Toward a Computer Vision Perspective on the Visual Impact of Vegetation in Symmetries of Urban Environments

Salma Samiei 1, 2 Pejman Rasti 1, 2 Hervé Daniel 3 Etienne Belin 2, 1 Paul Richard 2 David Rousseau 1, 2
1 IRHS - Institut de Recherche en Horticulture et Semences
2 LARIS - Laboratoire Angevin de Recherche en Ingénierie des Systèmes
3 UMR BAGAP - Biodiversité agroécologie et aménagement du paysage
Abstract : Rapid urbanization is a worldwide critical environmental challenge. With this urban migration soaring, we need to live far more efficiently than we currently do by incorporating the natural world in new and innovative ways. There are a lot of researches on ecological, architectural or aesthetic points of view to address this issue. We present a novel approach to assess the visual impact of vegetation in urban street edestrian view with the assistance of computer vision metrics. We statistically evaluate the correlations of the amount of vegetation with objective computer vision traits such as Fourier domain, color histogram, and estimated depth from monocular view. We show that increasing vegetation in urban street views breaks the orthogonal symmetries of urban blocks, enriches the color space with fractal-like symmetries and decreases the cues of projective geometry in depth. These uncovered statistical facts are applied to predict the requested amount of vegetation to make urban street views appear like natural images. Interestingly, these amounts are found in accordance with the ecosystemic approach for urban planning. Also, the study opens new questions for the understanding of the link between geometry and depth perception.
Keywords : depth map projective geometry urban greenery symmetry natural image statistics urban views fourier RGB fractals
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Salma Samiei, Pejman Rasti, Hervé Daniel, Etienne Belin, Paul Richard, et al.. Toward a Computer Vision Perspective on the Visual Impact of Vegetation in Symmetries of Urban Environments. Symmetry, Integrability and Geometry : Methods and Applications, National Academy of Science of Ukraine, 2018, 10 (12), pp.1-18. ⟨10.3390/sym10120666⟩. ⟨hal-01942463⟩

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