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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
Reconstruction process simply implied as reversing the eigenface procedure.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper, PCA based face recognition system and reconstruction of faces from principle components of faces are represented.
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Key Findings & Data:Principle component analysis used for construction of eigenfaces of given training set images.
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Conclusion & Impact:Reconstruction process simply implied as reversing the eigenface procedure.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
In this paper, PCA based face recognition system and reconstruction of faces from principle components of faces are represented. Principle component analysis used for construction of eigenfaces of given training set images. Using the eigenface method, expression of each face’s data reduced to a very small integer array. Euclidian distance was used for classification of test images. Reconstruction process simply implied as reversing the eigenface procedure.
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Cite This Article
ÖZTAŞ, O., ALTIOK, G. (2022). Face recognition and reconstruction using eigenfaces. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 9 - Sayı: 2, 997–1001. https://ajindex.com/articles/543741