Locating Facial Features in Image Sequences using Neural Networks

F
FG
1996
Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96)
Abstract - Locating Facial Features in Image Sequences using Neural Networks

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	Similar Articles Articles by M.J.T. Reinders Articles by R.W.C. Koch Articles by J.J. Gerbrands

Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96)

Killington, Vermont

October 14-October 16

ISBN: 0-8186-7713-9

	ASCII Text	x
	M.J.T. Reinders, R.W.C. Koch, J.J. Gerbrands, "Locating Facial Features in Image Sequences using Neural Networks," Automatic Face and Gesture Recognition, IEEE International Conference on, pp. 230, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996.

	BibTex	x
	@article{ 10.1109/AFGR.1996.557269, author = {M.J.T. Reinders and R.W.C. Koch and J.J. Gerbrands}, title = {Locating Facial Features in Image Sequences using Neural Networks}, journal ={Automatic Face and Gesture Recognition, IEEE International Conference on}, volume = {0}, year = {1996}, isbn = {0-8186-7713-9}, pages = {230}, doi = {http://doi.ieeecomputersociety.org/10.1109/AFGR.1996.557269}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Automatic Face and Gesture Recognition, IEEE International Conference on TI - Locating Facial Features in Image Sequences using Neural Networks SN - 0-8186-7713-9 SP EP A1 - M.J.T. Reinders, A1 - R.W.C. Koch, A1 - J.J. Gerbrands, PY - 1996 VL - 0 JA - Automatic Face and Gesture Recognition, IEEE International Conference on ER -

M.J.T. Reinders, Delft University of Technology\

R.W.C. Koch, Delft University of Technology\

J.J. Gerbrands, Delft University of Technology\

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AFGR.1996.557269

This paper describes a method for the automatic location of facial features, such as eyes, nose and mouth, in image sequences using a neural network approach. It is shown that by modeling the feature sought as a structural assembly of micro-features, and by using a probabilistic interpretation of neural network outputs, it is possible to construct a location system that is more robust than a location system which uses the feature as a single entity. With this micro-feature approach, not only the position of the features can be found, but also the shape of the features.

Citation:

M.J.T. Reinders, R.W.C. Koch, J.J. Gerbrands, "Locating Facial Features in Image Sequences using Neural Networks," fg, pp.230, Second IEEE International Conference on Automatic Face and Gesture Recognition (FG '96), 1996

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