Full Content is available to subscribers

Subscribe/Learn More  >

Adaptive Segmentation for Air Gestures Identification

[+] Author Affiliations
Mostafa Ghobadi, Ehsan T. Esfahani

University at Buffalo, Buffalo, NY

Paper No. DETC2014-34809, pp. V01BT02A030; 5 pages
  • ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1B: 34th Computers and Information in Engineering Conference
  • Buffalo, New York, USA, August 17–20, 2014
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4629-2
  • Copyright © 2014 by ASME


Having a user-friendly Human-CAD interaction with high speed and accuracy plays a key role in development of future intelligent modeling environments. A major part of this puzzle is sketch identification using either 2D gestures — which is commonly recorded from mouse, light pen and touchpad — or air gestures captured from some newly emerged devices such as Leap Motion and Soft-Kinect. To this end, we present a leaning based technique for segmentation of air gestures. The proposed technique can detect the separation points of any single-stroke air gesture using specific motion features such as speed, curvature and center of curvature. Two types of separation points are considered: 1) rough separation points or simply corner points and 2) soft separation points such as inflection points. The segmentation is performed in two steps: Support Vector Machine (SVM) is used to adaptively differentiate the corner points from regular points. A soft segmentation method is then implemented to further break the rough segments into a set of smaller arcs and lines based on sudden change in the center of curvature. The experimental validation shows robust performance of the proposed method and low computation expenses.

Copyright © 2014 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In