What Makes Photo Cultures Different?

Реди, Мириам; Crockett, Damon; Манович, Лев; Osindero, Simon

doi:10.1145/2964284.2967228

Cited by 7 publications

(8 citation statements)

References 9 publications

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“…Computer vision could have been used to obtain an approximate categorization of this demographic. For instance, Hu et al [16] and Redi et al [46] deploy artificial vision to categorize images by subject. However, we chose to carry it out manually since other observations for other metrics had to be carried out visually.…”

Section: Whomentioning

confidence: 99%

Implementing Gehl’s Theory to Study Urban Space. The Case of Monotowns

et al. 2021

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The paper presents a method to operationalize Jan Gehl’s questions for public space into metrics to map Russian monotowns’ urban life in 2017. With the use of social media data, it becomes possible to scale Gehl’s approach from the survey of small urban areas to the analysis of entire cities while maintaining the human scale’s resolution. When underperforming public spaces are detected, we propose a matrix for urban design interventions using Jane Jacobs’ typologies for good city life. Furthermore, this method was deployed to improve the conditions of public spaces in Russian monotowns through a series of architectural briefs for design competitions and urban design guidelines for local administrations.

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Section: Whomentioning

confidence: 99%

Implementing Gehl’s Theory to Study Urban Space. The Case of Monotowns

et al. 2021

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“…They discovered multiple fashion combinations by clustering and performed a comparative analysis of Northern and Southern Hemisphere clothing. Redi et al [29] analyzed the cultural styles of photographs using target detection methods and aesthetic computational tools to quantify the degree of similarity of photographs taken using a supervised classification approach. Shen et al [40] proposed a visual consistency approach to find the same regions from artworks through cosine similarity.…”

Section: Computer Vision and Stylementioning

confidence: 99%

“…However, multiobjective similarity metrics are complex, such as similarity metrics between cities. In previous studies [28,29,44], confusion matrices are often used to solve multiobjective metric problems. This method has the advantage of simple calculation and no consideration of the type and number of targets.…”

Section: Intercity Landscapementioning

confidence: 99%

“…The intention of this study is to acquire CLs from a large number of images to measure the visual differences among cities. The visual differences are mainly influenced by the images themselves, which have a "photographic cultural" nature [29]. This property is also responsible for CL similarity, and, therefore, we consider introducing this property, which has not been considered in previous studies.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [29] also referred to this property as a "style feature", and related studies [30,31] indicated that the statistical information of the feature maps of convolutional neural networks can represent such features well. Inspired by this, we introduced the "style feature".…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the Uniqueness and Similarity of City Landscapes Based on Deep Style Learning

Zhao

Luo

et al. 2021

IJGI

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The city landscape is largely related to the design concept and aesthetics of planners. Influenced by globalization, planners and architects have borrowed from available designs, resulting in the “one city with a thousand faces” phenomenon. In order to create a unique urban landscape, they need to focus on local urban characteristics while learning new knowledge. Therefore, it is particularly important to explore the characteristics of cities’ landscapes. Previous researchers have studied them from different perspectives through social media data such as element types and feature maps. They only considered the content information of a image. However, social media images themselves have a “photographic cultural” character, which affects the city character. Therefore, we introduce this characteristic and propose a deep style learning for the city landscape method that can learn the global landscape features of cities from massive social media images encoded as vectors called city style features (CSFs). We find that CSFs can describe two landscape features: (1) intercity landscape features, which can quantitatively assess the similarity of intercity landscapes (we find that cities in close geographical proximity tend to have greater visual similarity to each other), and (2) intracity landscape features, which contain the inherent style characteristics of cities, and more fine-grained internal-city style characteristics can be obtained through cluster analysis. We validate the effectiveness of the above method on over four million Flickr social media images. The method proposed in this paper also provides a feasible approach for urban style analysis.

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Advances and Challenges in Computational Image Aesthetics

Valenzise

Chen

Dufaux

2021

Human Perception of Visual Information

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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What Makes Photo Cultures Different?

Cited by 7 publications

References 9 publications

Implementing Gehl’s Theory to Study Urban Space. The Case of Monotowns

Implementing Gehl’s Theory to Study Urban Space. The Case of Monotowns

Analysis of the Uniqueness and Similarity of City Landscapes Based on Deep Style Learning

Advances and Challenges in Computational Image Aesthetics

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