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

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