A Performance Evaluation of Local Features for Image Based 3D Reconstruction | |
Fan, Bin1,2; Qingqun Kong2,3; Xinchao Wang4; Zhiheng Wang5; Shiming Xiang1,2; Chunhong Pan1,2; Pascal Fua1,2 | |
刊名 | IEEE Transactions on Image Processing |
2019 | |
卷号 | 28期号:10页码:4774-4789 |
关键词 | Local Feautre, Image Matching, 3d Reconstruction, Sfm |
文献子类 | 期刊 |
英文摘要 | This paper performs a comprehensive and comparative evaluation of the state-of-the-art local features for the task of image-based 3D reconstruction. The evaluated local features cover the recently developed ones by using powerful machine learning techniques and the elaborately designed handcrafted features. To obtain a comprehensive evaluation, we choose to include both float type features and binary ones. Meanwhile, two kinds of datasets have been used in this evaluation. One is a dataset of many different scene types with groundtruth 3D points, containing images of different scenes captured at fixed positions, for quantitative performance evaluation of different local features in the controlled image capturing situation. The other dataset contains Internet scale image sets of several landmarks with a lot of unrelated images, which is used for qualitative performance evaluation of different local features in the free image collection situation. Our experimental results show that binary features are competent to reconstruct scenes from controlled image sequences with only a fraction of processing time compared to using float type features. However, for the case of a large scale image set with many distracting images, float type features show a clear advantage over binary ones. Currently, the most traditional SIFT is very stable with regard to scene types in this specific task and produces very competitive reconstruction results among all the evaluated local features. Meanwhile, although the learned binary features are not as competitive as the handcrafted ones, learning float type features with CNN is promising but still requires much effort in the future. |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/25801] |
专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
通讯作者 | Zhiheng Wang |
作者单位 | 1.National Laboratory of Pattern Recognition 2.Institute of Automation, Chinese Academy of Sciences 3.University of Chinese Academy of Sciences 4.Steven Institute of Technology 5.Henan Polytechnic University 6.CVLab, EPFL |
推荐引用方式 GB/T 7714 | Fan, Bin,Qingqun Kong,Xinchao Wang,et al. A Performance Evaluation of Local Features for Image Based 3D Reconstruction[J]. IEEE Transactions on Image Processing,2019,28(10):4774-4789. |
APA | Fan, Bin.,Qingqun Kong.,Xinchao Wang.,Zhiheng Wang.,Shiming Xiang.,...&Pascal Fua.(2019).A Performance Evaluation of Local Features for Image Based 3D Reconstruction.IEEE Transactions on Image Processing,28(10),4774-4789. |
MLA | Fan, Bin,et al."A Performance Evaluation of Local Features for Image Based 3D Reconstruction".IEEE Transactions on Image Processing 28.10(2019):4774-4789. |
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