Key-Lectures: Keyframes Extraction in Video Lectures

Abstract

In this multimedia era, the education system is going to adopt the video technologies, i.e., video lectures, e-class room, virtual classroom, etc. In order to manage the content of the audiovisual lectures, we require a huge storage space and more time to access. Such content may not be accessed in real time. In this work, we propose a novel key frame extraction technique to summarize the video lectures so that a reader can get the critical information in real time. The qualitative, as well as quantitative measurement, is done for comparing the performances of our proposed model and state-of-the-art models. Experimental results on two benchmark datasets with various duration of videos indicate that our key-lecture technique outperforms the existing previous models with the best F-measure and Recall.