Kurzhals, KunoStoll, MichaelBruhn, AndrésWeiskopf, DanielHolger Winnemoeller and Lyn Bartram2017-10-182017-10-182017978-1-4503-5080-81816-0859https://doi.org/10.1145/3092912.3092914https://diglib.eg.org:443/handle/10.2312/cae2017a01The depiction of motion in static representations has a long tradition in art and science alike. Often, motion is depicted by spatiotemporal summarizations that try to preserve as much information of the original dynamic content as possible. In our approach to depicting motion, we remove the spatial constraints and generate new content steered by the temporal changes in motion. Applying particle steering in combination with the dynamic color palette of the video content, we can create a wide range of different image styles. With recorded videos, or by live interaction with a webcam, one can influence the resulting image. We provide a set of intuitive parameters to affect the style of the result, the final image content depends on the video input. Based on a collection of results gathered from test users, we discuss example styles that can be achieved with FlowBrush. In general, our approach provides an open sandbox for creative people to generate aesthetic images from any video content they apply.Computing methodologies Image processingVideo summarizationOptical flowvideobased graphicsartistic toolparticle steeringFlowBrush: Optical Flow Art10.1145/3092912.3092914