Facial Recognition System using Eigenfaces and SVM
Facial Recognition System using Eigenfaces (PCA) and SVM
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This code uses the Eigenface approach provided by M.Turk and A. Pentland to obtain training features. PCA is used to reduce the dimensionality of feature vector and SVM is used to obtain a training model. Use of Machine Learning improves the accuracy of Eigenface approach.
Cite As
Shreyas Shubhankar (2026). Facial Recognition System using Eigenfaces and SVM (https://github.com/shreyas00/Facial-Recognition-System), GitHub. Retrieved .
Categories
Find more on Dimensionality Reduction and Feature Extraction in Help Center and MATLAB Answers
General Information
- Version 1.0.0.0 (2.78 KB)
-
View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
Versions that use the GitHub default branch cannot be downloaded
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.
