Please use this identifier to cite or link to this item: http://thuvienso.bvu.edu.vn/handle/TVDHBRVT/16149
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dc.contributor.authorPhan, Ngoc Hoàng-
dc.contributor.authorBùi, Thị Thu Trang-
dc.date.accessioned2017-09-18T03:22:06Z-
dc.date.available2017-09-18T03:22:06Z-
dc.date.issued2017-07-
dc.identifier.urihttp://thuvienso.bvu.edu.vn/handle/TVDHBRVT/16149-
dc.description.abstractIn this paper we propose novel context-aware algorithms for hand poses classifying on images and video-sequences. The proposed hand poses classifying on images algorithm based on Viola-Jones method, wavelet transform, PCA and neural networks. On the first step, the Viola-Jones method is used to find the location of hand pose on images. Then, on the second step, the features of hand pose are extracted using combination of wavelet transform and PCA. Finally, on the last step, these extracted features are classified by multi -layer feed-forward neural networks. The proposed hand poses classifying on video-sequences algorithm based on the combination of CAMShift algorithm and proposed hand poses classifying on images algorithm. The experimental results show that the proposed algorithms effectively classify the hand pose in difference light contrast conditions and compete with state-of-the-art algorithms.vi
dc.language.isoenvi
dc.publisherresearchgate.netvi
dc.relation.ispartofseriesVol 4;-
dc.subjectImage processingvi
dc.subjectXử lý hình ảnhvi
dc.subjectVideo processingvi
dc.subjectXử lý videovi
dc.titleContext-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networksvi
dc.typeArticlevi
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