A PLSA-based Semantic Bag Generator with Application to Natural Scene Classification under Multi-Instance Multi-Label Learning Framework

摘要：

Classifying natural scenes into semantic categories has always been a challenging task. So far, many works in this field are primarily intended for single label classification, where each scene example is represented as a single instance vector. The multi-instance multi-label (MIML) learning framework proposed by Z. H. Zhou et al. 1 provides a new solution to the problem of scene classification in a different way. In this paper, we propose a novel scene classification method based on pLSA-based semantic bag generator and MIML learning framework. Under the framework of MIML learning, we introduce the mechanism that transfers an image into a set of instances through the pLSA-based bag generator. Experiments show that our approach achieves better classification performance comparing with the previous work.

关键词： natural scenes semantic categories multiinstance multi-label pLSA bag generator

作者: Shuangping Huang Lianwen Jin

作者单位: School of Electronic and Information Engineering South China University of Technology Guangzhou, P. R. China

会议类型: 国际会议

会议名称: The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)

会议地点: 西安

会议语种:英文

页码: 331-335

在线出版日期: 2009-09-20（万方平台首次上网日期，不代表论文的发表时间）