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Accuracy Analysis in Productivity Games: A Case Study on Landmark Annotation
Date Issued
2008
Date
2008
Author(s)
Chen, Li-Hui
Abstract
Despite impressive advancement in computer technology, there are still some problems that humans can solve efficiently but current computer programs can not. Image recognition and annotation are examples. Human computation is a new research area that focuses on this kind of problems. This thesis aims to explore the power of human computation and shows how humans could help solve problems that are hard for computers. We propose a two-player online human computation game, Image Hunter, to achieve the task of annotating for a collection of landmark images on the Internet. Moreover, we address on the quality analysis for the data collected by the game. We propose confidence evaluation instead of times accumulation to estimate the accuracy of the data. Experiments involving 28 players have been conducted. The preliminary results demonstrate that the game mechanism is reasonable and with confidence evaluation mechanism the accuracy improves effectively.
Subjects
人機協力演算法
具有生產力的遊戲
正確性分析
信任值
信任值估算
Type
thesis
File(s)
No Thumbnail Available
Name
ntu-97-R95922054-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):b06ba1a025765bab2859c8cac46ae36b