Linear Pose Estimation Algorithm Based on Quaternion

Abstract

Abstract.A novel linear camera pose estimation algorithm is presented using known 3D to 2D line correspondences and point correspondences. The rotation parameters are represented by unit quaternion. For n (n>=4) correspondences, we establish an equation system with 2n quadratic equations in thirteen variables and apply the "relinearization" method to obtain the rotation parameters and translation parameters simultaneously. We compare our algorithm with Ansar's NLL algorithm for line correspondences by some synthetic experiments. Our algorithm performs better on the aspect of running time and accuracy of determined pose parameters. Some real experiments are produced by 1 point-3 lines, 2 points-2 lines, 3 points-1 line correspondences. The projection of a 3D model is applied to estimate the performance of our algorithm.

An Accurate and Efficient Quaternion-Based Visualization Approach to 2D/3D Vector Data for the Mobile Augmented Reality Map

“…Quaternions have the ability to express precise spatial relationships and geometry. For 3D to 2D line and point correspondences, a novel linear pose estimation based on quaternion is provided, which improves the accuracy and running time of the camera pose estimation algorithm [77]. For visualization of indoor navigation, a quaternion-based precise 3D modeling method for path networks is proposed to automatically generate highly recognizable 3D models [78].…”