An Unified Image Tagging System Driven by Image-Click-Ads Framework

Abstract

With the exponential growth of web image data, image tagging is becoming crucial in many image based applications such as object recognition and content-based image retrieval. Despite the great progress achieved in automatic recognition technologies, none has yet provided a satisfactory solution to be widely useful in solving generic image recognition problems. So far, only manual tagging can provide reliable tagging results. However, such work is tedious, costly and workers have no motivation. In this paper, we propose an online image tagging system, EyeDentifyIt, driven by image-click-ads framework, which motivates crowdsourcing workers as well as general web users to tag images at high quality for low cost with low workload. A series of usability studies are presented to demonstrate how EyeDentifyIt provides improved user motivations and requires less workload, compared to state-of-the-art approaches.