A fast static gesture recognition method. (5th January 2015)
- Record Type:
- Journal Article
- Title:
- A fast static gesture recognition method. (5th January 2015)
- Main Title:
- A fast static gesture recognition method
- Authors:
- Zhang, Dongquan
Zhao, Jian - Abstract:
- Gesture recognition has become a hot spot in human interaction technology. But the difference of skin colour, the complexity of the background and the rotation of the gesture make it difficult to complete gesture segmentation and recognition. To overcome the impact of the difference of skin colour, in this paper gesture images are split out based on skin colour in the hue saturation value (HSV) colour space combined with the mean-shift algorithm. Then the Hu invariable moments of the gesture images are calculated as the feature vector to overcome the impact of the rotation of gesture. In the experiment 660 images were collected from 10 experimenters. Three hundred and thirty images of those were made up by left-hand gestures and the rest were made up by right-hand gestures. The experimental results show the accuracy of this algorithm is from 90% to 100% with single-hand static gestures.
- Is Part Of:
- International journal of computer applications technology. Volume 50:Number 3/4(2014)
- Journal:
- International journal of computer applications technology
- Issue:
- Volume 50:Number 3/4(2014)
- Issue Display:
- Volume 50, Issue 3/4 (2014)
- Year:
- 2014
- Volume:
- 50
- Issue:
- 3/4
- Issue Sort Value:
- 2014-0050-NaN-0000
- Page Start:
- 253
- Page End:
- 257
- Publication Date:
- 2015-01-05
- Subjects:
- static gesture recognition -- hand gesture segmentation -- Hu moment -- computer vision -- template match.
Technology -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.inderscience.com/jhome.php?jcode=ijcat ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 0952-8091
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8164.xml