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Canonical Correlation Analysis

  • David Forsyth
Chapter

Abstract

In many applications, one wants to associate one kind of data with another. For example, every data item could be a video sequence together with its sound track. You might want to use this data to learn to associate sounds with video, so you can predict a sound for a new, silent, video. You might want to use this data to learn how to read the (very small) motion cues in a video that result from sounds in a scene (so you could, say, read a conversation off the tiny wiggles in the curtain caused by the sound waves). As another example, every data item could be a captioned image. You might want to predict words from pictures to label the pictures, or predict pictures from words to support image search. The important question here is: what aspects of the one kind of data can be predicted from the other kind of data?

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • David Forsyth
    • 1
  1. 1.Computer Science DepartmentUniversity of Illinois Urbana ChampaignUrbanaUSA

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