关键词: 图像检索, 多义性对象学习, 相关反馈

Abstract:

 Recently, the advances in multi-media techniques greatly increase the number of images. Image retrieval becomes a hot topic. It is well-known that semantic gap is the major problem in contentbased image retrieval (CBIR), while the existing image retrieval systems cannot tackle this problem well. Since the ambiguity is one of the important reasons leading to semantic gap, we build iCome, an image retrieval system based on learning for ambiguity objects. Concerning the ambiguity in output space, iCome implements text-based image retrieval. Concerning the ambiguity in input space besides relevance feedback, iCome implements content-based image retrieval.
 

Key words: image retrieval, ambiguous instance learning, relevance feedback