Feature Selection for Grasp Recognition from Optical Markers

Feature Selection for Grasp Recognition from Optical Markers

Chang et al use feature subset selection to determine an optimal number of optical markers to track grasps. By sequentially adding to or removing from the set of possible markers, they determined that when using only 5 of 30 possible recognition accuracy is not significantly reduced (3-8% reduction). Recognition also translates well to new objects when using either 5 or 30 markers, but not necessarily to new users, who may form grasps in entirely different manners.

Discussion
Shouldn't the other 2 marker thats are used to define the local coordinate system also be excluded from the feature selection process, since their positions should be invariant as well? Also, several of the markers seem to be placed in highly redundant positions.

Reference
L.Y. Chang, N. Pollard, T. Mitchell, and E.P. Xing, "Feature Selection for Grasp Recognition from Optical Markers," Proceedings of the 2007 IEEE/RSJ Intl. Conference on Intelligent Robots and Systems (IROS 2007), October, 2007, pp. 2944-2950.