About StreetScore

StreetScore is an algorithm that assigns a score to a street view based on how safe it looks to a human — but using a computer (see FAQ). This website is a collection of map visualizations of perceived safety of street views from cities in the US as predicted by StreetScore. We will be releasing a map of perceived safety for a new city each week. The StreetScore algorithm was created by Nikhil Naik as part of a collaboration between the Macro Connections group and the Camera Culture group at MIT Media Lab. Jade Philipoom created the visualizations presented in the StreetScore website.

Please send your questions/comments to streetscore@media.mit.edu



StreetScore assigns a score to a street view based on how safe it looks to a human (but using a computer)
Publications
StreetScore - Predicting the Perceived Safety of One Million Streetscapes (pdf)
Nikhil Naik, Jade Philipoom, Ramesh Raskar and César A. Hidalgo.
CVPR Workshop on Web-scale Vision and Social Media
Accepted (2014)

Team Members
Nikhil Naik
Graduate Researcher
Nikhil is a PhD student in the Camera Culture group. He is interested in computer vision and computational social science.
Jade Philipoom
Undergraduate Researcher
Jade is a sophomore at MIT majoring in computer science and mathematics. She is excited to be involved with StreetScore.
César Hidalgo
Principal Investigator
César leads the MIT Media Lab's Macro Connections group. He is interested in complexity, visualization and networks.
Ramesh Raskar
Principal Investigator
Ramesh is the head of the Camera group at the MIT Media Lab. He develops novel tools for visual data capture and sharing.
Press
Acknowledgments
The development of StreetScore has been supported by the MIT Media Lab Consortia and by Google's Living Labs initiative. We would also like to thank Deepak Jagdish, Daniel Smilkov and Michael Wu for their help at various stages of the project.