Abstract
Most research on face recognition has focused on representation of face appearances rather than the classifiers. For robust classification performance, we need to adopt elaborate classifiers. Output coding is suitable for this purpose because it can allow online learning. In this paper, we propose an N-division output coding method. In the experiments we demonstrate such properties as problem complexity, margin of separation, machine relevance and the recognition performance among different output coding methods.
| Original language | English |
|---|---|
| Pages (from-to) | 3115-3123 |
| Number of pages | 9 |
| Journal | Pattern Recognition Letters |
| Volume | 24 |
| Issue number | 16 |
| DOIs | |
| Publication status | Published - 2003 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Software
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence
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N-division output coding method applied to face recognition. / Ko, Jaepil; Byun, Hyeran.
In: Pattern Recognition Letters, Vol. 24, No. 16, 01.01.2003, p. 3115-3123.Research output: Contribution to journal › Article
TY - JOUR
T1 - N-division output coding method applied to face recognition
AU - Ko, Jaepil
AU - Byun, Hyeran
PY - 2003/1/1
Y1 - 2003/1/1
N2 - Most research on face recognition has focused on representation of face appearances rather than the classifiers. For robust classification performance, we need to adopt elaborate classifiers. Output coding is suitable for this purpose because it can allow online learning. In this paper, we propose an N-division output coding method. In the experiments we demonstrate such properties as problem complexity, margin of separation, machine relevance and the recognition performance among different output coding methods.
AB - Most research on face recognition has focused on representation of face appearances rather than the classifiers. For robust classification performance, we need to adopt elaborate classifiers. Output coding is suitable for this purpose because it can allow online learning. In this paper, we propose an N-division output coding method. In the experiments we demonstrate such properties as problem complexity, margin of separation, machine relevance and the recognition performance among different output coding methods.
UR - http://www.scopus.com/inward/record.url?scp=0142120482&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0142120482&partnerID=8YFLogxK
U2 - 10.1016/S0167-8655(03)00179-X
DO - 10.1016/S0167-8655(03)00179-X
M3 - Article
AN - SCOPUS:0142120482
VL - 24
SP - 3115
EP - 3123
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
SN - 0167-8655
IS - 16
ER -