Extracting Descriptive Frames from Informational Videos

Abstract

     Informational videos are becoming increasingly important among all video types. The users spend so much time browsing the informative videos, even if they are not interested in all their topics. Thence, a new method for extracting descriptive frames is presented in this paper that allows users to navigate directly to the topics of their interest in the video. The proposed method consists of three main phases: video preprocessing, video segmentation, and the video separation phase. Firstly, frames are extracted from the videos, resized, and converted to grayscale. Then, the frames are divided into blocks, and the kurtosis moment is calculated for each block. The videos are segmented based on an examination of the differences between the features of the kurtosis moment. Lastly, the informative frames are grouped into a separate video after they are distinguished from the uninformative ones using the clustering technique. The results demonstrated the functional effectiveness of the proposed method. According to the accuracy and F1-Score measures, it has a performance of up to 100%. Moreover, the video is significantly summarized by reducing the duration to less than 1% of its original time.