3D pose estimation from an n-degree planar curved feature in two perspective views

3D pose estimation from 2D image data is a fundamental problem in computer vision. In this paper, a pose estimation method based on planar-curved features on the surface of an object is presented. This method is linear and generally applicable to any high degree (/spl ges/2) planar-curved features. So far, the 3D pose estimation methods presented in the literature are based either on point/line features or quadratic-curved features. The methods based on point and line features have to solve the correspondence problem. As there are so many edge points and line segments in an image, to establish the correspondences of these primitives between images is very difficult and time consuming in practice. The methods based on quadratic-curved features have to solve non-linear equations which normally result in many pseudo solutions. To eliminate these extra solutions and choose the right solution is very difficult. Our method is advantageous in these aspects.