Paper Info
Title
Content-based network resource allocation for real time remote laboratory applications
Abstract
This paper presents a practical solution to make remote laboratories a realizable dream. A remote laboratory is an online laboratory where students can get first-hand experience of engineering labs via Internet. Video transmission can provide hands on experience to the user but the transmission channel or networks typically have variable and low bandwidth that poses a tough constraint for such implementation. This work presents a practical solution to such problems by adaptively transmitting the best available quality of laboratory videos to the user depending on network bandwidth. The concept behind our work is that not all objects or frames of the video have equal importance, and thus bandwidth reduction can be accomplished by intelligently transmitting important parts at relatively higher resolution. A localized Time adaptive mean of Gaussian (L-TAMOG) approach is used to search for moving objects which are then allocated network resources dynamically according to the varying network bandwidth variations. Adaptive motion compensated wavelet-based encoding is used to achieve scalability and high compression. The proposed system tracks the network bandwidth and delivers optimally the most important contents of video to the student. Experimental results over several remote laboratory sequences show the efficiency of the proposed framework.
Year
DOI
Venue
2010
10.1007/s11760-009-0116-5
Signal, Image and Video Processing
Keywords
DocType
Volume
multimedia systems · l-tamog-based image segmentation · video transmission · interactive lab · scalable coding · adaptive network resource allocation,resource allocation,image segmentation,real time,local time
Journal
4
Issue
ISSN
Citations 
2
1863-1711
3
PageRank 
References 
Authors
0.42
8
3
Name
Order
Citations
PageRank
Ankush Mittal129040.34
Amit Pande226924.58
Praveen Kumar3645.99