A processor implemented method comprising: capturing a reference point cloud and a template point cloud; and characterized by automatically performing rigid registration of the reference point cloud and the template point cloud by: embedding a shape-based similarity constraint into a Gravitational Approach GA, wherein in the Gravitational Approach, the template point cloud moves towards the reference point cloud under the influence of a total force of attraction as induced by the reference point cloud, by constraining the force of attraction on each point of the template point cloud from each point of the reference point cloud with a measurement of local shape similarity, wherein curvature is used for representation of shape in the local shape similarity; iteratively performing: obtaining the total force applied on all points of the template point cloud by all points of the reference point cloud; computing translation of the template point cloud based on the obtained total force to obtain new position of the template point cloud with respect to the reference point cloud; estimating rotation required for the rigid registration based on the new position of each point of the template point cloud; and estimating scaling required for the rigid registration based on a ratio of eigenvalues of co-variance matrices associated with the reference point cloud and the template point cloud. capturing a reference point cloud and a template point cloud; and characterized by automatically performing rigid registration of the reference point cloud and the template point cloud by: embedding a shape-based similarity constraint into a Gravitational Approach GA, wherein in the Gravitational Approach, the template point cloud moves towards the reference point cloud under the influence of a total force of attraction as induced by the reference point cloud, by constraining the force of attraction on each point of the template point cloud from each point of the reference point cloud with a measurement of local shape similarity, wherein curvature is used for representation of shape in the local shape similarity; iteratively performing: obtaining the total force applied on all points of the template point cloud by all points of the reference point cloud; computing translation of the template point cloud based on the obtained total force to obtain new position of the template point cloud with respect to the reference point cloud; estimating rotation required for the rigid registration based on the new position of each point of the template point cloud; and estimating scaling required for the rigid registration based on a ratio of eigenvalues of co-variance matrices associated with the reference point cloud and the template point cloud. embedding a shape-based similarity constraint into a Gravitational Approach GA, wherein in the Gravitational Approach, the template point cloud moves towards the reference point cloud under the influence of a total force of attraction as induced by the reference point cloud, by constraining the force of attraction on each point of the template point cloud from each point of the reference point cloud with a measurement of local shape similarity, wherein curvature is used for representation of shape in the local shape similarity; iteratively performing: obtaining the total force applied on all points of the template point cloud by all points of the reference point cloud; computing translation of the template point cloud based on the obtained total force to obtain new position of the template point cloud with respect to the reference point cloud; estimating rotation required for the rigid registration based on the new position of each point of the template point cloud; and estimating scaling required for the rigid registration based on a ratio of eigenvalues of co-variance matrices associated with the reference point cloud and the template point cloud. obtaining the total force applied on all points of the template point cloud by all points of the reference point cloud; computing translation of the template point cloud based on the obtained total force to obtain new position of the template point cloud with respect to the reference point cloud; estimating rotation required for the rigid registration based on the new position of each point of the template point cloud; and estimating scaling required for the rigid registration based on a ratio of eigenvalues of co-variance matrices associated with the reference point cloud and the template point cloud.