Combining color and shape descriptors for 3D model retrieval

Nowadays many three dimensional models feature color information together with the shape description. However current content-based retrieval schemes for 3D models are based on shape information only and ignore color clues. The significance of shape vs. color clues for 3D model retrieval is instead a fundamental issue still almost unexplored at this time. A possible approach is to extend shape-based 3D model retrieval methods of proven effectiveness in order to include color. This work follows such rationale and introduces an extended version of the spin-image descriptor that can account also for color data. The comparison of color descriptors is performed using a novel scheme that allows to recognize as similar also objects with different colors but with the same color distribution over the shape. Shape and color similarity are finally combined together by an algorithm based on fuzzy logic. Experimental results show how the joint use of color and shape data allows to obtain better results than each of the two types of information alone. Comparisons with state-of-the-art content-based retrieval methods for 3D models also show how the proposed scheme outperforms standard solutions on object classes with meaningful color information. ► This paper shows how color data can improve shape-based 3D content-based retrieval. ► This paper proposes an original extension of the spin-image descriptor. ► Objects with the same color distribution over the shape are recognized as similar. ► The color and shape similarity are combined by an algorithm based on fuzzy logic. ► Performances are very good on object classes exhibiting meaningful color data.