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中国科学院软件研究所
  
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文贡坚.一种基于特征编组的直线立体匹配全局算法.软件学报,2006,17(12):2471-2484
一种基于特征编组的直线立体匹配全局算法
A Global Algorithm for Straight Line Stereo Matching Based on Feature Grouping
投稿时间:2005-09-20  修订日期:2006-03-07
DOI:
中文关键词:  立体匹配  直线匹配  特征编组  整数规划  分支定限法
英文关键词:stereo matching  line matching  feature grouping  integer optimization  branch-and-bound method
基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60275008, 40571103 (国家自然科学基金)
作者单位
文贡坚 国防科学技术大学,电子科学与工程学院,ATR重点实验室,湖南,长沙,410073 
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中文摘要:
      由于直线断裂、遮挡以及共面空间直线投影等因素的影响,从左右图像中提取出来的直线之间会出现"一配多"甚至"多配多"的匹配情况,然而目前很少有算法能可靠地处理这些情况.提出了一种基于特征编组的匹配算法来解决它.与已有方法不同,该方法是在由两幅图像共同组成的直线集上进行编组.每个特征编组包含了内部直线之间的匹配关系.这样,直线匹配的问题就转化为从直线集中提取一些相互兼容的特征编组的问题.整个算法分为两步:首先在几何和辐射约束的前提下构建所有可能的特征编组,并计算每个特征编组的匹配度,然后从所有可能的特征编组中寻找一个特征编组子集,在保证直线集中的每条直线最多属于该子集中一个特征编组的前提下,使得该子集中特征编组的匹配度之和最大.为了解决这个整数规划问题,设计了一种分两阶段的算法:首先将整个问题分为多个子问题,然后对于每个子问题,利用分支定限法寻找最优解.将所提出的算法应用于实际的立体图像对中,取得了满意的结果.
英文摘要:
      Due to line fragmentation, occlusion and projection of conjoint coplanar space straight lines, there are many “one-to-multiple” and even “multiple-to-multiple” mappings between two features sets in the process of stereo matching, but few reliable methods exist to deal with these cases. In this paper, an algorithm based on feature grouping is proposed to solve these problems. Different from the existing approaches, feature grouping is implemented among the feature set which is composed of linear features extracted from two images, and each feature group contains its associated matching relationships. Therefore, stereo matching becomes equivalent to extracting a set of mutually compatible feature groups from the two images. Two major steps involve in the whole matching process. As much putative feature groups as possible are constructed and their match measures are computed by exploiting some viable geometric and photometric constraints, and then a subset of feature groups is searched so that the sum of the associated match measures is the maximum under the condition that any extracted linear feature at most belongs to only a selected feature group. In order to solve the integer optimization problem, a two-stage method is devised. First, the whole problem is divided into many sub-problems. Second, for each sub-problem, a branch-and-bound method is implemented to find the optimal solution. The proposed algorithm is applied to match straight lines extracted from many pairs of real stereo images, and satisfying experimental results are obtained.
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