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Structure from motion algorithms have an inherent limitation that thereconstruction can only be determined up to the unknown scale factor. Modernmobile devices are equipped with an inertial measurement unit (IMU), which canbe used for estimating the scale of the reconstruction. We propose a methodthat recovers the metric scale given inertial measurements and camera poses. Inthe process, we also perform a temporal and spatial alignment of the camera andthe IMU. Therefore, our solution can be easily combined with any existingvisual reconstruction software. The method can cope with noisy camera poseestimates, typically caused by motion blur or rolling shutter artifacts, viautilizing a Rauch-Tung-Striebel (RTS) smoother. Furthermore, the scaleestimation is performed in the frequency domain, which provides more robustnessto inaccurate sensor time stamps and noisy IMU samples than the previously usedtime domain representation. In contrast to previous methods, our approach hasno parameters that need to be tuned for achieving a good performance. In theexperiments, we show that the algorithm outperforms the state-of-the-art inboth accuracy and convergence speed of the scale estimate. The accuracy of thescale is around $1\%$ from the ground truth depending on the recording. We alsodemonstrate that our method can improve the scale accuracy of the ProjectTango's build-in motion tracking.

Inertial-Based Scale Estimation for Structure from Motion on Mobile Devices