Digital imagery for significant cultural and historical materials

Chen, Ching-chih; Wactlar, Howard D.; Wang, James; Kiernan, Kevin S.

doi:10.1007/s00799-004-0097-5

Cited by 54 publications

(21 citation statements)

References 31 publications

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“…In terms of image content, there is little to compare among these paintings. An important aspect art historians often examine when studying and comparing paintings is the characteristic strokes used by artists [7]. Many impressionism masters formed their styles by special strokes [10].…”

Section: A Major Challengesmentioning

confidence: 99%

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Studying Digital Imagery of Ancient Paintings by Mixtures of Stochastic Models

Wang

2004

IEEE Trans. on Image Process.

159

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Abstract-This paper addresses learning based characterization of fine art painting styles. The research has the potential to provide a powerful tool to art historians for studying connections among artists or periods in the history of art. Depending on specific applications, paintings can be categorized in different ways. In this paper, we focus on comparing the painting styles of artists. To profile the style of an artist, a mixture of stochastic models is estimated using training images.

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Section: A Major Challengesmentioning

confidence: 99%

“…For a general introduction to digital imagery of cultural heritage materials and related database management, see [7], [18]. Readers are referred to [12], [26] for introduction to computer vision and image retrieval.…”

Section: Related Workmentioning

confidence: 99%

Studying Digital Imagery of Ancient Paintings by Mixtures of Stochastic Models

Wang

2004

IEEE Trans. on Image Process.

159

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“…With the evolution of technologies, efforts are initiated to digitize the ancient arts and paintings [1]. Every artist holds his individual means of narration and depicts the same in the form of paintings.…”

Section: Introductionmentioning

confidence: 99%

Model Based Approach for Identification of Relevant Images from Ancient Paintings

Naidu¹,

Srinivas²

2017

IJEM

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In this paper an attempt is made to retrieve the relevant paintings based on the approach of the artist using Generalized Bivariate Laplacian Mixture Model (GBLMM). This article helps in understanding the outline of assorted artists and help as a means to categorize a scrupulous painting based on the style or the text ingrained within the images. To profile the artist style GBLMM is used. The projected model helps to discriminate the strokes of the artists and lend a hand in the classification of paintings. The proposed model is implemented using high resolution Chinese painting images.

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“…Our work began with analyzing existing literature, sketches, drawings, videos, films, and photographs that describe and feature the four STiCKs chosen. Developing a proper understanding of these artifacts involved researching their history, creation and development; their meaning; their movement and Fourth, not only are these artifacts susceptible to physical decay and destruction [Karadag 2014;Chen et al 2005], but as time evolves some of them may disappear from the carnival [Hill 1985;Crowley 1956c]. Finally, archiving and displaying STiCKs serve educational and research purposes about history, design, visual, and performing arts associated with the carnival.…”

Section: Introductionmentioning

confidence: 99%

New Technologies in the Preservation of Cultural Artifacts with Spatial, Temporal, Corporeal, Kinetic Dimensions: Artifacts in the Trinidad Carnival

Noel¹

2017

SDH

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Historic cultural artifacts with spatial, temporal, corporeal, and kinetic dimensions (STiCK) are large threedimensional sculptures or structures that are performed by the body, occupy large amounts of physical space, and exist in their best physical form for a short period of time. They usually require a lot of space for storage, performance, and exhibition; are best understood in three-dimensions; are susceptible to decay and damage; and are not properly understood if displayed independent of the body. Using four traditional STiCK artifacts in the Trinidad Carnival as a case study, we illustrate how these artifacts can be displayed and interacted with using parametric computer-aided design, augmented reality, and embodied computer interaction. This work has potential implications for design, heritage, the Trinidad Carnival, and for historians, researchers, designers, and computer scientists.

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Digital imagery for significant cultural and historical materials

Cited by 54 publications

References 31 publications

Studying Digital Imagery of Ancient Paintings by Mixtures of Stochastic Models

Studying Digital Imagery of Ancient Paintings by Mixtures of Stochastic Models

Model Based Approach for Identification of Relevant Images from Ancient Paintings

New Technologies in the Preservation of Cultural Artifacts with Spatial, Temporal, Corporeal, Kinetic Dimensions: Artifacts in the Trinidad Carnival

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