doi: 10.7763/IJCTE.2012.V4.546
Autonomous Robot Control Using Facial Expressions
Rohin Mittal1
,
Prateek Srivastava2 ,
Alpha George3 ,
Asim Mukherjee4
- 1Apache Design Solutions Pvt. Ltd., Bengaluru, India.
- 2NTPC Ltd., Singrauli, India
- 3Samsung Software India R and D Center, Noida, India
- 4Electronics and Communication Engineering Department at Motilal Nehru National Institute of Technology, Allahabad, India
Abstract
In this paper, a novel real time robot control system using human facial expressions is presented. The proposed system mainly consists of three modules: face detection, facial expression recognition and robot control. The first module aims to find the user’s face from the image captured from a live video through a series of steps including skin color classification, edge detection and mathematical morphology, while the second module analyses the detected face to recognize the facial expressions like happiness, sadness, surprise, anger and neutral using Principal Component Analysis (PCA) and Euclidian distance calculation. Finally, the detected facial expressions are used as controlling commands for the robot. Experiments were conducted for respective modules. 150 images under different lightening conditions and complex background were employed. In the experiment on detecting the facial region, the rate of detection was 99.3% and on recognizing the facial expression, the recognition rate was 97.3%. The robot was then controlled autonomously with an accuracy of 100%. Combining the above three rates, the overall rate of success of our system was 97.3%.
Keywords
- Autonomous robot
- euclidian distance
- face detection
- facial expression recognition
- principle component analysis
How to Cite
Rohin Mittal, Prateek Srivastava, Alpha George, and Asim Mukherjee, "Autonomous Robot Control Using Facial Expressions," International Journal of Computer Theory and Engineering, vol. 4, no. 4, pp. 631-635, 2012. https://doi.org/10.7763/IJCTE.2012.V4.546
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).