Design of Face Image Retrieval System

YIN Bao-cai; SU Shi-qian

Journal of Beijing University of Technology > 2005 > 31(4): 337-341.

YIN Bao-cai, SU Shi-qian. Design of Face Image Retrieval System[J]. Journal of Beijing University of Technology, 2005, 31(4): 337-341.

Citation:

YIN Bao-cai, SU Shi-qian. Design of Face Image Retrieval System[J]. Journal of Beijing University of Technology, 2005, 31(4): 337-341.

Citation:

YIN Bao-cai, SU Shi-qian. Design of Face Image Retrieval System[J]. Journal of Beijing University of Technology, 2005, 31(4): 337-341.

PDF (352 KB)

Design of Face Image Retrieval System

Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science, Beijing University of Technology, Beijing 100022, China

More Information

Received Date: June 08, 2004
Available Online: November 21, 2022

Graphical Abstract

Abstract

Abstract

To retrieval directly information with images, by using the face detection technique based on the gravity-center template matching method and the face recognition technique based on methods of the principal component analysis and the linear discriminative analysis. To the given video sequence, the system can retrieve face image from big face image database on time. Experimental results show that the system is provided with good human-machine interface, high retrieval rate, short retrieval time and can well satisfy the user's requirements.
- content-based image retrieval,
- face detection,
- face recognition

FullText(HTML)

References (12)

References

[1]	YANG M H, KRIEGMAN D, AHUJA N. Detecting faces in images:A survey[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2002, 24(1):34-58.
[2]	GOVINDARAJU V, SRIHARI S N, SHER D B. A computational model for face location[A]. Proc IEEE Conf Computer Vision[C]. San Jose, CA:IEEE Computer Society Press, 1990. 718-721.
[3]	HSU Rein-lien, ABDEL-MOTTALEB Mohamed, JAIN A K. Face detection in color images[J]. IEEE Trans Pattern Anal ysis and Machine Intelligence, 2002, 21(5):696-706.
[4]	MIAO J, YIN B, WANG K, et al. A hierarchical multiscale and multiangle system for human face detection in a complex background using gravity-center template[J]. Pattern Recognition, 1999, 32(7):1237-1248.
[5]	ROWLEY Henry A, BALUJA Shumeet, KANADE Takeo. Neural network-based face detection[J]. IEEE Translation on Pattern Analysis and Machine Intelligence, 1998, 20(1):29-38.
[6]	OSUNA Edgar, FREUND Robert, GIROSI Federico. Training support vector machines:An application to face detection[A]. Proc IEEE Conf Computer Vision and Pattern Recognition[C]. San Juan, PR:IEEE Computer Society Press, 1997. 130-136.
[7]	VIOLA Paul, JONES Michael J. Rapid object detection using a boosted cascade of simple featrues[A]. Proc IEEE Conf Computer Vision and Pattern Recognition[C]. Kauai, HI:IEEE Computer Society Press, 2001. 511-518.
[8]	LIU Ce, SHUM Hueng-yeung. Kullback-leibler boosting[A]. Proc IEEE Conf Computer Vision and Pattern Recognition[C]. Madison, WI:IEEE Computer Society Press, 2003. 587-594.
[9]	MANJUNATH B S, CHELLAPPA R, MALSBURG C V D. A feature based approach to face recognition[A]. Proc IEEE Conf Computer Vision and Pattern Recognition[C]. Champaign, IL:IEEE Computer Society Press, 1992. 373-378.
[10]	TURK M, PENTLANDA. Eigen-faces for recognition[J]. Journal of Cognitive Neuroscience, 1991, 3(1):71-86.
[11]	BELHUMEUR Peter N, HESPANHA Joao, DAVID J. Kriegman eigenfaces vs. fisherfaces:Recognition using class specific linear projection[J]. IEEE Trans Pattern Analysis and Machine Intelligence, 2001, 23(2):228-233.
[12]	BRUNELLI R, FALAVIGNA D, POGGIO T, et al. Automatic person recognition by acoustic and geometric features[J]. Machine Vision and Applications, 1995, 8:317-325.

Cited By

Get Citation

PDF

XML

Article views (21) PDF downloads (6)

Turn off MathJax

Article Contents

Abstract

References

Design of Face Image Retrieval System

Abstract

References

Catalog

Export File

Citation

Format

Content