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迭代二次规划遮挡点恢复
引用本文:彭亚丽,刘侍刚,孙增国,洪灵,曹菡.迭代二次规划遮挡点恢复[J].电子学报,2018,46(11):2733-2737.
作者姓名:彭亚丽  刘侍刚  孙增国  洪灵  曹菡
作者单位:1. 现代教学技术教育部重点实验室, 陕西西安 710062; 2. 陕西省教学信息技术工程实验室, 陕西西安 710119; 3. 陕西师范大学计算机科学学院, 陕西西安 710119
摘    要:为了有效地的恢复遮挡点,本文提出一种迭代二次规划遮挡点恢复方法,该方法首先分别利用图像矩阵的行向量和列向量在图像矩阵生成的正交补空间上的投影为0的特性,构造行和列余差函数,同时,对遮挡点分别按行为主序和列为主序进行排列,利用排列后这两者之间存在一个变换关系,将行和列余差函数统一表示为一个二次优化目标函数.该方法同时考虑了遮挡点在行和列两个方向的约束,而且将遮挡点求解转化为迭代求解一个二次规划问题.实验结果表明,本文方法具有收敛速度快,恢复精度高等优点.

关 键 词:遮挡点恢复  二次规划  投影  
收稿时间:2017-08-30

Iterative Quadratic Programming Method for Occlusion Recovery
PENG Ya-li,LIU Shi-gang,SUN Zeng-guo,HONG Ling,CAO Han.Iterative Quadratic Programming Method for Occlusion Recovery[J].Acta Electronica Sinica,2018,46(11):2733-2737.
Authors:PENG Ya-li  LIU Shi-gang  SUN Zeng-guo  HONG Ling  CAO Han
Affiliation:1. Key Laboratory of Modern Teaching Technology, Ministry of Education, Xi'an, Shaanxi 710062; 2. Engineering Laboratory of Teaching Information Technology of Shaanxi Province, Xi'an, Shaanxi 710119; 3. School of Computer Science, Shaanxi Normal University, Xi'an, Shaanxi 710119
Abstract:In order to effectively recover the occlusion,this paper presents an iterative quadratic programming method for occlusion recovery.Based on the characteristic that the projections of the row vector and the column vector of image matrix to the orthogonal complementary subspace spanned by image matrix are zero vectors,the row and the column residual objective functions are respectively defined.At the same time,the occlusion positions are respectively sorted according to the row and the column order,whichcan be denoted by a transformation matrix.Based on the transformation matrix,a united residual objective function which is quadratic is obtained from the row and the column ones.The method has the advantages that both the row and the column constraints are simultaneously considered and the solution of occlusion is transformed to iterative solution a quadratic programming.The experimental results show that the method has fast convergence speed and high precision.
Keywords:occlusion recovery  quadratic programming  projection  
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