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An Enhancement of Outdoor Location-Based Augmented Reality Anchor Precision through VSLAM and Google Street View. [PDF]

Sensors (Basel)
Brata KC, Funabiki N, Panduman YYF, Fajrianti ED.   +3 more
europepmc   +1 more source

Semantic segmentation dataset of Land Use/Cover Area frame Survey (LUCAS) rural landscape Street View Images. [PDF]

Data Brief
Martinez-Sanchez L, Hufkens K, Kearsley E, Naydenov D, Czúcz B, van de Velde M.   +5 more
europepmc   +1 more source

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Google Street View: Capturing the World at Street Level

Computer, 2010
Street View serves millions of Google users daily with panoramic imagery captured in hundreds of cities in 20 countries across four continents. A team of Google researchers describes the technical challenges involved in capturing, processing, and serving street-level imagery on a global scale.
Dragomir Anguelov, Luc Vincent
exaly   +2 more sources

Do-It-Yourself Street Views and the Urban Imaginary of Google Street View

Journal of Urban Technology, 2021
Google Street View (GSV) is the de facto platform for street-level visual representation in most settings; however, its coverage is highly uneven due to a range of political, legal, technological, ...
Jonathan Cinnamon, Alfie Gaffney
openaire   +3 more sources

Views of the Street

Transportation Research Record: Journal of the Transportation Research Board, 2006
Urban transportation planners need community involvement to design the urban transportation system for its users and for those who experience its spillovers and externalities, positive and negative. The people in the urban transportation system include travelers, residents of nearby neighborhoods, transit service providers, and others.
McAndrews, Carolyn, Florez-Diaz, Josefina Maria, Deakin, Elizabeth   +2 more
openaire   +2 more sources

Street View Challenge: Identification of Commercial Entities in Street View Imagery

2011 10th International Conference on Machine Learning and Applications and Workshops, 2011
This paper presents our submission to the Street View Challenge of identifying commercial entities in street view imagery. The provided data set of the challenge consists of approximately 129K street view images tagged with GPScoordinates. The problem is to identify different types of businesses visible in these images.
Zamir, Amir Roshan, Darino, Alexander, Shah, Mubarak   +2 more
openaire   +2 more sources

View from street

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Street View

Transfers, 2013
The Pruitt-Igoe Myth, United States, 2011, produced by Chad Freidrichs, Jaime Freidrichs, Brian Woodman, and Paul Fehler, directed by Chad Freidrichs, written by Chad Freidrichs and Jaime Freidrichs.
openaire   +1 more source

Street-level: Google Street View’s abstraction by datafication

New Media & Society, 2017
While aerial photography is associated with vertical objectivity and spatial abstractions, street-level imagery appears less political in its orientation to the particularities of place. I contest this assumption, showing how the aggregation of street-level imagery into “big datasets” allows for the algorithmic sorting of places by their street-level ...
openaire   +1 more source