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New hand gesture recognition method for mouse operations
- Issue Date
- Aug-2011
- Publisher
- IEEE
- Keywords
- Object Detection; Weak classifiers; Gesture recognition; Haar-like features; Hand posture; Hand gesture; Mammals; Object recognition; Cascaded classifiers; Mouse operations; Human computer interaction; Algorithms; Region of interest; Hand-gesture recognit
- Citation
- 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), pp 1 - 4
- Pages
- 4
- Indexed
- SCOPUS
- Journal Title
- 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS)
- Start Page
- 1
- End Page
- 4
- ISSN
- 1548-3746
1558-3899
- Abstract
- Hand gestures can be used for natural and intuitive human-computer interaction. Our new method combines existing techniques of skin color based ROI segmentation and Viola-Jones Haar-like feature based object detection, to optimize hand gesture recognition for mouse operation. A mouse operation has two parts, movement of cursor and clicking using the right or left mouse button. In this paper, color is used as a robust feature to first define a Region of Interest (ROI). Then within this ROI, hand postures are detected by using Haar-like features and AdaBoost learning algorithm. The AdaBoost learning algorithm significantly speeds up the performance and constructs an accurate cascaded classifier by combining a sequence of weak classifiers. © 2011 IEEE.
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