Research on Interaction-oriented Gesture Recognition

Clicks: 314
ID: 33632
2014
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #10 of 17 articles by views in sensors & transducers

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
This thesis designs a series of gesture interaction with the features of the natural human-machine interaction; besides, it utilizes the 3D acceleration sensors as interactive input. Afterwards, it builds the Discrete Hidden Markov Model to make gesture recognition by introducing the collection proposal of gesture interaction based on the acceleration sensors and pre-handling the gesture acceleration signal obtained in the collection. In the end, the thesis proofs the design proposal workable and effective according to the experiments.
Reference Key
huang2014researchsensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Huang, Lu;Zhou, Zongkui;Liu, Rong;
Journal sensors & transducers
Year 2014
DOI
DOI not found
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.