Publication

Audio-visual synchronization recovery in multimedia content

Touradj Ebrahimi, Jong Seok Lee
2011
Conference Papers

Abstract

This paper proposes a method recovering audio-visual synchronization of multimedia content. It exploits the correlation between the acoustic and the visual signals in order to estimate the audio-visual drift existing in the content. By shifting the audio signal relative to the visual signal, the estimation of the drift is obtained by searching for the shift producing the maximal audio-visual correlation. We consider two correlation measures, namely, mutual information and canonical correlation, and compare their performance. Experimental results demonstrate that the method using the canonical correlation is effective in recovering the audio-visual synchronization for both speech and non-speech sequences.

Official source

https://infoscience.epfl.ch/entities/publication/4da53ec6-daa4-45bf-86ca-9bb28ab87f3c

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Touradj Ebrahimi, Jong Seok Lee
2011
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/4da53ec6-daa4-45bf-86ca-9bb28ab87f3c

About this result

Related concepts (32)

Correlation

In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics it usually refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve.

Pearson correlation coefficient

In statistics, the Pearson correlation coefficient (PCC) is a correlation coefficient that measures linear correlation between two sets of data. It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1. As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types of relationships or correlations.

Intraclass correlation

In statistics, the intraclass correlation, or the intraclass correlation coefficient (ICC), is a descriptive statistic that can be used when quantitative measurements are made on units that are organized into groups. It describes how strongly units in the same group resemble each other. While it is viewed as a type of correlation, unlike most other correlation measures, it operates on data structured as groups rather than data structured as paired observations.

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