For recognition of three-dimensional (3D) shapes and measurement of 3D positions of objects it is important for a vision system to be able to measure the 3D data of dense points in the environment. One approach is to measure the distance on the basis of the triangulation principle from the disparity of two images. However, this binocular vision method has difficulty in finding a correspondence of features between two images. This correspondence problem can be solved geometrically by adding another camera, i.e. by trinocular vision. This paper presents the principles and implementation details of trinocular vision. On the basis of the proposed method, we carried out several experiments, from which we found that many correct correspondences could be established, even for images of a complex scene, by only the geometrical constraint of trinocular vision. However, when there are dense points in the image, multiple candidate points are found and a unique correspondence cannot be established. Two approaches to solve this problem are discussed in this paper.