Effective and Efficient Video Summarization Approach for Mobile Devices
Dublin Core
Title
Effective and Efficient Video Summarization Approach for Mobile Devices
Subject
Video Summarization
Key Frame Extraction
Video Skimming
Visual Attention Model
Mobile Computing
Computer Vision
Description
in the context of mobile computing and multimedia processing, video summarization plays an important role for video browsing, streaming, indexing and storing. In this paper, an effective and efficient video summarization approach for mobile devices is proposed. The goal of this approach is to generate a video summary (static and dynamic) based on Visual Attention Model (VAM) and new Fast Directional Motion Intensity Estimation (FDMIE) algorithm for mobile devices. The VAM is based on how to simulate the Human Vision System (HVS) to extract the salient areas that have more attention values from video contents. The evaluation results demonstrate that, the effectiveness rate up to 87% with respect to the manually generated summary and the state of the art approaches. Moreover, the efficiency of the proposed approach makes it suitable for online and mobile applications.
Creator
Farouk, Hesham
ElDahshan, Kamal
Abozeid, Amr Abd Elawed
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 10 No. 1 (2016); pp. 19-26
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2016-01-18
Rights
Copyright (c) 2017 Hesham Farouk, Kamal ElDahshan, Amr Abd Elawed Abozeid
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Hesham Farouk, Kamal ElDahshan and Amr Abozeid Abd Elawed, Effective and Efficient Video Summarization Approach for Mobile Devices, International Association of Online Engineering (IAOE), Vienna, Austria, 2016, accessed November 6, 2024, https://igi.indrastra.com/items/show/1156