Histogram of Exclamation Marks and Its Application for Comics Analysis
This paper proposes a histogram formed by counting the number of exclamation marks in comic books for comics analysis. Exclamation marks in comic books are used for expressing character's emotion and are depicted in frequently excited scenes. Also they are easy to detect from different comic books written by various authors. Hence we represent each comic book by its distribution of exclamation marks as a histogram and use such histogram for topic change detection and visualization of relationships between comic books. Experimental results on real comic books show that our bold approach has potential for approximating of contents of comic books by using the proposed histograms.
FACE DETECTION FOR COMIC IMAGES WITH DEFORMABLE PART MODEL
Comic images include several kinds of picture elements, such as lines, dots, characters and sound effects. Therefore, they form quite complex structure compared with natural images. We have been trying to improve the convenience of e-comics by retrieving metadata elements, such as names of characters and positions of the characters. To extract characters from comic images, a method detecting characters’ face using the Histograms of Oriented Gradients (HOG) features and discriminating them has been proposed. However, this method does not provide stable face detection. In this paper, Deformable Part Model (DMP), which is originally proposed to detect natural objects, is applied to comic images in order to improve accuracy of face detection. As a consequence, it is turned out that we can obtain 85.5 % detection rate for unknown images. Thus, DPM can be regarded an effective method to detect objects in comic images.
Enhancing the Accessibility for All of Digital Comic Books
Comic books are very popular all over the world, among the readers of all ages. They are even sometimes referred to as the ninth art. In our increasingly digital world, comics still remain creature of print and paper and ink. Despite its convenience in many aspects, this media does not completely fulfil the needs of a large segment of public such as mobile users, motor-impaired people, and low-sighted people. In this paper, we explore how a digital version of comic books can be optimally accessed using a computer based interface. Among the supported reading modes, an automated mode provides a segmentation-based detection of panels and their display in the relevant reading order. This enables accessibility with minimal user interaction and maximal image size. An open-source prototype was implemented and validated in different operational contexts such as PC desktop, PC laptop, a PC controlled through voice, remote-controlled TV and mobile devices.