Google Street View: Capturing the World at Street Level

@article{Anguelov2010GoogleSV,
  title={Google Street View: Capturing the World at Street Level},
  author={Dragomir Anguelov and Carole Dulong and Daniel Filip and Christian Fr{\"u}h and St{\'e}phane Lafon and Richard Lyon and Abhijit S. Ogale and Luc Vincent and Josh Weaver},
  journal={Computer},
  year={2010},
  volume={43},
  pages={32-38}
}
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. 

Figures from this paper

Street-level: Google Street View’s abstraction by datafication
TLDR
Comparing the Broken Windows theory of criminogenesis with big data applications of street-level imagery informs a critical media studies approach to Google Street View and suggests alternative theoretical orientations for algorithm design that avoid the pitfalls of essentialist equations of place with social character.
Google Street View as a Replacement for In-Person Street Surveys: Meta-Analysis of Findings from Evaluations
Abstract Google Street View (GSV) is increasingly being used to evaluate streetscapes for research in fields as diverse as public health, architecture and urban design, and biology. Many researcher...
An algorithm to estimate building heights from Google street-view imagery using single view metrology across a representational state transfer system
Urban ecosystem studies require monitoring, controlling and planning to analyze building density, urban density, urban planning, atmospheric modeling and land use. In urban planning, there are many
Monocular urban localization using street view
TLDR
This is the first work that studies the global urban localization simply with a single camera and Street View, namely a topological place recognition process and then a metric pose estimation by local bundle adjustment.
Street view imagery in urban analytics and GIS: A review
Cataloging Public Objects Using Aerial and Street-Level Images — Urban Trees
TLDR
This work introduces a solution that adapts state-of-the-art CNN-based object detectors and classifiers, and shows that combining multiple views significantly improves both tree detection and tree species classification, rivaling human performance.
Google Street View and the Image as Experience
Google Street View (GSV) presents the world as fact, mapped and documented, and reconstituted online: an approximation of the street condition. Google’s fleet takes the built environment as its
Automatic Sky View Factor Estimation from Street View Photographs - A Big Data Approach
TLDR
This paper presents and validates a method for automatic estimation of SVF from massive amounts of street view photographs and presents an application of the proposed method with about 12,000 GSV panoramas to characterize the spatial distribution of SVf over Manhattan Island in New York City.
GrabView: A Scalable Street View System for Images Taken from Different Devices
TLDR
GrabView is presented, a street view system that uses a data capture during ride sharing service trips model, collects up-to-date geo-referenced multimedia content at low cost, and serves a navigation and browsing user experience equivalent to that from dedicated mapping vehicles.
...
...

References

Large-scale privacy protection in Google Street View
TLDR
This work presents a system that combines a standard sliding-window detector tuned for a high recall, low-precision operating point with a fast post-processing stage that is able to remove additional false positives by incorporating domain-specific information not available to the sliding- window detector.