# On the mapping of Points of Interest through StreetView imagery and paid crowdsourcing

## TL;DR

This paper presents the Virtual City Explorer system that uses paid crowdworkers and street-view imagery to map Points of Interest, offering a scalable and effective alternative to traditional volunteer-based geographic information collection.

## Contribution

The paper introduces a novel system combining street-view imagery and paid crowdsourcing for POI mapping, demonstrating its effectiveness and exploring cost-reduction strategies.

## Key findings

- Paid crowdworkers effectively identify POIs covering most areas.
- The approach finds unique POIs not detected by experts or volunteers.
- Tabooing discovered POIs encourages exploration and reduces costs.

## Abstract

The use of volunteers has emerged as low-cost alternative to generate accurate geographical information, an approach known as Volunteered Geographic Information (VGI). However, VGI is limited by the number and availability of volunteers in the area to be mapped, hindering scalability for large areas and making difficult to map within a time-frame. Fortunately, the availability of street-view imagery enables the virtual exploration of urban environments, making possible the recruitment of contributors not necessarily located in the area to be mapped. In this paper, we describe the design, implementation, and evaluation of the Virtual City Explorer (VCE), a system to collect the coordinates of Points of Interest within a bounded area on top of a street view service with the use of paid crowdworkers. Our evaluation suggests that paid crowdworkers are effective for finding PoIs, and cover almost all the area. With respect to completeness, our approach does not find all PoIs found by experts or VGI communities, but is able to find PoIs that were not found by them, suggesting complementarity. We also studied the impact of making PoIs already discovered by a certain number of workers \emph{taboo} for incoming workers, finding that it encourages more exploration from workers , increase the number of detected PoIs , and reduce costs.