Efficient 6-DoF camera pose tracking with circular edges

Abstract

Camera pose tracking attracts much interest from both academic and industrial communities, of which the methods based on planar markers are easy to be implemented. However, most existing methods need to identify multiple points in the marker images for matching to space points. Then, PnP methods are used to compute the camera poses. If cameras move fast or are far away from the markers, the matching is easy to generate errors. To address these problems, we design circular markers and represent 6D camera pose analytically as concise forms from each marker by projective invariance. Afterwards, the pose is further optimized by a cost function based on a polar-n-direction geometric distance. The proposed method is from imaged circular edges, which makes camera pose tracking more robust to noise, blur and distance from camera to marker than existing methods. Extensive experimental results show that the proposed 6-DoF camera pose tracking method outperforms state-of-the-art methods in terms of noise, blur, and distance from camera to marker. Simultaneously, it efficiently runs at about 100 FPS on a consumer computer.