Open AccessVideo Summarization using Keyframe Extraction Methods
Author(s) -
Ajay Mushan,
Prof. Pujashree Vidap
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b4043.079220
Subject(s) - automatic summarization , computer science , convolutional neural network , redundancy (engineering) , video compression picture types , artificial intelligence , video processing , multiview video coding , search engine indexing , video tracking , frame (networking) , computer vision , uncompressed video , video post processing , smacker video , feature extraction , telecommunications , operating system
Video summarization plays an important role in too many fields, such as video indexing, video browsing, video compression, video analyzing and so on. One of the fundamental units in the video structure analysis is the keyframe extraction, Keyframe provides meaningful frames from the video. The keyframe consists of the meaningful frame from the videos which help for video summarization. In this proposed model, we presented an approach that is based on Convolutional Neural Network, keyframe extraction from videos and static video summarization. First, the video should be converted to frames. Then we perform redundancy elimination techniques to reduce the redundancy from frames. Then extract the keyframes from video by using the Convolutional Neural Network(CNN) model. From the extracted keyframe, we form a video summarization.