Hybrid hand tracking system
Jing-Ming Guo, Hoang-Son Nguyen · 2011
This study presents a hybrid hand tracking system using Pixel-Based Hierarchical-Feature AdaBoosting (PBHFA), skin color segmentation, and codebook background cancellation. The object of this approach is to construct a system which is able to cope with hand detection and further tracking tasks. To reduce the effect of false positive, the skin color segmentation and the foreground subtraction by applying the codebook model are employed for rejecting all of the candidates which are not hand targets. As documented in the experimental results, the proposed system can achieve promising results, and thus it can be considered as an effective candidate in handling practical applications which require hand postures.