文章摘要
引用本文:姜宇航,王美清,黄陈思.优化特征检测的三维重建算法[J].福州大学学报(自然科学版),2017,45(1):86~90
优化特征检测的三维重建算法
3D reconstruction algorithm based on an improved feature point detection method
  
DOI:10.7631/issn.1000-2243.2017.01.86
中文关键词: 三维重建  多视角  特征点检测  Harris算子
英文关键词: 3D reconstruction  multiple views  feature detection  Harris operator
基金项目:
作者单位
姜宇航 福州大学数学与计算机科学学院福建 福州 350116 
王美清 福州大学数学与计算机科学学院福建 福州 350116 
黄陈思 福州大学数学与计算机科学学院福建 福州 350116 
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中文摘要:
      提出一种自适应优化特征点检测的三维重建方法. 该优化方法以Harris算子作为基础,将Harris算子的响应矩阵分块处理,分块选取响应值. 通过比较块中最大响应值与全局响应均值的大小,分情况选择特征点. 解决了Harris算子的阈值设置问题,减少了特征点的集群现象,改善了重建结果容易出现空洞的问题,也间接提高了重建速度. 实验结果验证了该方法的有效性.
英文摘要:
      This paper presents an adaptive 3D reconstruction algorithm based on an improved feature point detection method. The optimization method is based on the Harris operator as the basis. In this article,we firstly separate the Harris operator’s response matrix into blocks. Then we compare the maximum response value in each block with the mean response value of the response matrix. Finally,we select the feature points in different situations. In this way,we solve the problem of how to set the appropriate threshold. The cluster phenomenon of feature points is relieved. And there are fewer holes in the results of the 3D reconstruction. The time of the reconstruction is also saved. The experiment results indicate that our method is effective.
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