StreetLens: An In-Vehicle Video Dataset for Public Facility Monitoring in Urban Streets
Authors: 
Amani Abu Jabal, Abdullah Alfarrarjeh, Suhib Alsaggar, Ruba AbuRumman, Kareem Abuqaoud, Loujin Abuhejleh, Ibrahim Almatar, Seon Ho KimAuthors Info & Claims
Pages 415 - 421
Abstract
Monitoring public facilities is essential for governments to establish safer, cleaner, and more resilient cities, ultimately benefiting all citizens. One promising approach for public facility surveillance is to employ visual machine-learning methods on street scenes. The potential development and advancements in such state-of-the-art methods require the availability of visual datasets annotated with several public facility defects (e.g., illegal dumping, graffiti, street potholes, and damaged traffic signs). Towards this, we introduce "StreetLens", a new dataset of videos capturing urban streets with plentiful annotations for vision-based public facility monitoring. This dataset includes four-and-a-half hours of videos recorded by smartphone cameras placed in moving vehicles in the suburbs of three different cities.
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- StreetLens: An In-Vehicle Video Dataset for Public Facility Monitoring in Urban Streets
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Published In
April 2024
557 pages
ISBN:9798400704123
DOI:10.1145/3625468
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Published: 17 April 2024
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