Image and video based painterly animation

We present techniques for transforming images and videos into painterly animations depicting different artistic styles. Our techniques rely on image and video analysis to compute appearance and motion properties. We also determine and apply motion information from different (user-specified) sources to static and moving images. These properties that encode spatio-temporal variations are then used to render (or paint) effects of selected styles to generate images and videos with a painted look. Painterly animations are generated using a mesh of brush stroke objects with dynamic spatio-temporal properties. Styles govern the behavior of these brush strokes as well as their rendering to a virtual canvas. We present methods for modifying the properties of these brush strokes according to the input images, videos, or motions. Brush stroke color, length, orientation, opacity, and motion are determined and the brush strokes are regenerated to fill the canvas as the video changes. All brush stroke properties are temporally constrained to guarantee temporally coherent non-photorealistic animations.