In this paper, we incorporate a set of principles that originated in cognitive psychology into the design of 3-D shape analysis and retrieval systems. Based on the "visual salience-guided mesh decomposition" scheme we proposed previously, a 3-D shape represented in mesh form is first broken into parts such that human visual perception of the parts can be appropriately mimicked. Next, the decomposed parts are individually analyzed and quantified according to the properties of visual salience. To establish the indices of 3-D meshes for the subsequent retrieval process, spherical parameterization is adopted to map the decomposed parts onto the surface of a unit sphere. In this way, the degree of similarity between a query provided by a user and models in the database can be calculated. The experiment results show that the retrieval performance of the proposed scheme is indeed efficient and powerful.