Semmo, Amir; Döllner, Jürgen
Expressive Poster Session
We present a novel technique for oil paint filtering that uses color palettes for colorization. First, dominant feature-aware colors are derived from the input image via entropy-based metrics. Seed pixels are then determined and propagated to the remaining pixels by adopting the optimization framework of Levin et al.  for feature-aware colorization. Finally, the quantized output is combined with flow-based highlights and contour lines to simulate paint texture. Our technique leads to homogeneous outputs in the color domain and enables interactive control over color definitions.