Egomotion Estimation Using Assorted Features |
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Authors: | Vivek Pradeep Jongwoo Lim |
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Affiliation: | 1.Applied Sciences Group,Microsoft Corporation,Redmond,USA;2.Honda Research Institute,Mountain View,USA |
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Abstract: | We propose a novel minimal solver for recovering camera motion across two views of a calibrated stereo rig. The algorithm
can handle any assorted combination of point and line features across the four images and facilitates a visual odometry pipeline
that is enhanced by well-localized and reliably-tracked line features while retaining the well-known advantages of point features.
The mathematical framework of our method is based on trifocal tensor geometry and a quaternion representation of rotation
matrices. A simple polynomial system is developed from which camera motion parameters may be extracted more robustly in the
presence of severe noise, as compared to the conventionally employed direct linear/subspace solutions. This is demonstrated
with extensive experiments and comparisons against the 3-point and line-sfm algorithms. |
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