A Novel Automatic Image Annotation Method Based on Multi-Instance Learning
Shunle Zhu, Xiaoqiu Tan · Procedia Engineering · 2011
Automatic image annotation (AIA) is the bridge of high-level semantic information and the low-level feature. AIA is an effective method to resolve the problem of “Semantic Gap”. According to the intrinsic character of AIA, which is many regions contained in the annotated image, AIA Based on the framework of multi-instance learning (MIL) is proposed in this paper. Each keyword is analyzed hierarchically in low-granularity-level under the framework of MIL. Through the representative instances are mined, the semantic similarity of images can be effectively expressed and the better annotation results are able to be acquired, which testifies the effectiveness of the proposed annotation method.