Abstract-This paper addresses learning-based characterization of fine art painting styles. The research has the potential to provide a powerful tool to art historians for studying connections among artists or periods in the history of art. Depending on specific applications, paintings can be categorized in different ways. In this paper, we focus on comparing the painting styles of artists. To profile the style of an artist, a mixture of stochastic models is estimated using training images.
In REF , Li et al. have addressed the learning-based characterization of fine art painting styles.
Studying digital imagery of ancient paintings by mixtures of stochastic models
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Computer Science Medicine