A solution for camera tracking based on coplanar circles from industrial objects was presented. Firstly, a coordinate system for an object frame was constructed based on coplanar circles. Then, the Extended Kalman Filter(EKF) was exploited to predict camera pose to restrict the positions and regions for searching ellipse contours, and the candidate contour points of ellipse were formed by calculating normalized cross coefficient of gradient. With maximum likelihood estimation, a high accurate ellipse was obtained after eliminating outliers from candidate dataset. Finally,the camera pose was estimated using projective theory of conics, and the filter state was updated. Experiments show that the maximum pose deviation of camera tracking is 1.4° for rotation and 3.5 mm for translation, and the tracking rate is 10~12 frame/s.The results can meet the requirement of pose tracking in industrial Augmented Reality(AR).