Abstract

This paper presents a novel solution to the metric reconstruction of objects using any smart device equipped with a camera and an inertial measure- ment unit (IMU). We propose a batch, vision centric approach which only uses the IMU to estimate the metric scale of a scene reconstructed by any algorithm with Structure from Motion like (SfM) output. IMUs have a rich history of being com- bined with monocular vision for robotic navigation and odometry applications. These IMUs require sophisticated and quite expensive hardware rigs to perform well. IMUs in smart devices, however, are chosen for enhancing interactivity - a task which is more forgiving to noise in the measurements. We anticipate, how- ever, that the ubiquity of these “noisy” IMUs makes them increasingly useful in modern computer vision algorithms. Indeed, we show in this work how an IMU from a smart device can help a face tracker to measure pupil distance, and an SfM algorithm to measure the metric size of objects. We also identify motions that produce better results, and develop a heuristic for estimating, in real-time, when enough data has been collected for an accurate scale estimation.