NDLI: Progressive Dictionary Learning with Hierarchical Structure for Scalable Video Coding

Content Provider	IEEE Xplore Digital Library
Author	Xin Tang Wenrui Dai Hongkai Xiong
Copyright Year	2015
Description	Author affiliation: Dept. of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China (Xin Tang; Wenrui Dai; Hongkai Xiong)
Abstract	To enable learning-based video coding for transmission over heterogenous networks, this paper proposes a scalable video coding framework by progressive dictionary learning. With the hierarchical B-picture prediction structure, the inter-predicted frames would be reconstructed in terms of the spatio-temporal dictionary in a successive sense. Within the progressive dictionary learning, the training set is enriched with the samples from the reconstructed frames in the coarse layer. Through minimizing the expected cost, the stochastic gradient descent is leveraged to update the dictionary for practical coding. It is demonstrated that the learning-based scalable framework can effectively guarantee the consistency of motion trajectory with the well-designed spatio-temporal dictionary.
Starting Page	472
Ending Page	472
File Size	100723
Page Count	1
File Format	PDF
ISBN	9781479984305
ISSN	10680314
DOI	10.1109/DCC.2015.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Training Encoding Video coding Data compression Electronic mail Trajectory
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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