Face detection in color images with complex background

Image analysis – Color image processing – Image segmentation using color

Reexamination Certificate

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

C382S118000

Reexamination Certificate

active

07035456

ABSTRACT:
A method (100) of locating human faces, if present, in a cluttered scene captured on a digital image (105) is disclosed. The method (100) relies on a two step process, the first being the detection of segments with a high probability of being human skin in the color image (105), and to then determine a bounday box, or other boundary indication, to border each of those segments. The second step (140) is the analysis of features within each of those boundary boxes to determine which of the segments are likely to be a human face. As human skin is not highly textured, in order to detect segments with a high probability of being human skin, a binary texture map (121) is formed from the image (105), and segments having high texture are discarded.

REFERENCES:
patent: 6571003 (2003-05-01), Hillebrand et al.
patent: 6633655 (2003-10-01), Hong et al.
patent: 6697502 (2004-02-01), Luo
patent: 6718049 (2004-04-01), Pavlidis et al.
patent: 6940545 (2005-09-01), Ray et al.
patent: 6959099 (2005-10-01), Gutta et al.
patent: 2003/0053685 (2003-03-01), Lestideau
“Direct Least Square Fitting of Ellipses”, Fitzgibbon, et al., IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, No. 5, May 1999, pp. 476-480.
Yow, Kin Choong and Cipolla, Robert,Feature-Based Human Face Detection, CUED/F-INFENG/TR 249, University of Cambridge, England (Aug. 1996).
Andrew W. Fitzgibbon, et al., “Direct Least Square Fitting of Ellipses”, Department of Artificial Intelligence, University of Edinburgh (Jan. 4, 1996), pp. 1-15.
Kah-Kay Sung, et al., “Example-based Learning for View-based Human Face Detection”, Massachusetts Institute of Technology, Artificial Intelligence Laboratory and Center for Biological and Computational Learning, A.I. Memo No. 1521, C.B.C.L. Paper No. 112, (Dec. 1994), pp. 1-20.
Bernd Menser, et al., “Segmentation and Tracking of Facial Regions in Color Image Sequences” (2000), pp. 1-10.
Jay P. Kapur, “Face Detection in Color Images”, University of Washington Department of Electrical Engineering (1997), pp. 1-7.
Marc Antonini, et al., “Image Coding Using Wavelet Transform”,IEEE Transactions of Image Processing, vol. 1, No. 2 (Apr. 1992), pp. 205-220.
Kin Choong Yow, et al., “Feature-Based Human Face Detection”,Image and Vision Computing, vol. 15, No. 9 (1997), pp. 713-735 (renumbered as pp. 1-30).
Jean-Christophe Terrillon, et al., “Detection of Human Faces in Complex Scene Images by Use of a Skin Color Model and of Invariant Fourier-Mellin Moments”, ICPR '98, IEEE (1998), pp. 1350-1355.
Bernd Menser, et al., “Segmentation of Human Faces in Color Images Using Connected Operators” (1999), pp. 1-5.
Nicholas J. Redding, et al.,“An Efficient Algorithm for Mumford-Shah segmentation and its application to SAR Imagery”, Defence Science and Technology Organisation, Australia (1999), pp. 35-41.
G. Koepfler, et al., “A Multiscale Algorithm for Image Segmentation by Variational Method”,SIAM J. Numer. Numer. Anal., vol. 31, No. 1 (1994), pp. 282-299.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Face detection in color images with complex background does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Face detection in color images with complex background, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Face detection in color images with complex background will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-3528832

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.