3D model retrieval based on exact visual similarity

Many content-based 3D model retrieval techniques have been proposed in the last decade. Compared with other methods, light field descriptor (LFD) is generally acknowledged as the best model representation. Taking LFD as example, we analyze the disadvantage of the model descriptors based on visual similarity and propose a modified descriptor which preserves the exact geometrical features of the model in each view. Since the modification avoids distortion, the visual differences between dissimilar models are kept. The experimental results show that the improved method outperforms the original LFD approach significantly. According to our analysis and the results, we draw a conclusion about the methods based on 2D visual similarity. Furthermore, a new user-friendly query interface is provided to assist user to draw 2D query from ordinary picture. This method not only makes retrieval process efficient but also gets more accurate results than other methods proposed before.