Extraction of Frame Sequences in the Manga Context

Christian Roggia, Fabio Persia
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引用次数: 1

Abstract

Manga are one of the most popular forms of comics consumed on a global level. Unfortunately, this kind of media was not designed for digital consumption, and consequently its format does not fit well into small areas, such as smartphone screens. In order to cope with this issue, in this paper we propose a novel approach to comics segmentation and sequencing by taking advantage of existing machine learning concepts which are used to generate an artificial intelligence (AI) capable of correctly detecting panels within an image. The regions proposed by the AI are then used to generate a grid that acts as anchor points for a mobile application guiding the reader during navigation and enabling full Manga responsiveness. The developed approach achieves overall better performances in terms of precision and recall, as well as higher fault tolerance than state-of-the-art approaches. The reliability of this method is also considered largely satisfactory for real-world scenarios, so that we are about to finalize an app implementing the method to be spread soon; additionally, future work will be devoted to generalize our approach to all the comics formats.
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漫画语境中帧序列的提取
漫画是全球最受欢迎的漫画形式之一。不幸的是,这种媒体不是为数字消费而设计的,因此它的格式不适合小区域,比如智能手机屏幕。为了解决这个问题,在本文中,我们提出了一种新的漫画分割和排序方法,利用现有的机器学习概念,用于生成能够正确检测图像中的面板的人工智能(AI)。然后,人工智能提出的区域被用来生成一个网格,作为移动应用程序的锚点,在导航过程中指导读者,并实现完整的漫画响应。所开发的方法在精度和召回率方面实现了更好的总体性能,并且比最先进的方法具有更高的容错性。这种方法的可靠性也被认为在现实世界的场景中是令人满意的,所以我们即将完成一款应用程序,实现即将推广的方法;此外,未来的工作将致力于推广我们对所有漫画格式的方法。
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