A vision based system for communicating in virtual reality environments by recognizing human hand gestures

Nowadays, with the emerging of the new applications like virtual reality using image processing and machine vision algorithms, it is necessary to have more modern interfaces for interaction with robots and computers. To cope with this problem, vision based gesture recognition systems play a significant role. This paper implements a vision based system for human hand gesture recognition. We propose three different methods for human hand gesture recognition, including, 1-a new method based on spatio-temporal volumes, 2-hand gesture recognition based on Motion History Image (MHI) and 3-method based on eigen space features. In these algorithms, after applying necessary pre-processing on video frames, some features are extracted for each gesture. These features are then analyzed and finally, a classification algorithm is applied for the hand gesture recognition. We tested the proposed three algorithms with the collected dataset and the results showed that proposed method based on the spatio-temporal volumes results in the correct recognition rate of 99.58 % for noiseless and 97.92 % for noisy data. Comparing the results of the proposed method based on the spatio-temporal volumes with two other methods shows that the recognition rate is improved up to 5.83 % and 8.75 % respectively.