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Monocular visual odometry based on optical flow and feature matching
- Source :
- 2017 29th Chinese Control And Decision Conference (CCDC).
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
Abstract
- To solve the problem of real-time precise localization in CPS-denied places, a monocular visual odometry method based on optical flow tracking and feature matching is proposed. To speed up traditional pose estimation algorithm, the image sequences are classified into key frames and non-key frames. The conventional pipeline of feature detection and matching is utilized to process key frames, while utilizing Lucas Kanade optical flow to track the correspondences in non-key frames. To improve the robustness of the visual odometry method, a RANSAC-based outlier rejection scheme is applied in the phase of pose estimation. Moreover, a Kalman Filter based on the dynamic equation is designed to optimize the pose estimation. Experimental results demonstrate that proposed method can acquire the high accuracy of feature matching, while highlighting the real-time performance of optical flow tracking, which can meet the needs of real-time accurate localization in cities.
- Subjects :
- 0209 industrial biotechnology
business.industry
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Optical flow
Pattern recognition
02 engineering and technology
Kalman filter
RANSAC
020901 industrial engineering & automation
Lucas–Kanade method
Robustness (computer science)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Computer vision
Artificial intelligence
Visual odometry
business
Pose
Mathematics
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 29th Chinese Control And Decision Conference (CCDC)
- Accession number :
- edsair.doi...........07026d1f9cde3730fb23f2cc9e2e35d4