourages the public’s interaction with the artworks and experiential learning through activities that utilize VR functionalities in a meaningful way. This framework was applied in a contemporary art museum where the description of artistic concepts is not always obvious to the general public due to the abstract forms of the artworks or the particularities of different artistic movements. This paper focuses on the application development and three user experience evaluations (museum experts, technical experts and general audience). The results were positive regarding the perceived sense of control, usability and the feelings of the user, including their sense of entertainment. Additionally, the participants valued the educational value of the developed activity types and their usefulness. Moreover, the users were interested in exploring the cultural heritage content available in the exhibition, and they would suggest the application to colleagues or friends.

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Section: Introductionmentioning

confidence: 99%

A Virtual Reality Museum to Reinforce the Interpretation of Contemporary Art and Increase the Educational Value of User Experience

et al. 2023

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“…On the other hand, in recent years deep learning and convolutional networks have gained a lot of traction in quality control for Industry 4.0 [12] with several methods proposed for micro-electronics [13,14], metal parts manufacturing [15], visual inspection process in the printing [16], visual quality control automation on the assembly line [17], spectrophotometric color correction [18] and geometric deep lean learning to support sustainable organizational growth [19] among others.…”

Section: Introductionmentioning

confidence: 99%

A comparison of 2DCNN network architectures and boosting techniques for regression-based textile whiteness estimation

Vafeiadis

Kolokas

Dimitriou

et al. 2022

Simulation Modelling Practice and Theory

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“…Cultural Heritage (CH) assets suffer from man-made hazards, and natural disasters [1,2] as UNESCO declares in "World Heritage in Danger" [3]. Therefore, CH entities require regular inspection for defects, material deterioration and structure deformation.…”

Section: Introductionmentioning

confidence: 99%

Automatic Inspection of Cultural Monuments Using Deep and Tensor-Based Learning on Hyperspectral Imagery

Tzortzis

Rallis

Makantasis

et al. 2022

2022 IEEE International Conference on Image Processing (ICIP)

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In Cultural Heritage, hyperspectral images are commonly used since they provide extended information regarding the optical properties of materials. Thus, the processing of such high-dimensional data becomes challenging from the perspective of machine learning techniques to be applied. In this paper, we propose a Rank-R tensor-based learning model to identify and classify material defects on Cultural Heritage monuments. In contrast to conventional deep learning approaches, the proposed high order tensor-based learning demonstrates greater accuracy and robustness against overfitting. Experimental results on real-world data from UN-ESCO protected areas indicate the superiority of the proposed scheme compared to conventional deep learning models.

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Realistic Texture Reconstruction Incorporating Spectrophotometric Color Correction

Cited by 5 publications

References 16 publications

A Virtual Reality Museum to Reinforce the Interpretation of Contemporary Art and Increase the Educational Value of User Experience

A Virtual Reality Museum to Reinforce the Interpretation of Contemporary Art and Increase the Educational Value of User Experience

A comparison of 2DCNN network architectures and boosting techniques for regression-based textile whiteness estimation

Automatic Inspection of Cultural Monuments Using Deep and Tensor-Based Learning on Hyperspectral Imagery

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