Probabilistic Combination of Noisy Points and Planes for RGB-D Odometry

Pedro F. Proença; Yang Gao

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arXiv · 1705.06516

Probabilistic Combination of Noisy Points and Planes for RGB-D Odometry

Pedro F. Proença·Yang Gao

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Abstract

This work proposes a visual odometry method that combines points and plane primitives, extracted from a noisy depth camera. Depth measurement uncertainty is modelled and propagated through the extraction of geometric primitives to the frame-to-frame motion estimation, where pose is optimized by weighting the residuals of 3D point and planes matches, according to their uncertainties. Results on an RGB-D dataset show that the combination of points and planes, through the proposed method, is able to perform well in poorly textured environments, where point-based odometry is bound to fail.

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Pedro F. Proença, Yang Gao. 2017-05-18. Probabilistic Combination of Noisy Points and Planes for RGB-D Odometry. https://arxiv.org/abs/1705.06516

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