Results 21 to 30 of about 180,114 (174)

Combining geolocation and height estimation of objects from street level imagery

CoRR, 2023
We propose a pipeline for combined multi-class object geolocation and height estimation from street level RGB imagery, which is considered as a single available input data modality. Our solution is formulated via Markov Random Field optimization with deterministic output.
Matej Ulicny, Vladimir A. Krylov, Julie Connelly, Rozenn Dahyot   +3 more
openaire   +2 more sources

On the potential of Google Street View for environmental waste quantification in urban Africa: An assessment of bias in spatial coverage

Sustainable Environment, 2023
Mismanaged domestic waste threatens ecosystem health, with substantial increases predicted from developing country cities if current consumption and waste service collection trends continue.
Farouk Umar, Josephine Amoah, Moses Asamoah, Mawuli Dzodzomenyo, Chidinma Igwenagu, Lorna-Grace Okotto, Joseph Okotto-Okotto, Pete Shaw, Jim Wright   +8 more
doaj   +1 more source

LONG-TERM VISUAL LOCALIZATION IN LARGE SCALE URBAN ENVIRONMENTS EXPLOITING STREET LEVEL IMAGERY [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
In this paper, we present our approach for robust long-term visual localization in large scale urban environments exploiting street level imagery. Our approach consists of a 2D-image based localization using image retrieval (NetVLAD) to select reference ...
J. Meyer, D. Rettenmund, S. Nebiker
doaj   +1 more source

Urban Visual Intelligence: Studying Cities with AI and Street-level Imagery

CoRR, 2023
The visual dimension of cities has been a fundamental subject in urban studies, since the pioneering work of scholars such as Sitte, Lynch, Arnheim, and Jacobs. Several decades later, big data and artificial intelligence (AI) are revolutionizing how people move, sense, and interact with cities.
Zhang, Fan, Miranda, Arianna Salazar, Duarte, Fábio, Vale, Lawrence, Hack, Gary, Chen, Min, Liu, Yu, Batty, Michael, Ratti, Carlo   +8 more
openaire   +2 more sources

Street-Level Imagery and Deep Learning for Characterization of Exposed Buildings [PDF]

, 2021
<p>Knowledge on the key structural characteristics of exposed buildings is crucial for accurate risk modeling with regard to natural hazards. In risk assessment this information is used to interlink exposed buildings with specific representative vulnerability models and is thus a prerequisite to implement sound risk models.
Aravena Pelizari, Patrick, Geiß, Christian, Schoepfer, Elisabeth, Riedlinger, Torsten, Aguirre, Paula, Santa Maria, Hernan, Merino Pena, Yvonne, Gómez Zapata, Camilo, Pittore, Massimiliano, Taubenböck, Hannes   +9 more
openaire   +3 more sources

The “Paris-End” of Town? Deriving Urban Typologies Using Three Imagery Types

Urban Science, 2020
Urban typologies allow areas to be categorised according to form and the social, demographic, and political uses of the areas. The use of these typologies and finding similarities and dissimilarities between cities enables better targeted interventions ...
Kerry A. Nice, Jason Thompson, Jasper S. Wijnands, Gideon D. P. A. Aschwanden, Mark Stevenson   +4 more
doaj   +1 more source

Object Geolocation from Crowdsourced Street Level Imagery [PDF]

, 2019
We explore the applicability and limitations of a state-of-the-art object detection and geotagging system [4] applied to crowdsourced image data. Our experiments with imagery from Mapillary crowdsourcing platform demonstrate that with increasing amount of images, the detection accuracy is getting close to that obtained with high-end street level data ...
Vladimir A. Krylov, Rozenn Dahyot
openaire   +2 more sources

Detecting, Classifying, and Mapping Retail Storefronts Using Street-level Imagery

Proceedings of the 2020 International Conference on Multimedia Retrieval, 2020
Up-to-date listings of retail stores and related building functions are challenging and costly to maintain. We introduce a novel method for automatically detecting, geo-locating, and classifying retail stores and related commercial functions, on the basis of storefronts extracted from street-level imagery.
Shahin Sharifi Noorian, Sihang Qiu, Achilleas Psyllidis, Alessandro Bozzon, Geert-Jan Houben   +4 more
openaire   +3 more sources

Mitigation Strategies to Improve Reproducibility of Poverty Estimations From Remote Sensing Images Using Deep Learning

Earth and Space Science, 2022
The challenges of Reproducibility and Replicability (R & R) in computer science experiments have become a focus of attention in the last decade, as efforts to adhere to good research practices have increased. However, experiments using Deep Learning (DL)
J. Machicao, A. Ben Abbes, L. Meneguzzi, P. L. P. Corrêa, A. Specht, R. David, G. Subsol, D. Vellenich, R. Devillers, S. Stall, N. Mouquet, M. Chaumont, L. Berti‐Equille, D. Mouillot   +13 more
doaj   +1 more source

Investigating the Impact of Perceived Micro-Level Neighborhood Characteristics on Housing Prices in Shanghai

Land, 2022
It is widely accepted that houses in better-designed neighborhoods are found to enjoy a price premium. Prior studies have mainly examined the impact of macro-level neighborhood attributes (e.g., park accessibility using land use data) on housing prices ...
Qiwei Song, Yifeng Liu, Waishan Qiu, Ruijun Liu, Meikang Li   +4 more
doaj   +1 more source