An efficient iterative pose estimation method was proposed to improve the accuracy and robustness of monocular vision measurement systems. By using homogeneous coordinates,it avoids the limit of existing algorithms on the selection of reference points for a paraperspective camera model. First, a method to compute the pose of an object under the paraperspective camera model was researched using homogeneous coordinates, and its geometric meaning was expatiated in detail. Then, this method was used to estimate the pose of an object in an iterative way under the full perspective camera model with high precision. Simulation results indicate that the proposed method improves the accuracy, speed and robustness of the paraperspective camera model based iterative pose estimation. Real measurement results show that the translation measurement precision and rotation measurement precision of the proposed method are better than 0.1 mm and 0.1°,respectively,and it can satisfy the requirements of various vision detection systems.Furthermore, the accuracy of the proposed method can be improved further by using the land mark point method and sub-pixel feature locating tech-niques.夏军营(1983-)，男，河南驻马店人，博士研究生，2004年、2006年于国防科学技术大学分别获得学士、硕士学位，主要从事视觉测量方面的研究。