面向计算机视觉问题的图匹配算法研究与应用

项目名称： 面向计算机视觉问题的图匹配算法研究与应用

项目编号： No.61503383

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 杨旭

作者单位： 中国科学院自动化研究所

项目金额： 21万元

中文摘要： 计算机视觉领域中目标识别、三维重建等很多任务往往建立在已确定特征点对应关系的基础上，但如何实现鲁棒的对应实际上仍是一个有挑战性的任务。特征对应可以通过图匹配良好定义并有效解决，受计算机运算、存储能力的提高和其他一些因素的刺激，该研究方向受到关注。在此背景下，针对图匹配算法与应用中的若干关键问题，本项目拟开展两个层次的研究，第一层次拓展申请人前期工作，开展以下三项研究：(1)自适应图匹配、(2)基于邻接张量的不同规模高阶图匹配、(3)基于图匹配的月面图像处理；第二层次探索新的方向，包括：（4）探索基于梯度优化与基于谱分解优化的图匹配算法间的内部关联、（5）探索大规模图匹配的时间/空间可行性方案。在保留前期工作注重理论推导的特点基础上，本项目同时注重应用指导，上述研究内容（3）、（5）均从实际应用需求出发，反推相关算法设计与改进。

中文关键词： 图匹配；计算机视觉；组合优化

英文摘要： Feature correspondence is a fundamental problem in computer vision, which lays the foundations for many important tasks, such as object recognition, 3D reconstruction. It can be well defined, and effectively solved by graph matching, which is attracting more research interests, driven by more powerful computation and storage abilities of modern computers and some other factors. Aiming at some key problems in graph matching algorithms and their applications, in this project we plan to carry out research on two levels, with the first one to extend our previous work, and the second one to explore new research directions. Specifically, the first one consists of three studies, which are respectively adaptive graph matching, adjacency tensor based matching between hyper-graphs with different sizes, and graph matching based lunar surface image processing. And the second one consists of the exploration on relations between gradient based optimization and spectral decomposition based optimization, and the exploration on time/space effective solutions for the matching between huge size graphs. In this project, we pay great attentions to both theoretical deductions and realistic applications, where the above lunar surface image processing and huge size graph matching problems both belong to application driven research.

英文关键词： graph matching;computer vision;combinatorial optimization