Image Geolocation by Non-Expert Crowd Workers with an Expert Strategy
- Resource Type
- Conference
- Authors
- Kim, Seungun; Matsubara, Masaki; Morishima, Atsuyuki
- Source
- 2022 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2022 IEEE International Conference on. :4009-4013 Dec, 2022
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Geology
Big Data
Image Geolocation
Crowdsourcing
Human Computation
- Language
Identifying the location where a photo was taken is an important operation in many applications such as the disaster response if it is not associated with the location information. This process usually is done by experts who are familiar with the geolocation. However it is not guaranteed that we can find such expert workers. In this paper, we explore an approach to improve the quality of image geolocation with an workflow implement experts’ strategy for the image geolocations. The result of preliminary experiment suggested that our approach is effective in improving the accuracy of non-expert geolocation.