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Yong Wang, Mihaela van der Schaar, Shih-Fu Chang, Alexander C. Loui. Classification-based multidimensional adaptation prediction for scalable video coding using subjective quality evaluation. IEEE Transactions on Circuits and Systems for Video Technology, 15:1270-1279, 2005.

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Scalable video coding offers a flexible representation for video adaptation in multiple dimensions comprising spatial detail and temporal resolution, thus providing great benefits for universal media access (UMA) applications. However, currently most of the approaches address the multi-dimensional adaptation (MDA) problem in an ad hoc manner. One challenging issue affecting the systematic MDA solution is the difficulty in constructing analytical models in theoretical optimization that capture the relations between video utility and MDA operations. In this paper, we propose a general classification-based prediction framework for selecting the preferred MDA operations based on subjective quality evaluation. For this purpose, we first apply domain-specific knowledge or general unsupervised clustering to construct distinct categories within which the videos share similar preferred MDA operations. Thereafter, a machine learning based method is applied where the low level content features extracted from the compressed video streams are employed to train a framework for the problem of joint SNR-temporal adaptation selection based on the Motion Compensated 3D SubBand Coding (MC-3DSBC) system. We conduct extensive subjective tests involving 31 subjects, 128 video clips, and formal subjective quality metrics. Statistical analysis of the experimental results confirms the excellent accuracy in using domain knowledge and content features to predict the MDA operation


Yan Wang
Yong Wang
Shih-Fu Chang

BibTex Reference

   Author = {Wang, Yong and van der Schaar, Mihaela and Chang, Shih-Fu and Loui, Alexander C.},
   Title = {Classification-based multidimensional adaptation prediction for scalable video coding using subjective quality evaluation},
   Journal = {IEEE Transactions on Circuits and Systems for Video Technology},
   Volume = {15},
   Pages = {1270--1279},
   Year = {2005}

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