Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks

Authors

DOI:

https://doi.org/10.4108/eai.6-7-2017.152758

Keywords:

Hand poses classifying, image processing, video processing, method Viola-Jones, CAMShift algorithm, wavelet transform, PCA, neural networks

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.

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Published

06-07-2017

How to Cite

1.
Ngoc Hoang P, Thu Trang BT. Context-aware hand poses classifying on images and video-sequences using a combination of wavelet transforms, PCA and neural networks. EAI Endorsed Trans Context Aware Syst App [Internet]. 2017 Jul. 6 [cited 2024 Nov. 14];4(12):e2. Available from: https://publications.eai.eu/index.php/casa/article/view/1963