What is it about?
Human action recognition is a technique that recognizes the movement of human being. In the previous studies in this field, various types of parameters have been used for recognizing human action which was both times consuming and difficult to understand. Here we have described a method which uses the multi-directional features such as Shearlet Transform.
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Why is it important?
We proposed a technique that takes the features of depth video sequences muti-directionally. So, maximum features can be taken that enhances the accuracy of the proposed approach compared to the existing ones. Even, the movement of animals can be recognized using our proposed method.
Perspectives
The emerging cost-effective depth sensors have made easier the action recognition task significantly. In this paper, we propose an effective method to analysis human actions from depth video sequences based on multi-scaling and multi-directional transformation which provide additional body shape and motion information for action recognition. In our proposed method we have analyzed human motion using Shearlet Transform which provides better accuracy than some previous research related to human motion analysis.
Mr Mohammad Shahadat Hossain
shahadatku10@outlook.com
Read the Original
This page is a summary of: Human Motion Analysis from Depth Video Sequences Using Multi-scale and Multi-directional Features, British Journal of Applied Science & Technology, January 2017, Sciencedomain International,
DOI: 10.9734/bjast/2017/31153.
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