A Deep Learning-Based Semantic Filter for RANSAC-Based Fundamental Matrix Calculation and the ORB-SLAM System
文献类型：期刊论文
| 作者 | Shao, Chunyan; Zhang, Chi; Fang, Zaojun; Yang, Guilin |
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2020 |
| 卷号 | 8页码:3212-3223 |
| 关键词 | ATTENTION SELECTION |
| DOI | 10.1109/ACCESS.2019.2962268 |
| 英文摘要 | The estimation of a fundamental matrix (F-matrix) from two-view images is a crucial problem in epipolar geometry, and a key point in visual simultaneous localization and mapping (VSLAM). Conventional robust methods proposed by the data calculation space, such as Random Sample Consensus (RANSAC), encounter computational inefficiency and low accuracy when the outliers exceed 50%. In this paper, a semantic filter-based on faster region-based convolutional neural network (faster R-CNN) is proposed to solve the outlier problem in RANSAC based F-matrix calculations. The semantic filter is trained using semantic patches tailored by inliers, providing different semantic labels in various image regions. First, the patches classified into the top three bad labels are filtered out during the pre-processing phase. Second, precise and robust correspondences are determined by the remaining high-level semantic contexts. Finally, the inliers are assessed using RANSAC to produce an accurate F-matrix. The proposed algorithm can improve the accuracy of F-matrix calculations, as low-quality feature correspondences are effectively decreased. Experiments on KITTI and ETH sequences illustrate that the 3D position error can be reduced by applying the semantic filter to the ORB-SLAM system. Further, indoor and real environment experiments demonstrate that an effective lower trajectory error is yielded with the proposed approach. |
| 学科主题 | Computer Science ; Engineering ; Telecommunications |
| 源URL | [http://ir.nimte.ac.cn/handle/174433/20254]  |
| 专题 | 2020专题 2020专题_期刊论文 |
| 作者单位 | Zhang, C (corresponding author), Chinese Acad Sci, Zhejiang Key Lab Robot & Intelligent Mfg Equipmen, Ningbo Inst Mat Technol & Engn, Ningbo 315201, Zhejiang, Peoples R China. |
| 推荐引用方式 GB/T 7714 | Shao, Chunyan,Zhang, Chi,Fang, Zaojun,et al. A Deep Learning-Based Semantic Filter for RANSAC-Based Fundamental Matrix Calculation and the ORB-SLAM System[J]. IEEE ACCESS,2020,8:3212-3223. |
| APA | Shao, Chunyan,Zhang, Chi,Fang, Zaojun,&Yang, Guilin.(2020).A Deep Learning-Based Semantic Filter for RANSAC-Based Fundamental Matrix Calculation and the ORB-SLAM System.IEEE ACCESS,8,3212-3223. |
| MLA | Shao, Chunyan,et al."A Deep Learning-Based Semantic Filter for RANSAC-Based Fundamental Matrix Calculation and the ORB-SLAM System".IEEE ACCESS 8(2020):3212-3223. |
入库方式： OAI收割
来源：宁波材料技术与工程研究所
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