Region-Based Image Transform for Transition Between Object Appearances

We propose a method of region-based image transform to achieve accurate transition between object appearances. A view-transition model (VTM) is one of the statistical methods that learn appearance transition from a sample image dataset of a large number of objects with various appearances. However, the VTM method has a practical problem that the appearance transition cannot be performed accurately if a sufficient number of learning samples is not available in the dataset. To cope with the problem, the proposed method first determines the regions of input and output images whose pixel values mutually affect each other during appearance transition, then transforms iteratively between partial images in the regions. We conducted experiments using actual image datasets. The results show that the proposed method could accurately transform appearances compared with the VTM method.