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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xinxin Gao Chuang Zhang Ming Wu Zhiqing Lin |
| Copyright Year | 2009 |
| Description | Author affiliation: Pattern Recogniation & Intelligent System Lab, Beijing University of Posts and Telecommunications, Box186#, 100876, China (Xinxin Gao; Chuang Zhang; Ming Wu; Zhiqing Lin) |
| Abstract | Image annotation plays a very important role in managing and retrieving abundant images over the internet nowadays. In this paper, we try to propose a Human-Computer interactive framework for online image annotation which fully considers the human judgments and all online-users' feedback. First, an interactive image annotation interface is demonstrated. It is utilized to interact with online-users and collect the original manual annotations. Second, an object-based image annotation framework is proposed to provide the automatic results for users. Then, the users' feedback can be recorded and integrated to help our system to achieve performance improvement. Third, a comprehensive method of annotation refinement is developed to remove the noisy keywords. Finally, experimental results demonstrate the effectiveness of our proposed system. |
| Starting Page | 400 |
| Ending Page | 404 |
| File Size | 128220 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424448982 |
| DOI | 10.1109/ICNIDC.2009.5360895 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-11-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image recognition Image retrieval Humans Human-Computer interactive Pattern recognition Noise shaping Data mining Object-based Feedback Image annotation Annotation refinement Internet Large-scale systems Intelligent systems Users' feedback |
| Content Type | Text |
| Resource Type | Article |
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