Pose estimation for one-dimensional object with general motion

Jinbo Liu; Ge Song; Xiaohu Zhang

doi:10.1117/12.2069782

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24 November 2014 Pose estimation for one-dimensional object with general motion

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93010I (2014) https://doi.org/10.1117/12.2069782
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

Our primary interest is in real-time one-dimensional object’s pose estimation. In this paper, a method to estimate general motion one-dimensional object’s pose, that is, the position and attitude parameters, using a single camera is proposed. Centroid-movement is necessarily continuous and orderly in temporal space, which means it follows at least approximately certain motion law in a short period of time. Therefore, the centroid trajectory in camera frame can be described as a combination of temporal polynomials. Two endpoints on one-dimensional object, A and B, at each time are projected on the corresponding image plane. With the relationship between A, B and centroid C, we can obtain a linear equation system related to the temporal polynomials’ coefficients, in which the camera has been calibrated and the image coordinates of A and B are known. Then in the cases that object moves continuous in natural temporal space within the view of a stationary camera, the position of endpoints on the one-dimensional object can be located and also the attitude can be estimated using two end points. Moreover the position of any other point aligned on one-dimensional object can also be solved. Scene information is not needed in the proposed method. If the distance between the endpoints is not known, a scale factor between the object’s real positions and the estimated results will exist. In order to improve the algorithm’s performance from accuracy and robustness, we derive a pain of linear and optimal algorithms. Simulations’ and experiments’ results show that the method is valid and robust with respect to various Gaussian noise levels. The paper’s work contributes to making self-calibration algorithms using one-dimensional objects applicable to practice. Furthermore, the method can also be used to estimate the pose and shape parameters of parallelogram, prism or cylinder objects.

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Jinbo Liu, Ge Song, and Xiaohu Zhang "Pose estimation for one-dimensional object with general motion", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010I (24 November 2014); https://doi.org/10.1117/12.2069782

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