This paper presents Computational Cartoonist, a comic-style anime summarization system that detects key frame and generates comic layout automatically. In contract to previous studies, we define evaluation criteria based on the correspondence between anime films and original comics to determine whether the result of comic-style summarization is relevant. To detect key frame detection for anime films, the proposed system segments the input video into a series of basic temporal units, and computes frame importance using image characteristics such as motion. Subsequently, comic-style layouts are decided on the basis of pre-defined templates stored in a database. Several results demonstrate the efficiency of our key frame detection over previous methods by evaluating the matching accuracy between key frames and original comic panels.
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