By generating reproducible brush strokes of Chinese ink painting, we propose an image-based tool for lively displaying real painting process of Chinese ink painting. Contrasted with previous work where the brush trajectory is explicitly specified as manual input, we automatically extract this trajectory from the outlines of the shapes to paint and model the brush footprints; first complex shape of an input image is decomposed into brush strokes. Second, we estimate the brush trajectory with shape outline and build a brush footprint model to measure the quality of the trajectory constrained by the variation along a stroke of the painting process parameters, such as location, size, and orientation of the footprints. Finally, with our real-time rendering model, the estimated trajectories are dynamically rendered into brush strokes by mapping footprint textures sampled from the input images. It is particularly useful for analysis and appreciation of Chinese ink painting, as well as for art practice and education. © 2012 Science China Press and Springer-Verlag Berlin Heidelberg.