Research Article
Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks
@ARTICLE{10.4108/eai.6-7-2017.152758, author={Phan Ngoc Hoang and Bui Thi Thu Trang}, title={Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks}, journal={EAI Endorsed Transactions on Context-aware Systems and Applications}, volume={4}, number={12}, publisher={EAI}, journal_a={CASA}, year={2017}, month={7}, keywords={Hand poses classifying, image processing, video processing, method Viola-Jones, CAMShift algorithm, wavelet transform, PCA, neural networks.}, doi={10.4108/eai.6-7-2017.152758} }- Phan Ngoc Hoang
Bui Thi Thu Trang
Year: 2017
Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks
CASA
EAI
DOI: 10.4108/eai.6-7-2017.152758
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.
Copyright © 2017 Phan Ngoc Hoang and Bui Thi Thu Trang, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.