· 2014
SVO: Fast semi-direct monocular visual odometry
- 2,105citations
- 2014year
Short summary
A new semi-direct visual odometry algorithm, SVO, achieves faster and more precise motion estimation by directly using pixel intensities, eliminating costly feature extraction and matching.
AI-generated from the title and abstract; the full text is not read.
Key points
- SVO uses a semi-direct approach that operates directly on pixel intensities for motion estimation.
- This method eliminates the need for costly feature extraction and robust matching techniques.
- It achieves subpixel precision and high frame rates (55 FPS onboard, >300 FPS on laptop).
- A probabilistic mapping method explicitly models outliers for more reliable 3D point estimation.
AI-generated from the title and abstract; the full text is not read.
Abstract
We propose a semi-direct monocular visual odometry algorithm that is precise, robust, and faster than current state-of-the-art methods. The semi-direct approach eliminates the need of costly feature extraction and robust matching techniques for motion estimation. Our algorithm operates directly on pixel intensities, which results in subpixel precision at high frame-rates. A probabilistic mapping method that explicitly models outlier measurements is used to estimate 3D points, which results in fewer outliers and more reliable points. Precise and high frame-rate motion estimation brings increased robustness in scenes of little, repetitive, and high-frequency texture. The algorithm is applied to micro-aerial-vehicle state-estimation in GPS-denied environments and runs at 55 frames per second on the onboard embedded computer and at more than 300 frames per second on a consumer laptop. We call our approach SVO (Semi-direct Visual Odometry) and release our implementation as open-source software.
The authors' abstract, as published at the source., 2014 · DOI ↗
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Field: Aerospace Engineering
Aerospace EngineeringEngineering