Human emotion modelling could prove to be an important area of application for the purpose of increasing interaction between human and the computer. For modelling emotion, we have used corners as facial feature present in the image. A corner is a very important feature of an image. It represent intersection of two curves/edges, it also represents a significant change in the colour intensities in the image nearby the point itself. Extraction of corners in the image may prove to be very useful in certain areas of image processing. In this paper, various corner detection algorithms like SUSAN, Harris, Moravec and FAST corner detector algorithms are empirically evaluated with our proposed brute force approach. The comparison is based on how much time does the algorithm takes to detect the corners on the facial features of frontal human face. Furthermore, the algorithm that was found to be performing better was used in the face modelling application.

1. S. Cordelia, M. Roger, B. Christian, "Evaluation of Interest Point Detectors," International Journal of Computer Vision, Vol. 37, pp. 151-172, 2000.
2. S. Smith, J. Brady, "SUSAN - A new approach to low level image processing," International Journal of Computer Vision, Vol. 23, No. 1,pp. 45-48, 1997.
3. C. Harris, M. Stephens, "A combined corner and edge detector," Proceedings of the Fourth Alvey Vision Conference, University of Sheffield Printing Unit, Manchester, pp. 147-151, 1988.
4. D. Nilanjan, N. Pradipti, B. Nilanjana, D. Debolina, C. Subhabrata, "A Comparative study between Moravec and Harris Corner Detection of Noisy Images Using Adaptive Wavelet Thresholding Technique," International Journal of Engineering Research and Applications, Vol. 2, Iss. 1, pp. 599-606, 2012.
5. H. Moravec, "Rover Visual Obstacle Avoidance," Proceedings of Fifth International Joint Conference on Artificial Intelligence, pp. 598-600, 1979.
6. R. Edward, D. Tom, "Machine Learning for High Speed Corner Detection," 9thEuropean Conference on Computer Vision, vol. 1, pp. 430-443, 2006.
7. T. Miroslav, H. Mark, "Fast Corner Detection," Image and Vision Computing, Vol. 16, pp. 75-87, 1998.
8. V. Santosh, G. Sanjay, "An empirical evaluation of wavelet based viz-a-viz classical state of image denoising," IC3-2013, Sixth International Conference on IEEE, pp. 331-336, 8-10 August 2013.
9. V. Santosh, K. Vinish, S. Amit, "Background Subtraction Techniques," International Symposia ISAC-2011.
10. C. Jie, Z. Li-Hui, Z. Juan, D. Li-Hua, "The Comparison and Application of Corner Detection Algorithms," Journal of Multimedia, Vol. 4, No. 6, pp. 435-441, 2009.
11. M. Farzin, M. Farahnaz, "Performance Evaluation of Corner Detectors using Consistency and Accuracy Measures," Computer Vision and Image understanding, Vol. 102, No. 1, pp 81-94, 2006.
12. L. Yong- Hwan, "Detection and Recognition of Facial Emotion using Bezier Curves," IT Convergence Practice (INPRA), Vol. 1, 2013.
13. Chavan, P. M. , Jadhav M. C. , Mashruwala J. B. , Nehete A. K. and Panjari P. A. 2013. "Real Time Emotion Recognition through Facial Expressions for Desktop Devices", International Journal of Emerging Science and Engineering(IJESE), Vol. I,7.
14. Gupta, N. and Kaur, N. 2013, "Design and Implementation of Emotion Recognition System by using Matlab", International Journal of Engineering Research and Applications (IJERA), ISSN: 2248-9622, Vol. 3,4, 2002-2006.
15. Gosavi, A. P and Khot, S. R. Sept 2013, "Facial Expression Recognition Using Principal Component Analysis", International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307, Vol. 3, 4.
16. Lee, Y. H, 2013, "Detection and Recognition of facial Emotion using Bezier Curves", IT Convergence Practice (INPRA), Vol. 1.
17. http://en. wikipedia. org/wiki/B%C3%A9zier_curve
18. http://en. wikipedia. org/wiki/YCbCr
19. http://www. cs. mtu. edu/~shene/COURSES/cs3621/NOTES/spline/Bezier/bezier-construct. html
20. http://www. equasys. de/colorconversion. html.

Corner Detection Susan Harris Moravec Fast Brute Force Bezier Curve Face Modelling.