K.Tieuand P. Viola, "Boosting Image Retrieval," Proc. IEEECS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 228-235, 2000. Home/Search Document Not in Database Summary Related Articles Check |
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Feature Selection Applied to Image Beauty Estimation - Klautau (Correct)
....information about beauty . Instead of pre establishing a set of features, one can alternatively adopt a datadriven method that may extract a too large set, which can then be reduced in a second stage through feature selection. Following such approach, the image retrieval system proposed in [TV00] uses a cascade of filters to convert each image into a relatively large (46,8 5 dimensional) feature vector. A small subset of these features is selected through a boosting based method. The idea is that few of these features respond in a highly selective way to a group of images or specific ....
....method. The idea is that few of these features respond in a highly selective way to a group of images or specific characteristic as, e.g. the light dark light region associated to the eyes and nose of a human face. We discuss now the boosting based and other feature selection techniques. As in [TV00] Das01] used the AdaBoost algorithm [SS99] for selecting features. Both works use boosting as a filter method. In [SN99] boosting was integrated to wrapper methods. Wrappers are of interest because they can lead to improved ac curacy when compared to filter methods. In [Ng98] an analysis of ....
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K. Ticu and P. Viola. Boosting image retrieval. In IEEE Conference on Computer Vision and Pattern Recognition, pages 228-235, 2000.
FloatBoost Learning and Statistical Face Detection - Li, Zhang (2004) (3 citations) (Correct)
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K.Tieuand P. Viola, "Boosting Image Retrieval," Proc. IEEECS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 228-235, 2000.
FloatBoost Learning and Statistical Face Detection - Li, Zhang (2004) (3 citations) (Correct)
No context found.
K.Tieuand P. Viola, "Boosting Image Retrieval," Proc. IEEECS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 228-235, 2000.
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