Intelligent Vision System for Human-Robot Interface

This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.

Authors:

• Al-Amin Bhuiyan
• Chang Hong Liu

Keywords:

• Fuzzily skewed filter
• human-robot interface
• rmscontrast
• skin color segmentation.

References:

[1] H. Shinn, and H. Hui-Ling, "Facial modeling from an uncalibrated face
image using a coarse-to-fine genetic algorithm", Pattern Recognition,
Vol. 34, No. 8, 2001, pp. 1015-1031.
[2] F. Goudail, E. Lange, T. Iwamoto, K. Kazuo, and N. Otsu, "Face
recognition system using loacal autocorrelations and multiscale
integration", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 18, No. 10, 1996, pp. 1024-1028.
[3] H. Rowley, B. Shumeet, and T. Kanade, "Neural network-based face
detection", IEEE Transaction on Pattern Analysis and Machine
Intelligence, Vol. 20, No. 1, 1998, pp. 23-37.
[4] M. Turk, and A. Pentland, "Eigenfaces for recognition", Journal of
cognitive neuroscience, Vol. 3, No. 1, 1991, pp. 71-86.
[5] D. Tampe, "Heuristic filtering and reliable calibration methods for video
based pupil-tracking systems, Instruments and Computers, 25(2), 1990,
137-142.
[6] K. Sung, and T. Poggio, "Example-based learning for view-based human
face detection", IEEE Transactions on Pattern Analysis and Machine
Intelligence ,Vol. 20, No. 1, 1998, pp. 39-50.
[7] K. Lam, and Y. Hong, "Locating and extracting the eye in human face
images", Pattern Recognition, Vol. 29, No. 5, 1996, pp. 771-779.
[8] B. Moghaddam, and A. Pentland, "Face recognition using View-Based
Modular Eigenspaces", Proc. of Automatic Systems for the
Identification and Inspection of Humans, SPIE Vol. 2277, 1994.
[9] E. Peli, "Contrast in Complex Images", Journal of Optical Society, Vol.
7, No. 10, 1990, pp. 2032-2040.
[10] Y. Tae-Woong, O. Il-Seok, "A fast algorithm for tracking human faces
based on chromatic histograms", Pattern Recognition Letters, Vol. 20,
No. 10, 1999, pp. 967-978.
[11] R.C. Gonzalez, R.E. Woods, Digital image processing, Prentice Hall,
Inc., 2nd Edition, London, 2002, pp. 88-93.
[12] J. Jantzen, "Tutorial on Fuzzy Logic",
www.iau.dtu.dk/~jj/pubs/logic.pdf
[13] D. Marius, S. Pennathur, and Klint Rose, "Face detection using color
thresholding and eigenimage template matching",
ww.stanford.edu/class/ee368/Project_03/Project/reports/
[14] M.A. Bhuiyan, V. Ampornaramveth, S. Muto, and H. Ueno, "On
Tracking of Eye for Human-Robot Interface", International Journal of
Robotics and Automation, Vol. 19, No. 1, 2004, pp. 42-54.