Bodhisattva head images modeling style recognition of Dazu Rock Carvings based on deep convolutional network

As the only World Culture Heritage in Chongqing, the Dazu Rock Carvings have been suffering from natural environment erosion for almost one thousand years, so the inpainting of these carvings is desired. In order to reduce the inpainting risk and keep the carvings' original appearance, it is necessary to introduce digital image processing techniques to perform virtual inpainting initially. The key step in exemplar-based inpainting algorithm is to search for the most similar patch. Efficient modeling style recognition is therefore the basis of the carvings' inpainting. Focusing on Bodhisattva head images, this paper proposes a two-step recognition method for their modeling style: feature extraction utilizing VGGNet1 and clustering with K-means algorithm. The proposed method obtains promising results compared with 5 classical feature extraction algorithms. According to experiment results, combining both art archaeology and image analysis, we conclude: (1) the modeling style is similar for the statues in the same cave or region; and the modeling style of the statues on the same subject is also similar, even though they are in different caves or regions; (2) the name of Beishan No 180 should be “Cave of Eleven Incarnations of Avalokitesvara” instead of the previous “Cave of Thirteen Incarnations of Avalokitesvara”. It is because the modeling style of two statues behind the major statue is quite different from the others. They were probably carved to substitute the two outmost damaged statues. Our work can be viewed as a reference to solve some art problems. Moreover, as it is efficient to search for similar images by our method, this paper can be as the basis for virtual exemplar-based inpainting of Dazu Rock Carvings in our future work.