Deepvio: Self-supervised deep learning of monocular visual inertial odometry using 3d geometric constraints
This paper presents an self-supervised deep learning network for monocular visual inertial
odometry (named DeepVIO). DeepVIO provides absolute trajectory estimation by directly
merging 2D optical flow feature (OFF) and Inertial Measurement Unit (IMU) data.
Specifically, it firstly estimates the depth and dense 3D point cloud of each scene by using
stereo sequences, and then obtains 3D geometric constraints including 3D optical flow and
6-DoF pose as supervisory signals. Note that such 3D optical flow shows robustness and …
odometry (named DeepVIO). DeepVIO provides absolute trajectory estimation by directly
merging 2D optical flow feature (OFF) and Inertial Measurement Unit (IMU) data.
Specifically, it firstly estimates the depth and dense 3D point cloud of each scene by using
stereo sequences, and then obtains 3D geometric constraints including 3D optical flow and
6-DoF pose as supervisory signals. Note that such 3D optical flow shows robustness and …
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