Car/Non-Car Classification in an Informative Sample Subspace
In this paper, we present a method for data classification with application to car/non-car objects. We first developed a sample based car/non-car maximal mutual information low dimensional subspace. We then trained a support vector machine (SVM) in this subspace for the detection of cars. Using publ...
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| creator | Jianzhong Fang Guoping Qiu |
| description | In this paper, we present a method for data classification with application to car/non-car objects. We first developed a sample based car/non-car maximal mutual information low dimensional subspace. We then trained a support vector machine (SVM) in this subspace for the detection of cars. Using publicly available standard training and testing data sets, we demonstrated that our car detector gave very competitive performances |
| doi_str_mv | 10.1109/ICPR.2006.356 |
| format | Conference Proceeding |
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| identifier | ISSN: 1051-4651 |
| ispartof | 18th International Conference on Pattern Recognition (ICPR'06), 2006, Vol.2, p.962-965 |
| issn | 1051-4651 2831-7475 |
| language | eng |
| recordid | cdi_ieee_primary_1699366 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Computer science Image databases Information technology Mutual information Object detection Performance evaluation Pixel Support vector machine classification Support vector machines Testing |
| title | Car/Non-Car Classification in an Informative Sample Subspace |
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