This paper presents a curvature based hand shape recognition method using images of a hand. The curvatures extracted from hand shape contours are converted to a non-dimensional quantity. Combining the contour geometry with the non-dimensional quantities, signatures are generated for template hand shapes. These template signatures are used to recognize hand shapes embedded in newly acquired image contours. The method provides a means of identifying a hand shape in a position and orientation independent manner. Nevertheless, the position and orientation of the hand gesture can still be obtained. The paper then presents a way to use hand shapes in an efficient virtual interface for a wheelchair. The presented system uses only four ergonomically chosen hand shapes to effect command inputs. The wheelchair operates in two different modes: the manual mode and the autonomous mode. The hand shapes used are arranged in a hierarchy taking into account the safety, ergonomics and reliability of operation. Results are presented to show the behavior of the wheelchair in both modes.
['Seong-Pal Kang', 'Michal Tordon', 'Jayantha Katupitiya']
Curvature based hand shape recognition for a virtual wheelchair control interface