An orthogonal iteration pose estimation algorithm based on an incident ray tracking model

Although the pinhole imaging model prevails among current pose estimation algorithms, this idealized model gradually shows its limitation and inaccuracy, especially in harsh environments. In recent years, a few generic imaging models have been proposed to replace the dominant pinhole one. Among them, the camera model, named the incident ray tracking model, has proved to be superior. This model consists of mappings between pixels on the image and straight lines in 3D space. Based on the incident ray ttacking camera model, a pose estimation algorithm, which can be called the perspective-ray-based orthogonal iteration (PROI), is proposed in this paper. The proposed algorithm introduces the popular orthogonal iteration algorithm into the incident ray tracking model. In this method, the object space collinearity error is expressed by a more accurate perspective ray instead of the traditional line of sight. The orthogonal rotation matrices are computed by an iterative algorithm and the iterative initial value is given in a weak perspective model. Experiment results on the pose estimation with better accuracy and efficiency by PROI have shown the superiority of the proposed method compared with the best currently employed optimization algorithms.