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231223s2011 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2010.2055880
|2 doi
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|a eng
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| 100 |
1 |
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|a Shen, Chunhua
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Efficiently learning a detection cascade with sparse eigenvectors
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|c 2011
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Completed 29.03.2011
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|a Date Revised 21.12.2010
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a Real-time object detection has many computer vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detection system, much effort has been spent on improving the boosting method. In this work, we first show that feature selection methods other than boosting can also be used for training an efficient object detector. In particular, we introduce greedy sparse linear discriminant analysis (GSLDA) for its conceptual simplicity and computational efficiency; and slightly better detection performance is achieved compared with . Moreover, we propose a new technique, termed boosted greedy sparse linear discriminant analysis (BGSLDA), to efficiently train a detection cascade. BGSLDA exploits the sample reweighting property of boosting and the class-separability criterion of GSLDA. Experiments in the domain of highly skewed data distributions (e.g., face detection) demonstrate that classifiers trained with the proposed BGSLDA outperforms AdaBoost and its variants. This finding provides a significant opportunity to argue that AdaBoost and similar approaches are not the only methods that can achieve high detection results for real-time object detection
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| 650 |
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4 |
|a Journal Article
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| 650 |
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4 |
|a Research Support, Non-U.S. Gov't
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| 700 |
1 |
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|a Paisitkriangkrai, Sakrapee
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zhang, Jian
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 20(2011), 1 vom: 10. Jan., Seite 22-35
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|x 1941-0042
|7 nnns
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|g volume:20
|g year:2011
|g number:1
|g day:10
|g month:01
|g pages:22-35
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4 |
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|u http://dx.doi.org/10.1109/TIP.2010.2055880
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