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Video Content AdaptationQoS by using the tree algorithm

This paper discusses the implementation of a content adaptation framework using the Tree algorithm for optimizing video quality and reducing transcoding overhead. Topics include content adaptation, decision engine, tree algorithm, frame dropping, and coefficient dropping.

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Video Content AdaptationQoS by using the tree algorithm

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  1. Video Content AdaptationQoS by using the tree algorithm 2003. 4. 9. 20022161 Jaepil Han 20022156 Jinho Choo 20022081 Sunwoo Yang

  2. Content • Introduction • Related Theory • Content Adaptation - Framwork - Implementation • The present works • Further works

  3. Introduction(1/2) • The optimal tradeoff point between transcoding overhead(CPU cost) and storage needed for the various pre-processed content variants • Content adaptation involves creating different versions suitable for rendering by mobile devices from some original content such as a web page. • The decision engine will look for the best tradeoff among various parameters in order to reduce the loss of quality in various domains.

  4. Introduction(2/2) • The decision engine will take into account the different types of context such as device capability profile, networking charateristics, user preference, and metadata about the content itself • We’ll implement the engine for bandwidth among networking charateristics. • Study the video content adaptation and implementation it by using the Tree algorithm

  5. Related thoery(1/2) • Trees algorithm - is a connected undirected graph with no simple circuits - particulary useful in computer science for instance, it can be used to construct efficient codes for storing and transmitting data

  6. Related thoery(2/2) - this algorithm is applied to the decision engine for the best tadeoff among various parameters in order to reduce the loss of quality in various domains. for example, frame dropping, coefficient dropping, PSNR, Bandwidth. The Applied Tree algorithm

  7. The content Adaptation (1/5) • Framework

  8. The content Adaptation (2/5) • Frame dropping (FD) • Selection of the skipped frame locations • Based on frame type or perceptual importance of the frames • Consider decoding-independent cases only • The first B, all B, all B&P, P frames dropping • Only a coarse level of target bit rate is achievable

  9. The content Adaptation (3/5) • DCT coefficient dropping (CD) • Meet the target bit rate with a greater granularity • Percentage of rate-reduction to be achieved like a CD (10%) • Minimize the overall distortion by optimally allocating the number of dropped coefficients among blocks • find breakpoints that minimize the CD distortion while meeting the target rate as: • where and denote the rate required to encode block and the distortion, respectively, when the breakpoint value is used, and is the total number of blocks

  10. The content Adaptation(4/5) • Implementation - Procedure

  11. The content Adaptation(5/5) • Reference Info - reference value according to Bandwidth : FD(Frame Dropping), CD(Coefficient Dropping), PSNR • Parsing - reference Info is xml file format. So this file must be parsed • Decision Making - find adapted parameter by tree algorithm, Interpolation, Logic. • Adapt the bit stream parameter - generate the adpated bit stream parameter file

  12. The present works(1/2) • Implement Parsing system (a) Top : xml file (b) Bottom : parsed data

  13. The present works(2/2) • Implement the Interface - input the User Info(bandwidth) - display the value of the adapted parameter

  14. Futher works • In Adaptation engine, - Implementation of Decision making : Find efficiently and accurately Optimized value - adapt the bit stream

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