Efficiently Training A Better Visual Detector With Sparse Eigenvectors
Face detection plays an important role in many vision applications. Since Viola and Jones  proposed the first real-time AdaBoost based object detection system, much ef- fort 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 ob- ject detector. In particular, we have adopted Greedy Sparse Linear Discriminant Analysis (GSLDA)  for its computa- tional efficiency; and...[Show more]
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|Source:||Proceeings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009)|
|01_Paisitkriangkrai_Efficiently_Training_A_Better_2009.pdf||644.97 kB||Adobe PDF||Request a copy|
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