  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.
