Efficient Circle-Based Camera Pose Tracking Free of PnP

TL;DR

This paper introduces a novel circle-based camera pose tracking method that eliminates the need for PnP/RANSAC, achieving robust, accurate, and real-time performance using only circle edge detection and analytical pose representation.

Contribution

The paper proposes a new circle marker-based approach that directly computes 6D camera pose analytically and optimizes it without PnP or RANSAC, enhancing robustness and speed.

Findings

Outperforms existing methods in noise, blur, and distance robustness.

Achieves approximately 100 FPS on a consumer CPU.

Eliminates the need for point matching and RANSAC in pose estimation.

Abstract

Camera pose tracking attracts much interest both from academic and industrial communities, of which the methods based on planar markers are easy to be implemented. However, most of the existing methods need to identify multiple points in the marker images for matching to space points. Then, PnP and RANSAC are used to compute the camera pose. If cameras move fast or are far away from markers, matching is easy to generate errors and even RANSAC cannot remove incorrect matching. Then, the result by PnP cannot have good performance. To solve this problem, we design circular markers and represent 6D camera pose analytically and unifiedly as very concise forms from each of the marker by projective invariance. Afterwards, the pose is further optimized by a proposed nonlinear cost function based on a polar-n-direction geometric distance. The method is from imaged circle edges and without PnP/RANSAC, making pose tracking robust and accurate. Experimental results show that the proposed method outperforms the state of the arts in terms of noise, blur, and distance from camera to marker. Simultaneously, it can still run at about 100 FPS on a consumer computer with only CPU.