Abstract
This paper describes a new method for the moving object detection using the IMU sensor and instance image segmentation. In the proposed method, the feature points are extracted by the detector, and the initial fundamental matrix is calculated from the IMU data. Next, the epipolar line is used to classify the extracted feature points. From the background feature point matching, fundamental matrix is calculated iteratively to minimize the error of classification. After the feature point classification, image segmentation is used to enhance the quality of the classification result. The proposed method is implemented and tested with real-world driving videos, and compared with the previous works.
| Original language | English |
|---|---|
| Pages (from-to) | 1049-1059 |
| Number of pages | 11 |
| Journal | International Journal of Precision Engineering and Manufacturing |
| Volume | 22 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2021 Jun |
Bibliographical note
Funding Information:This work was supported by the IT R&D program of MSIT/IITP. [R2020040040, Development of 5G-based 3D spatial scanning device technology for virtual space composition.]
Funding Information:
This work was supported by the IT R&D program of MSIT/IITP. [R2020040040, Development of 5G-based 3D spatial scanning device technology for virtual space composition.]
Publisher Copyright:
© 2021, Korean Society for Precision Engineering.
Keywords
- Deep learning
- Motion estimation
- Moving camera
- Moving object detection
ASJC Scopus subject areas
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering