Cameras and gravity: Estimating planar object orientation

Abstract

Photography on a mobile camera provides access to additional sensors. In this paper, we estimate the absolute orientation of a planar object with respect to the ground, which can be a valuable prior for many vision tasks. To find the planar object orientation, our novel algorithm combines information from a gravity sensor with a planar homography that matches a region of an image to a training image (e.g., of a company logo). We demonstrate our approach with an iPhone application that records the gravity direction for each captured image. We find a homography that maps the training image to the test image, and propose a novel homography decomposition to extract the rotation matrix. We believe this is the first paper to estimate absolute planar object orientation by combining the inertial sensor information with vision algorithms. Experiments show that our proposed algorithm performs reliably.