Hand gesture recognition supported by fuzzy rules and Kalman filters
Michał Lech, Bożena Kostek · International Journal of Intelligent Information and Database Systems · 2012
The paper presents a system based on camera and multimedia projector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology. In addition, OpenCV is used for image processing and J2SE with jFuzzyLogic package is employed for gesture interpretation. Results of fuzzy rule-based and fixed threshold-based gesture recognition effectiveness are provided. Additionally, for fuzzy rule-based gesture recognition the system efficacy after utilising Kalman filters is examined. The so-called interactive whiteboard application is given as an example of the system usage.