Abstract
We describe experiments with eigenfaces for recognition and interactive search in a large-scale face database. Accurate visual recognition is demonstrated using a database of O(10/sup 3/) faces. The problem of recognition under general viewing orientation is also examined. A view-based multiple-observer eigenspace technique is proposed for use in face recognition under variable pose. In addition, a modular eigenspace description technique is used which incorporates salient features such as the eyes, nose and mouth, in an eigenfeature layer. This modular representation yields higher recognition rates as well as a more robust framework for face recognition. An automatic feature extraction technique using feature eigentemplates is also demonstrated.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
EigenfaceArtificial intelligencePattern recognition (psychology)Facial recognition systemComputer scienceFeature extractionSalientThree-dimensional face recognitionModular designOrientation (vector space)Face (sociological concept)Feature (linguistics)Computer visionFace detectionMathematics
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Publication Info
- Year
- 1994
- Type
- article
- Citations
- 1808
- Access
- Closed
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Cite This
Pentland,
Moghaddam,
Starner
(1994).
View-based and modular eigenspaces for face recognition.
.
https://doi.org/10.1109/cvpr.1994.323814
Identifiers
- DOI
- 10.1109/cvpr.1994.323814