Image analysis – Color image processing – Pattern recognition or classification using color
Reexamination Certificate
2007-03-13
2007-03-13
Miriam, Daniel (Department: 2624)
Image analysis
Color image processing
Pattern recognition or classification using color
C382S118000
Reexamination Certificate
active
10610245
ABSTRACT:
Improved methods and apparatuses are provided for use in face detection. The methods and apparatuses significantly reduce the number of candidate windows within a digital image that need to be processed using more complex and/or time consuming face detection algorithms. The improved methods and apparatuses include a skin color filter and an adaptive non-face skipping scheme.
REFERENCES:
patent: 6148092 (2000-11-01), Qian
patent: 6574354 (2003-06-01), Abdel-Mottaleb et al.
patent: 7110575 (2006-09-01), Chen et al.
Garcia, et al “Face Detection Using Quantize Skin Color Regions Merging and Wavelet Packet Analysis” IEEE, pp. 264-277, 1999.
Viola, et al “Rapid Object Detection Using a Boosted Cascade of Simple Features”, computer vision and pattern recognition, pp. 1-9, 2001.
Gabbur “Detection and Segmentation of Human Faces in Color Images With Complex Backgrounds”, ECE#532-Computer vision project report, pp. 1-32, 2001.
Vapnik; “Statistical Learning Theory”; 1998; A Volume in the Wiley Series on Adaptive and Learning Systems for Signal Processing, Communications, andControl; Simon Haykin, Series Editor.
Fleuret et al; “Course-to-Fine Face Detection”; International Journal of Computer Vision 2001, 23 pages.
Freund et al.; “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting*”; Journal of Computer and System Sciences 55, 1997, Article No. SS971504; pp. 119-139.
Li et al.; “Statistical Learning of Multi-view Face Detection”; 15 pages. Microsoft Research Asia.
Pentland et al.; “View-Based and Modular Eigenspaces for Face Recognition”; 1994 IEEE; pp. 84-91.
Bichsel et al.; “Human Face Recognition and the Face Image Set's Topology”; Image Understanding vol. 59, No. 2, Mar. pp. 254-261, 1994.
Osuna et al.; “Training Support Vector Machines: an Application to Face Detection”; 1997 IEEE; pp. 130-136.
Hsu et al.; “Face Detection in Color Images”; 2002 IEEE; pp. 696-706.
Sung et al; “Example-Based Learning for View-Based Human Face Detection”; IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, No. 1, Jan. 1998; pp. 39-50.
Ng et al.; “Multi-View Face Detection and Pose Estimation Using A Composite Support Vector Machine accross the View Sphere”; 1999 IEEE; pp. 14-21.
Rowley et al.; “Neural Network-Based Face Detection”; IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, No. 1, Jan. 1998.
Papageorgiou et al.; “A General Framework for Object Detection”; 1998 The Institute of Electrical and Electronics Engineers, Inc.; pp. 555-563.
“The Boosting Approach to Machine Learning An Overview”, Robert E. Schapire, Dec. 19, 2001, MSRI Workshop on Nonlinear Estimation and Classification, 2002, pp. 1-23.
“Robust Real-time Object Detection”, Viola et al., Jul. 13, 2001, Second International Workshop on Statistical and Computational Theories of Vision-Modeling, Learning, Computing, and Sampling, pp. 1-25.
“Feature Selection for Face Detection”, Serre et al., Sep. 2000, Massachusetts Institute of Technology, 2000, A.I. Memo No. 1697, C.B.C.L Paper No. 192, 17 pages.
“A SNoW-Based Face Detector”, Roth et al., Department of Computer Science and the Beckman Institute, University of Illinois at Urbana-Champaign, 7 pages.
“A Statistical Method for 3D Object Detection Applied to Faces and Cars”, Schneiderman et al., Robotics Institute, Carnegie Mellon University, 6 pages.
Li Mingjing
Zhang Hong-Jiang
Zhang Lei
Lee & Hayes PLLC
Microsoft Corporation
Miriam Daniel
LandOfFree
Speedup of face detection in digital images does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Speedup of face detection in digital images, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Speedup of face detection in digital images will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3754652