Rotation Tolerant Hand Pose Recognition Using Aggregation Of Gradient Orientations

The visual recognition of hand poses is one of the central problems in the development of applications controlled by visual gestures. In this paper, a generic orientation histogram based technique is described and applied to the pose recognition from intensity images. The technique addresses the need for rotation tolerant recognition using an orientation normalization technique, where the uncertainty related to the reference point of normalization is also taken into account by cyclic filtering. To complement the scheme, the circularly symmetric composition of histogram aggregation regions is introduced and the rotation tolerance can be controlled by range selection. In the experiments, we provide results on the choice between the parameter values and make comparisons to the existing techniques, which show the potential of the approach.