LOX Framework: Designing Human Computation Games to Update Street Views

Although the Web has abundant information, it does not necessarily contain the latest, most recently updated information. In particular, interactive map websites and the accompanying street view applications often have outdated information because street views change constantly and are very costly to update. In this work, we propose the LOX (Labeling and O/X) framework – a scalable human computation framework that discovers the latest updates of street views through mobile games. The challenge in this work is providing an interface to identify the differences between the latest street view and the outdated street view images. The LOX framework addresses this problem through three mobile games – a compatibility ESP (cESP) Game, a Drag&Drop Labeling Game and an O/X Game. The cESP and Labeling Games encourage users to identify new updates on outdated street view images while the O/X Game increases the precision of the differences identified by the users between the existing street view images and the latest street view. We conducted several user studies to assess the design and usability of the game. The collected data allowed us to assess the performance of utilizing human computation games to update new information while providing us guidance on how to design user interfaces and workflows to increase the quality of the data. The games provide an opportunity for significant cost savings to the service providers by providing an inexpensive method to determine which street views need to be updated.