Frame Interpolation for Cloud-Based Mobile Video Streaming

Usman, M; He, X; Lam, KM; Xu, M; Bokhari, SMM; Chen, J

Frame Interpolation for Cloud-Based Mobile Video Streaming

Usman, M

He, X

Lam, KM Xu, M

Bokhari, SMM Chen, J

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Multimedia, 2016, 18 (5), pp. 831 - 839
Issue Date:: 2016-05-01

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Field	Value	Language
dc.contributor.author	Usman, M https://orcid.org/0000-0003-2165-4575	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.contributor.author	Lam, KM	en_US
dc.contributor.author	Xu, M https://orcid.org/0000-0001-9581-8849	en_US
dc.contributor.author	Bokhari, SMM	en_US
dc.contributor.author	Chen, J	en_US
dc.date.available	2016-01-20	en_US
dc.date.issued	2016-05-01	en_US
dc.identifier.citation	IEEE Transactions on Multimedia, 2016, 18 (5), pp. 831 - 839	en_US
dc.identifier.issn	1520-9210	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41586
dc.description.abstract	© 2016 IEEE. Cloud-based High Definition (HD) video streaming is becoming popular day by day. On one hand, it is important for both end users and large storage servers to store their huge amount of data at different locations and servers. On the other hand, it is becoming a big challenge for network service providers to provide reliable connectivity to the network users. There have been many studies over cloud-based video streaming for Quality of Experience (QoE) for services like YouTube. Packet losses and bit errors are very common in transmission networks, which affect the user feedback over cloud-based media services. To cover up packet losses and bit errors, Error Concealment (EC) techniques are usually applied at the decoder/receiver side to estimate the lost information. This paper proposes a time-efficient and quality-oriented EC method. The proposed method considers H.265/HEVC based intra-encoded videos for the estimation of whole intra-frame loss. The main emphasis in the proposed approach is the recovery of Motion Vectors (MVs) of a lost frame in real-time. To boost-up the search process for the lost MVs, a bigger block size and searching in parallel are both considered. The simulation results clearly show that our proposed method outperforms the traditional Block Matching Algorithm (BMA) by approximately 2.5 dB and Frame Copy (FC) by up to 12 dB at a packet loss rate of 1%, 3%, and 5% with different Quantization Parameters (QPs). The computational time of the proposed approach outperforms the BMA by approximately 1788 seconds.	en_US
dc.relation.ispartof	IEEE Transactions on Multimedia	en_US
dc.relation.isbasedon	10.1109/TMM.2016.2537200	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Frame Interpolation for Cloud-Based Mobile Video Streaming	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	18	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080106 Image Processing	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	open_access
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	18	en_US

Abstract:

© 2016 IEEE. Cloud-based High Definition (HD) video streaming is becoming popular day by day. On one hand, it is important for both end users and large storage servers to store their huge amount of data at different locations and servers. On the other hand, it is becoming a big challenge for network service providers to provide reliable connectivity to the network users. There have been many studies over cloud-based video streaming for Quality of Experience (QoE) for services like YouTube. Packet losses and bit errors are very common in transmission networks, which affect the user feedback over cloud-based media services. To cover up packet losses and bit errors, Error Concealment (EC) techniques are usually applied at the decoder/receiver side to estimate the lost information. This paper proposes a time-efficient and quality-oriented EC method. The proposed method considers H.265/HEVC based intra-encoded videos for the estimation of whole intra-frame loss. The main emphasis in the proposed approach is the recovery of Motion Vectors (MVs) of a lost frame in real-time. To boost-up the search process for the lost MVs, a bigger block size and searching in parallel are both considered. The simulation results clearly show that our proposed method outperforms the traditional Block Matching Algorithm (BMA) by approximately 2.5 dB and Frame Copy (FC) by up to 12 dB at a packet loss rate of 1%, 3%, and 5% with different Quantization Parameters (QPs). The computational time of the proposed approach outperforms the BMA by approximately 1788 seconds.

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http://hdl.handle.net/10453/41578