Accuracy Analysis in Productivity Games: A Case Study on Landmark Annotation

• Main Authors: Li-Hui Chen, 陳麗徽
• Other Authors: 許永真
• Format: Others
• Language: en_US
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/43404326196918604742

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 96 === 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.