Image-based quiz generation from news video archives based on principal object
Masanori Sano, Nobuyuki Yagi, Norio Katayama, Shin’ichi Satoh · 2008
This paper describes our attempt to generate quizzes automatically from news programs, as novel method for content creation. Of the many types of possible quizzes we focus on the format of a multiple-choice quiz with accompanying images. To begin, we worked on formulating the engineering problem of quiz generation - selection of images suitable for a quiz, selection of text that explains the image, and the generation of alternative choices that are similar but different by selecting from subtitles. All the approaches were designed based on principal object in the image and text. As the suitable image for the quiz, an image which has a clear subject - we defined it as spotlight-image - is introduced. As for generation of the similar but different choices, categorizing the subject into person or other can make the correspondence between images and sentence much clear, and then appropriate choices are generated. By introducing these techniques, the accuracy has risen (35.7% up) and the effectiveness of our proposed method were confirmed.