A Hybrid Object Tracking for Hand Gesture Approach based on MS-MD and its Application

In the research presented here, the hand gesture recognition is considered in American Sign Language to propose a hybrid approach, which is now organized based on the integration of the mean shift (MS), and the motion information (MD), entitled MS-MD approach. This is in fact proposed to track and recognize the hand gesture, in an effective manner, along with the corresponding potential benchmarks. The investigated results are synchronously acquired in line with these well-known techniques in the area of object tracking to modify those obtained from the traditional ones. The MS scheme is capable of tracking the objects based on its detailed objects, so we have to specify ones, as long as the MD scheme is not realized. In the proposed approach, the advantages of two algorithms are efficiently used, in a synchronous manner, to outperform the hand tracking performance. In the first step, the MD scheme is applied to remove a number of parts without area motion, and subsequently the MS scheme is accurately realized to deal with hand tracking. Subsequently, the present approach is considered to eliminate the weakness of the traditional methods, which are only organized in association with the MS scheme. The results are all carried out on Boston-104 database, where the hand gesture is tracked, in a better form, with respect to the previous existing ones.

کلیدواژه ها:

Hand Tracking ، Motion Detection ، Mean Shift ، Hand Gesture Recognition ، American Sign Language