| Author: | Chia, Stephen Si-wai |
| Title: | A study on the application of eigenvectors to the recognition of line-drawn faces |
| Degree: | M.Sc. |
| Year: | 1998 |
| Subject: | Face perception -- Computer simulation Optical pattern recognition Eigenvectors Principal components analysis Hong Kong Polytechnic University -- Dissertations |
| Department: | Multi-disciplinary Studies |
| Pages: | viii, 133 leaves : ill. ; 30 cm |
| Language: | English |
| Abstract: | This work examined the use of eigenvectors in the recognition of binary line-drawn human faces. The use of the eigenvectors as a means of dimension reduction was reviewed. The effectiveness of its application to the recognition and reconstruction of line-drawn faces was demonstrated. A masked version of the human face was used concentrating on the area of the face excluding the hair and face outline. The aspects demonstrated included the effect of reduction of the number of eigenvectors used, comparison between the values of principal components calculated for a foreign set against that from the training set, and the ability of the eigenvectors to reconstruct an occluded member of the training set. The ability of the eigenvectors to reconstruct something not in the training set was investigated. Some possible reasons for the results were discussed. Some ways to implement a library of line-drawn faces for recognition were proposed. It seems that the potential of line-drawn faces in their use for recognition (at least by using the eigenvector approach) is fairly limited both in terms of speed and accuracy, notwithstanding that they can be made more compact to store. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b14211130.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.71 MB | Adobe PDF | View/Open |
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