Publication: SVO: fast semi-direct monocular visual odometry
SVO: fast semi-direct monocular visual odometry
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Forster, C., Pizzoli, M., & Scaramuzza, D. (2014). SVO: fast semi-direct monocular visual odometry. Proceedings of the IEEE International Conference on Robotics and Automation, 15–22. https://doi.org/10.1109/ICRA.2014.6906584
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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. P
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Forster, C., Pizzoli, M., & Scaramuzza, D. (2014). SVO: fast semi-direct monocular visual odometry. Proceedings of the IEEE International Conference on Robotics and Automation, 15–22. https://doi.org/10.1109/ICRA.2014.6906584