Skip to main content

Statistical Analysis of Massive Data Streams Proceedings of a Workshop (2004) / Chapter Skim
Currently Skimming:


Pages 187-188

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 187...
... IV. CONCLUSIONS We have presented techniques for constructing classifiers that combine statistical information from training data with tangent approximations to known transformations, and we demonstrated the techniques by applying them to a face recognition task.
Read the entire page →
From page 188...
... , dl (the symmetrized Mahalanobis distance) , and LDA Correlation (the best performing algorithm in the CSU distribution)
Read the entire page →

Key Terms

  • training data
  • feret data
  • eye coordinates
  • mahalanobis distance
  • recognition task

  • recognition algorithms
  • error rate
  • evaluation procedure


    • This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
    More information on Chapter Skim is available.