Paper Info
Title
Mobile-cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors.
Abstract
Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource-and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.
Year
DOI
Venue
2014
10.3390/s140917112
SENSORS
Keywords
Field
DocType
wireless capsule sensor,video summarization,mobile-cloud computing,energy saving,remote monitoring,implantable sensors
Mobile cloud computing,Histogram,Computer vision,Automatic summarization,Wireless,Computer science,Remote sensing,Redundancy (engineering),Artificial intelligence,Data compression,Channel (digital image),Cloud computing
Journal
Volume
Issue
ISSN
14
9.0
1424-8220
Citations 
PageRank 
References 
19
0.61
54
Authors
3
Name
Order
Citations
PageRank
Irfan Mehmood1311.19
Muhammad Sajjad2632.67
Sung Wook Baik3311.19