When the hand and the forearm enter the available depth range of the depth camera

the data of the hand and the forearm will be extracted together.Processing these data as a whole may affect some important algorithms such as the center of palm estimation

the orientation of hand estimation and hand tracing.The center of the palm is quite stable in the gesture interaction

so the line through the center of the palm and the center of the hand cluster is usual used as a hand orientation indicator.As a result

improving the performance of the center of palm estimation is favorable for increasing the overall performance. In order to correctly separate the hand from the forearm

the research begins with finding the motion features of the wrist and the contour features of the hand

and takes advantage of the geometric characteristics of an inscribed rectangle.At last a wrist recognition algorithm has been proposed.For improving the performance of the center of palm estimation

we start with analyzing the geometric characteristics of an acute triangle and an inscribed circle

and combine the features of the hand interaction.Finally a new algorithm of estimating the center of palm is proposed. The algorithms above are tested in an air multi-touch system.The proposed algorithm in this paper runs nearly 7 times quicker than the original algorithm

and still can keep the stability of the estimated coordinate of the center of palm

coordinate deviation not more than 3 pixels.Moreover

the success rate of the center of palm estimation is improved by using the wrist recognition algorithm.The accuracy of the center of palm estimation is improved due to using the wrist recognition algorithm. Our experiments proved that the wrist recognition algorithm can separate the hand from the forearm well

and the new algorithm of the center of palm estimation can support real time interaction well.