Most pose estimation algorithms using a single two-dimensional (2D) image are designed based on totally or partially knowing the correspondence between three-dimensional (3D) and 2D feature points, but few have involved in a correspondenceless case. A camera pose estimation algorithm is proposed by using particle system kinematics in classical mechanics. It can simultaneously decide the correspondence and the camera pose. Besides, by introducing object space collinear error and matching matrix, the proposed algorithm can be used not only in the case when the correspondences of 3D/2D feature points are one to one, but also in the case when the 3D feature points are partially occluded and when there are 2D false feature points in an image. Through experiments and comparison with other algorithms, the result shows that the proposed algorithm can effectively find the correct correspondence and estimate camera pose without increasing computational complexity, and the impact of image noises and 2D false feature points on the algorithm is little.