The Comparative Analysis of a Vision Based HGR System Used for Handicapped People

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  •   Rushikesh Tukaram Bankar

  •   Suresh Salankar

Abstract

The object tracking is critical to visual / video surveillance, analysis of the activity and gesture recognition. The major difficulties to be occurred in the visual tracking are different environmental conditions, illumination changes, occlusion and appearance. In this paper, the comparative analysis of the different systems which are used to recognize the head gestures under different environmental conditions is discussed. The existing algorithm used to recognize the head gestures has some limitations. The existing algorithm cannot work under outdoor environmental conditions. The traditional camshift algorithm and unscented kalman filter are integrated and used to recognize the head gestures under outdoor environmental conditions. The unscented kalman filter is a tracking algorithm used to remove the limitations of the traditional camshift algorithm. The simulation result shows the better performance of the improved algorithm than the traditional camshift algorithm.


Keywords: Camshift, Face Detection, Face Tracking, Head Gesture Recognition

References

Y. Zhang, J. Zhang, and Y. Luo, “A Novel Intelligent Wheelchair Control System based on Hand Gesture Recognition,” 2011 IEEE / ICME International Conference on Complex Medical Engineering, May 22 - 25, Harbin, China.

Noriyuki Kawarazaki, and Alejandro Israel Barragan Diaz, “Gesture Recognition System for Wheelchair Control Using A Depth Sensor,” IEEE International Conference.

Ericka Janet Rechy Ramirez, Huosheng Hu, and Klaus McDonald Maier, “Head Movement based control of an intelligent wheelchair in an indoor environment,” Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics, December 11 - 14, 2012, Guangzhou, China.

N. Kawarazaki, and A. Diaz, “Gesture Recognition System For Wheelchair Control Using A Depth Sensor,” IEEE International Conference 2013.

E. Ramirez, H. Hu, and K. Maier, “Head Movement based control of an intelligent wheelchair in an indoor environment,” Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics, December 11 - 14, 2012, Guangzhou, China.

R. Mbouna, S. Kong, and M. Chun, “Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring,” 2013 IEEE Transactions on Intelligent Transportation Systems, Vol. 14, No. 03, September, 1462 - 1469.

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How to Cite
[1]
Bankar, R. and Salankar, S. 2019. The Comparative Analysis of a Vision Based HGR System Used for Handicapped People. European Journal of Engineering Research and Science. 4, 10 (Oct. 2019), 52-54. DOI:https://doi.org/10.24018/ejers.2019.4.10.1509.