This paper describes a method to localize objects which are partially buried in an unstructured environment. The objects are limited to surfaces of revolution in the present study. Candidate regions are extracted as convex surface regions from a range data that is obtained by area-based stereo matching. The surface type at each point is determined based on the signs of the maximum and minimum curvatures, which are calculated by fitting a quadric in the local window. For each candidate region, multiple hypotheses for the position and direction of the rotational axis are generated for each object model. Each hypothesis is verified and improved by an iterative method, and the most reliable hypothesis is adopted. The experimental results demonstrate the effectiveness of the proposed method for actual range data.