This paper tackles a particular shape matching problem: given a data base of shapes (described as triangular meshes), we search for all shapes which describe a human. We do so by applying a 3D face detection approach on the mesh which consists of three steps: first, a local symmetry value is computed for each vertex. Then, the symmetry values in a certain neighborhood of each vertex are analyzed for building sharp symmetry lines. Finally, the geometry around each vertex is analyzed to get further facial features like nose and forehead. We tested our approach with several shape data bases (e.g. the Princeton Shape Benchmark) and achieved high rates of correct face detection.