Gestures for natural interaction with video

In the context of immersive communications, we propose a method enabling natural video interactions through hand gesture recognition between users and a video meeting system. The interaction can be performed either by the mean of hand posture recognition or by the dynamic hand gesture recognition according to user’s preference. The statistical approach adopted in our work to recognize hand posture has shown accurate results for both performance evaluation and user test. Besides, the combination of data-mining fields and signal processing for dynamic gestures recognition allows us to define the appropriate rules and to reduce the confusion between gestures. Furthermore, the hand region extraction is based on both skin color and background subtraction to avoid the detection of static objects that have a similar skin color. Finally, the collected user’s feedback allows as to evaluate our approach from the user’s point of view and to define the limitations that will be discussed in our perspectives in order to improve the results.