A Hybrid Object Tracking for Hand Gesture (HOTHG) Approach based on MS-MD and its Application
محورهای موضوعی : Image ProcessingAmir Hooshang Mazinan 1 , Jalal Hassanian 2
1 - Azad University, South Tehran Branch
2 - Azad University, South Tehran Branch
کلید واژه:
چکیده مقاله :
In the research proposed here, a hybrid object tracking approach, namely HOTHG, with its application to hand gesture recognition in American Sign Language; ASL, is realized. This is in fact proposed to track and recognize the hand gesture, in an effective manner, in line with the mean shift; MS, and the motion detection; MD, entitled MS/MD-based approach. The results are synchronously investigated based on these two well-known techniques in the area of object tracking to modify those obtained from the traditional ones. The MS algorithm can track the objects based on its detailed targets, so we have to specify ones, as long as the MD algorithm is not realized. In the proposed approach, the advantages of two algorithms are efficiently used to upgrade the hand tracking performance. In the first step, the MD algorithm is applied to remove a number of parts without area motion, and subsequently the MS algorithm is accurately realized for hand tracking. Finally, the present approach is carried out to eliminate the weakness of the traditional methods, which are only organized in association with the MS algorithm. The results are all carried out on Boston-104 database, where the hand gesture is tracked in better form with respect to the previous existing approaches.
In the research proposed here, a hybrid object tracking approach, namely HOTHG, with its application to hand gesture recognition in American Sign Language; ASL, is realized. This is in fact proposed to track and recognize the hand gesture, in an effective manner, in line with the mean shift; MS, and the motion detection; MD, entitled MS/MD-based approach. The results are synchronously investigated based on these two well-known techniques in the area of object tracking to modify those obtained from the traditional ones. The MS algorithm can track the objects based on its detailed targets, so we have to specify ones, as long as the MD algorithm is not realized. In the proposed approach, the advantages of two algorithms are efficiently used to upgrade the hand tracking performance. In the first step, the MD algorithm is applied to remove a number of parts without area motion, and subsequently the MS algorithm is accurately realized for hand tracking. Finally, the present approach is carried out to eliminate the weakness of the traditional methods, which are only organized in association with the MS algorithm. The results are all carried out on Boston-104 database, where the hand gesture is tracked in better form with respect to the previous existing approaches.
