Learning the Traditional Art of Chinese Calligraphy via Three-Dimensional Reconstruction and Assessment

Jian, Muwei; Dong, Junyu; Gong, Maoguo; Yu, Hui; Nie, Liqiang; Yin, Yilong; Lam, Kin‐Man

doi:10.1109/tmm.2019.2937187

Cited by 53 publications

(19 citation statements)

References 47 publications

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“…e object's reflectance spectrum value is shown on the left, with the wavelength range represented by the abscissa and the reflectance of the corresponding wavelength represented by the ordinate. e spectral distribution of the light source is shown in the center image, with the abscissa representing the wavelength range and the ordinate representing the relative radiation strength corresponding to that wavelength [7]. e standard chroma observer data is shown on the right, with the abscissa representing the wavelength range and the ordinate representing the tristimulus values of the corresponding wavelength.…”

Section: Color Feature Region Segmentation Of Work Of Artmentioning

confidence: 99%

Design of Artistic Creation Style Extraction Model Based on Color Feature Data

Yao

Sohail

2022

Mathematical Problems in Engineering

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In order to improve the style extraction and extraction ability of works of art, a color extraction method based on color features is proposed. The color feature extraction method is used to extract the style of visual works of art. The color feature region of works of art is segmented combined with a sparse scattered point reorganization method. Texture tracking and matching method is used for information fusion of works of art, combined with corner detection, three-dimensional edge contour feature detection method to realize texture filling and automatic rendering of art color extraction to improve art graphics’ color visual feature expression ability. The color feature data method is used for visual feature sampling and equalizing works of art. According to the equilibrium configuration results, the fuzzy clustering method is used to extract the color style of works of art to improve the style extraction and extraction identification ability of works of art. The simulation results show that this method has high accuracy in color extraction of works of art. It has a good effect on the extraction of art creation style and improves the ability of three-dimensional extraction and automatic extraction of art.

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Section: Color Feature Region Segmentation Of Work Of Artmentioning

confidence: 99%

Design of Artistic Creation Style Extraction Model Based on Color Feature Data

Yao

Sohail

2022

Mathematical Problems in Engineering

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“…First of all, the policy is the most basic, so the establishment of online painting and calligraphy trading venues needs a period of precipitation. China's calligraphy and painting market is relatively mature and stable, and value can be reflected in this market [2].…”

Section: Introductionmentioning

confidence: 99%

Research on Marketing Strategy of Chinese Painting and Calligraphy Art Based on Wireless Communication Network Resources

Zhong

2022

Security and Communication Networks

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China has a thousand years of cultural heritage, and its famous paintings and calligraphy works are all representatives of the works of art. Calligraphy and painting have changed from works of art to commodities. This is undoubtedly caused by the changes of the times and society. Calligraphy and painting have gradually formed in this process. The most basic feature that distinguishes the market from other markets is the difference in marketing strategies. Aiming at the current problems in the online marketing of Chinese paintings and calligraphy works, a marketing strategy for Chinese paintings and calligraphy works based on wireless communication network resources is proposed. In view of the lack of accurate analysis of the current Chinese painting and calligraphy and artwork marketing and the uneven quality of the artwork, the above-mentioned problems can be improved through the allocation of wireless communication network resources. The experimental results show that the scope of dissemination of Chinese paintings and calligraphy works using this marketing strategy is wider, and the marketing transaction rate and profit are greater.

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“…For M1, M2, M3, and M4, we adjust the architecture of the feature extraction network, the corresponding multi-scale max-pooling fusion, and the number of concatenations in the regression stage, but maintain the GM-CondConv module unchanged. Note that the 1 8 resolution feature in M4 has dimensions R 1 8 H× 1 8 W ×512 . For the network without full resolution features, we down sample at the beginning.…”

Section: Methodsmentioning

confidence: 99%

“…The goal of photometric stereo is to recover the dense surface orientation of a 3D object from varying shading cues, with a fixed camera, by establishing the relationship between two-dimensional images and the object geometry [1]. The earliest photometric stereo algorithm reconstructed the surface normal based on the Lambertian assumption [2].…”

Section: Introductionmentioning

confidence: 99%

Learning conditional photometric stereo with high-resolution features

Peng

Jian

et al. 2021

Comp. Visual Media

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Photometric stereo aims to reconstruct 3D geometry by recovering the dense surface orientation of a 3D object from multiple images under differing illumination. Traditional methods normally adopt simplified reflectance models to make the surface orientation computable. However, the real reflectances of surfaces greatly limit applicability of such methods to real-world objects. While deep neural networks have been employed to handle non-Lambertian surfaces, these methods are subject to blurring and errors, especially in high-frequency regions (such as crinkles and edges), caused by spectral bias: neural networks favor low-frequency representations so exhibit a bias towards smooth functions. In this paper, therefore, we propose a self-learning conditional network with multi-scale features for photometric stereo, avoiding blurred reconstruction in such regions. Our explorations include: (i) a multi-scale feature fusion architecture, which keeps high-resolution representations and deep feature extraction, simultaneously, and (ii) an improved gradient-motivated conditionally parameterized convolution (GM-CondConv) in our photometric stereo network, with different combinations of convolution kernels for varying surfaces. Extensive experiments on public benchmark datasets show that our calibrated photometric stereo method outperforms the state-of-the-art.

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Learning the Traditional Art of Chinese Calligraphy via Three-Dimensional Reconstruction and Assessment

Cited by 53 publications

References 47 publications

Design of Artistic Creation Style Extraction Model Based on Color Feature Data

Design of Artistic Creation Style Extraction Model Based on Color Feature Data

Research on Marketing Strategy of Chinese Painting and Calligraphy Art Based on Wireless Communication Network Resources

Learning conditional photometric stereo with high-resolution features

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