DoCam: Depth Sensing with an Optical Image Stabilization Supported RGB Camera

Optical image stabilizers (OIS) are widely used in digital cameras to counteract motion blur caused by camera shakes in capturing videos and photos. In this paper, we sought to expand the applicability of the lens-shift OIS technology for metric depth estimation, i.e., let a RGB camera to achieve the similar function of a time-of-flight (ToF) camera. Instead of having to move the entire camera for depth estimation, we propose DoCam, which controls the lens motion in the OIS module to achieve 3D reconstruction. After controlling the lens motion by altering the MEMS gyroscopes readings through acoustic injection, we improve the traditional bundle adjustment algorithm by establishing additional constraints from the linearity of the lens control model for high-precision camera pose estimation. Then, we elaborate a dense depth reconstruction algorithm to compute depth maps at real-world scale from multiple captures with micro lens motion (i.e., ≤ 3 mm). Extensive experiments demonstrate that our proposed DoCam can enable a 2D color camera to estimate high-accuracy depth information of the captured scene by means of controlling lens motion in the OIS. DoCam is suitable for a variety of applications that require depth information of the scenes, especially when only a single color camera is available and located at a fixed position.

In Proceedings of the 28th Annual International Conference on Mobile Computing and Networking