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arXiv · 2404.17251

Camera Motion Estimation from RGB-D-Inertial Scene Flow

Samuel Cerezo·Javier Civera
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Abstract

In this paper, we introduce a novel formulation for camera motion estimation that integrates RGB-D images and inertial data through scene flow. Our goal is to accurately estimate the camera motion in a rigid 3D environment, along with the state of the inertial measurement unit (IMU). Our proposed method offers the flexibility to operate as a multi-frame optimization or to marginalize older data, thus effectively utilizing past measurements. To assess the performance of our method, we conducted evaluations using both synthetic data from the ICL-NUIM dataset and real data sequences from the OpenLORIS-Scene dataset. Our results show that the fusion of these two sensors enhances the accuracy of camera motion estimation when compared to using only visual data.

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Samuel Cerezo, Javier Civera. 2024-04-26. Camera Motion Estimation from RGB-D-Inertial Scene Flow. https://arxiv.org/abs/2404.17251

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