Tracking 3-D Motion of Dynamic Objects Using Monocular Visual-Inertial Sensing

Abstract

Six degree-of-freedom (6-DoF) visual tracking of dynamic objects is fundamental to a large variety of robotics and augmented reality (AR) applications. A key to this problem is accurate distance measurement of dynamic objects, which is usually obtained via stereo cameras, RGB-D sensors, or LiDARs. In this paper, however, we address the problem using only a monocular camera rigidly mounted with a low-cost inertial measurement unit. This is a light-weight, small-size, and low-cost solution, which is particularly suitable for tracking dynamic objects on drones or on mobile phones. Starting from a generic image-based two-dimensional tracker, we propose a novel method to resolve the object scale ambiguity in monocular vision in a geometric manner based on correlation analysis. This enables accurate metric three-dimensional tracking of arbitrary objects without requiring any prior knowledge about the object shape or size. We discuss the applicability by analyzing the observability condition and degenerated cases for object scale recovery. Simulation and real-world experimental results with ground truth comparison, along with AR application examples, demonstrate the feasibility of the proposed 6-DoF tracking method.