Invariant feature representations for 3D objects are one of the basic needs in 3D object retrieval and classification. One tool to obtain rotation invariance are Spherical Harmonics, which are an orthogonal basis for the functions defined on the 2-sphere. We show that the irreducible representations of the 3D rotation group, which acts on the Spherical Harmonic representation, can give more information about the considered object than the Spherical Harmonic expansion itself. We embed our new feature extraction methods in the group integration framework and show experiments for 3D-surface data (Princeton Shape Benchmark).