Name
Abstract | ||
|---|---|---|
This paper addresses the issue of combining pre-processing methods--dimensionality reduction using Principal Component Analysis (PCA) and Locally Linear Embedding (LLE)--with Support Vector Machine (SVM) classification for a behaviorally important task in humans: gender classification. A processed version of the MPI head database is used as stimulus set. First, summary statistics of the head database are studied. Subsequently the optimal parameters for LLE and the SVM are sought heuristically. These values are then used to compare the original face database with its processed counterpart and to assess the behavior of a SVM with respect to changes in illumination and perspective of the face images. Overall, PCA was superior in classification performance and allowed linear separability. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/3-540-36181-2_49 | Biologically Motivated Computer Vision |
Keywords | Field | DocType |
gender classification,mpi head database,face image,head database,processed counterpart,human faces,principal component analysis,processed version,linear embedding,original face database,classification performance,pca,svm,dimensionality reduction,support vector | Linear separability,Heuristic,Embedding,Dimensionality reduction,Pattern recognition,Support vector machine,Artificial intelligence,Principal component analysis,Machine learning,Mathematics | Conference |
Volume | ISSN | ISBN |
2525 | 0302-9743 | 3-540-00174-3 |
Citations | PageRank | References |
23 | 1.01 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arnulf Graf | 1 | 145 | 9.85 |
| F A Wichmann | 2 | 231 | 17.54 |