Scene Motion Decomposition for Learnable Visual Odometry

Understand

Optical Flow (OF) and depth are commonly used for visual odometry since they provide sufficient information about camera ego-motion in a rigid scene.

• We reformulate the problem of ego-motion estimation as a problem of motion estimation of a 3D-scene with respect to a static camera.
• The entire scene motion can be represented as a combination of motions of its visible points.
• Using OF and depth we estimate a motion of each point in terms of 6DoF and represent results in the form of motion maps, each one addressing single degree of freedom.