Name
Abstract | ||
|---|---|---|
Visual odometry is a widely known art in the field of computer vision used for the task of estimating rotation and translation between two consecutive time instants. The RANSAC scheme used for outlier rejection incorporates a constant threshold for selecting inliers. The selection of an optimum number of inliers dispersed over the entire image is very important for accurate pose estimation and is decided on the basis of inlier threshold. In this paper, the threshold for inlier classification is adapted with the help of fuzzy logic scheme and varies with the data dynamics. The fuzzy logic is designed with an assumption about the maximum possible camera rotation that can be observed between consequent frames. The proposed methodology has been applied on KITTI dataset, and a comparison has been laid forth between adaptive RANSAC with and without using fuzzy logic with an aim of imparting flexibility to visual odometry algorithm. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-7895-8_23 | CVIP |
Field | DocType | Citations |
Visual odometry,Computer science,RANSAC,Fuzzy logic,Outlier,Algorithm,Pose,Data dynamics | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rahul Mahajan | 1 | 0 | 0.34 |
| P. Vivekananda Shanmuganathan | 2 | 0 | 0.34 |
| Vinod Karar | 3 | 0 | 0.34 |
| Shashi Poddar | 4 | 6 | 3.25 |