Research of dynamic gesture recognition based on multi-instance learning of kinematics features

Abstract

Compared to static gestures,dynamic gestures had some new characteristics.The problems of dynamic gestures recognition was spewed by using kinematics mode,such as divergence modes,curl modes,symmetric and ant-symmetric modes,the second and third principal invariant modes of the gradient tensor,the second and third principal invariant modes of the strain tensor and the third principal invariant modes of spin tensor; Further,a framework based on multi-instance learning was proposed,organize all these principle modes for each gesture were organized to a dynamic gestures bag-of-words,and the similarity between the mode of unknown type dynamic gestures and the all bag-of-words were calculated.Then,the nearest neighbor method was used to recognize the dynamic gestures.The experimental results show that the dynamic gestures recognition based on multi-instance kinematics features principal mode learning methods can obtain a higher recognition rate.

Keywords

• gesture recognition;kinematics features;temporal axis dimension reduction;multi-instance learning