A rough fuzzy neural network approach for robust face detection and tracking - Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition - page 253

FIGURE 15 Face tracking of a subject under various complex motion and partial occlusion.
FIGURE 16 The motion signature obtained by tracing the center point of the face detected in
each frame.
8 Conclusions and Future Works
A new method for face tracking and detection has been presented in this study, which has
been designed to detect frontal faces in color images without a priori knowledge about the
number of faces or the size of the faces in a given image. All our experiment results show that
the proposed method can obtain high detection rates in the presence of both simple and com-
plex backgrounds. SM detection may not be suitable for certain cases, such as when there are
colors in the image that resemble the skin, but are not skin pixels. To overcome this problem
OM transform could be employed to correctly detect the face region in the SM image. The on-
going work involves increasing the speed of our proposed method as well as adopting par-
allel processing provided by GPUs. In addition, the method is also being adopted as a pre-
processor for a face recognition system, such that false positives may be rejected by the face
validation process of the recognition system.
References
[1] Sun YB, Kim JT, Lee WH. Extraction of face objects using skin color information. In: Pro-
ceedings of the IEEE international conference on communications, circuits and sys-
tems and West Sino expositions; 2002:1136-1140.
[2] Soriano M, Martinkauppi B, Huovinen S, Laaksonen M. Adaptive skin color model-
ing using the skin locus for selecting training pixels. Patern Recogn. 2003;36(3):681-690.
[3] Viola P, Jones MJ. Robust real-time face detection. Int J Comput Vis.
2004;57(2):137-154.
[4] Lienhart R, Maydt J. An extended set of Haar-like features for rapid object detection.
900-903. Proceedings of the IEEE international conference on image processing. 2002;vol. 1.
[5] Rowley H, Baluja S, Kanade T. Neural network-based face detection. IEEE Trans Pat-
tern Anal Mach Intell. 1998;20(1):23-38.
[6] Sun Z, Bebis G, Miller R. Object detection using feature subset selection. Patern Re-
cogn. 2004;37(11):2165-2176.
[7] Juang CF, Chang SW. Fuzzy system-based real-time face tracking in a multi-subject
environment with a pan-tilt-zoom camera. Expert Syst Appl. 2010;37(6):4526-4536.