Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks
Journal Title: EAI Endorsed Transactions on Context-aware Systems and Applications - Year 2017, Vol 4, Issue 12
Abstract
In 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.
Authors and Affiliations
Phan Ngoc Hoang, Bui Thi Thu Trang
Keywords
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- EP ID EP45797
- DOI http://dx.doi.org/10.4108/eai.6-7-2017.152758
- Views 229
- Downloads 0
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