Hand-gesture recognition : comparative study of global, semi-local ans local approaches
Résumé
Asepsis preservation in operating rooms is essen- tial for limiting patient infection by hospital-acquired diseases. Because of this, surgeons may not be directly in contact with sterile equipment surrounding them, and must instead rely on assistants to interact with these in their place. Gesture-based Human-Computer Interfaces constitute an interesting option for allowing surgeons to control such equipment without breaking asepsis-preservation rules. In this paper, we will describe the results given by our preparative study to such a system. Methods representative of the three main approaches in object description (i.e. local, semi- local and global approaches) are compared in terms of hand posture recognition performance when the pictures' background are not removed. A picture database presenting variations in the postures' angles and illumination, as well as plain and altered backgrounds was created to this end. We study the effects of altered backgrounds, user-dependency and incomplete training databases on recognition rates. Obtained results give semi-local approaches such as Dalal et al.'s Histograms of Oriented Gradients more promising than local or global ones. However, performance degradation is such important when considering non-uniform picture backgrounds that pre-treatments aiming at segmenting the hand from the background appear to be necessary.
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