Moment-based human motion recognition from the representation of DMHI templates

This paper presents a noble appearance-based recognition approach of human motion and gestures of several peoplespsila several actions from uncalibrated camera by employing motion history-based representation. It employs the basic motion history image-based and the directional motion history image-based representation and then exploits these motion templates to recognize various motions having more than one motion direction or complex motion. Traditionally, the basic MHI approach used seven Hu moments for feature vector calculation. This paper analyzed the implementation of a better feature vector calculation for our directional approach. We tried with two different feature vector sets for Hu moment. Moreover, due to its better performance, we computed another feature vector set based on the top twelve orders of Zernike moments. Due to computational cost, we finally ignored to employ Zernike moments for the DMHI template for recognition. This new feature vector calculation approach can reduce the calculation and shows good recognition rate. Finally, this paper raised some future concerns of this method.