摘要
"语义鸿沟"已成为基于内容图像检索的瓶颈,解决这个问题需要建立从图像的低层特征到高层语义的映射.对当前语义映射研究进行了综述,首先给出一个结合语义的图像检索框架,并分析了图像内容的层次模型及图像语义的表示方法;然后根据算法的特点,将现有的语义映射方法和技术分为4大类,重点阐述了各类方法提出的思路、模型,并讨论各自的优势和局限性;最后以图像检索实际应用的需要为依据,提出在图像语义检索相关领域的重要课题和研究方向.
Semantic gap has become a bottleneck of content-based image retrieval. In order to bridge the gap and improve retrieval accuracy, a map from lower-level visual features to high-level semantics should be formulated. This paper provides a comprehensive survey on semantic mapping. Firstly, an image retrieval framework integrated with high-level semantics is presented. Secondly, image semantic description is introduced in two aspects image content level-models and semantic representations. Thirdly, as the emphasis of this paper, semantic mapping approaches and techniques are investigated by classifying them into four main categories in terms of their characteristics. Various ideas and models proposed in these approaches are analyzed. In addition, advantages and limitations of each category are discussed. Finally, based on the state-of-the-art technology and the demand from real-world applications, several important issues related to semantic image retrieval are identified and some promising research directions are suggested.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2008年第8期1085-1096,共12页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金重点项目(60435010)
国家“八六三”高技术研究发展计划(2006AA01Z128)
国家“九七三”重点基础研究发展规划项目(2007CB311004)
关键词
语义映射
基于内容图像检索
语义概念
图像标注
支持向量机
相关反馈
semantic mapping
content-based image retrieval
semantic concept
image annotation
support vector machine
relevance feedback
