The Man-Machine Finger-Guessing Game Based on Cooperation Mechanism

In this study, a Man-machine Finger-guessing game is designed based on the IntelliSense and Man-machine coordination mechanism of hand gesture. The image sequence is obtained by the Kinect and the human hand is extracted using segmentation and skin color modeling. The proposed SCDDF (Shape Context Density Distribution Feature), which combined DDF (Density Distribution Feature) algorithm and shape context recognition algorithm, is used to extract gesture identity. Gestures are finally identified by registering with templates in the pre-established gesture library. Furthermore, we proposed a new human-computer cooperative mechanism, including two points: (1) The virtual interface is used to control the ‘Midas Touch problem’. (2) The whole game is more natural and smooth. In the aspect of gesture recognition, we combined DDF algorithm and shape context recognition algorithm, and proposed the SCDDF algorithm. The new algorithm improved recognition rate by 14.3% compared with DDF algorithm.