A New Color Image Database for Benchmarking of Automatic Face Detection and Human Skin Segmentation Techniques
This paper presents a new color face image database
for benchmarking of automatic face detection algorithms and human
skin segmentation techniques. It is named the VT-AAST image
database, and is divided into four parts. Part one is a set of 286 color
photographs that include a total of 1027 faces in the original format
given by our digital cameras, offering a wide range of difference in
orientation, pose, environment, illumination, facial expression and
race. Part two contains the same set in a different file format. The
third part is a set of corresponding image files that contain human
colored skin regions resulting from a manual segmentation
procedure. The fourth part of the database has the same regions
converted into grayscale. The database is available on-line for
noncommercial use. In this paper, descriptions of the database
development, organization, format as well as information needed for
benchmarking of algorithms are depicted in detail.
[1] M. H. Yang, and D. J. Kriegman, "Detecting Faces in Images: A
Survey", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 24, No. 1, Jan. 2002, pp. 34 - 58.
[2] E. Hjelmås, and B. K. Low, "Face Detection: A Survey", Computer
Vision and Image Understanding, Vol. 83, No. 3, Sept. 2001, pp. 236-
274.
[3] H. Rowley, S. Baluja, and T. Kanade, "Neural Network-Based Face
Detection", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 20, No. 1, Jan. 1998, pp. 23-38.
[4] H. Rowley, S. Baluja, and T. Kanade, "Rotation Invariant Neural
Network-Based Face Detection", Proc. IEEE Conf. on Computer Vision
and Pattern Recognition, 1998, pp. 38-44.
[5] H. Schneiderman, and T. Kanade, "A Statistical Method for 3D Object
Detection Applied to Faces and Cars", Proc. IEEE Conference on
Computer Vision and Pattern Recognition, Vol. 1, 2000, pp. 746-751.
[6] H. Kruppa, M. A. Bauer, and B. Schiele, "Skin Patch Detection in Real-
World Images", Proc of the DAGM-Symposium, 2002, pp. 109-116.
[7] P. Viola and M. Jones., "Robust real-time face detection", International
Journal of Computer Vision (IJCV) 57(2), 2004, pp. 137-154.
[8] T. Theocharides, G. Link, N. Vijaykrishnan, M. J. Irwin, and W. Wolf,
"Embedded Hardware Face Detection", Proc. 17th International
Conference on VLSI Design, Jan. 2004, p.133.
[9] A. C. Loui, C. N. Judice, and S. Liu, "An Image Database for
Benchmarking of Automatic Face Detection and Recognition
Algorithms", Proc. IEEE Conference on Image Processing, Vol. 1, 1998,
pp.146-150.
[10] P. Sharma, and R.B. Reilly, "A Color Face Image Database for
Benchmarking of Automatic Facial Detection Algorithms", Proc. 4th
European Conference of Video/Image Processing and Multimedia
Communications, July 2003, pp, 423 - 428.
[11] P. J. Phillips, P. Rauss, and S. Der, "FERET (Face Recognition
Technology) Recognition Algorithm Development and Test Report",
Technical Report ARL-TR 995, U.S. Army Research Laboratory,
October 1996.
[12] K-K. Sung, and T. Poggio, "Example-Based Learning for View-based
Human Face Detection", IEEE Transactions on Pattern Analysis and
Machine Intelligence, Vol. 20, No. 1, Jan. 1998, pp. 39-51.
[13] A. Martinez, and R. Benavente, "The AR Face Database," Technical
Report CVC 24, Purdue Univ., 1998.
[14] R-L. Hsu, and M. Abdel-Mottaleb, "Face Detection in Colour Images",
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.
24, No. 5, May 2002, pp. 696 - 706.
[15] C. Garcia, and G. Tziritas, "Face Detection Using Quantized Skin
Colour Regions Merging and Wavelet Packet Analysis", IEEE
Transactions on Multimedia, Vol. 1, No. 3, September 1999, pp. 264 -
277.
[16] C. Lin, "Face Detection by Colour and Multilayer Feedforward Neural
Network", Proc. IEEE International Conference on Information
Acquisition, June-July 2005, pp. 518-523.
[17] K. Sandeep and A.N. Rajagopalan,"Human Face Detection in Cluttered
Color Images using Skin Color and Edge Information", Proc. Indian
Conference on Computer Vision, Graphics and Image Processing, Dec.
2002.
[18] U.S. Census Bureau, 2000 Census of Population, Public Law 94-171
http://factfinder.census.gov/.
[19] Y. Wei, X. Bing, and C. Chareonsak, "FPGA Implementation of
ADABOOST Algorithm for Detection of Face Biometrics", Proc. IEEE
International Workshop on Biomedical Circuits and Systems, Dec. 2004,
pp. S1/6.17-20.
[20] E. Osuna, R. Freund, and F. Girosit, "Training Support Vector
Machines: An Application to Face Detection", Proc. IEEE Computer
Society Conference on Computer Vision and Pattern Recognition, June
1997, pp. 130-136.
[21] Yongmen Li, S. Gong, and H. Liddell, "Support Vector Regression and
Classification-based Multi-view Face Detection and Recognition", Proc.
4th IEEE International Conference on Automatic Face and Gesture
Recognition, March 2000, pp. 300-305.
[22] Adobe Photoshop CS2, http://www.adobe.com/products/photoshop/.
[23] O. Bernier, M. Collobert, R. Feraud, V. Lemaire, J. E. Viallet, and D.
Collobert, "MULTRAK: A System for Automatic Multiperson
Localization and Tracking in Real-time", Proc. International Conference
on Image Processing, ICIP 98. Vol. 1, Oct. 1998, pp. 136-140.
[24] S.Z. Li and Z. Zhang, "FloatBoost Learning and Statistical Face
Detection", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 26, Issue 9, Sept. 2004, pp. 1112-1123.
[25] S.Z. Li, L. Zhu, Z. Zhang, and H.-J. Zhang, "Learning to Detect Multiview
Faces in Real-time", Proc. 2nd International Conference on
Development and Learning, June 2002, pp. 172-177.
[26] Microsoft Office Excel, http://office.microsoft.com/enus/
excel/default.aspx.
[27] Microsoft Office Access, http://office.microsoft.com/enus/
access/default.aspx.
[28] Matlab Online, http://www.mathworks.com/products/matlab/.
[29] T. Theocharides, N. Vijaykrishnan, and M. J. Irwin, "A Parallel
Architecture for Hardware Face Detection", Proc. IEEE Computer
Society Annual Symposium on Emerging VLSI Technologies and
Architectures, March 2006.
[30] Computer Vision laboratory, Faculty of Computer and Information
Science, University of Ljubljana, Slovenia, http://www.lrv.fri.unilj.
si/facedb.html.
[1] M. H. Yang, and D. J. Kriegman, "Detecting Faces in Images: A
Survey", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 24, No. 1, Jan. 2002, pp. 34 - 58.
[2] E. Hjelmås, and B. K. Low, "Face Detection: A Survey", Computer
Vision and Image Understanding, Vol. 83, No. 3, Sept. 2001, pp. 236-
274.
[3] H. Rowley, S. Baluja, and T. Kanade, "Neural Network-Based Face
Detection", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 20, No. 1, Jan. 1998, pp. 23-38.
[4] H. Rowley, S. Baluja, and T. Kanade, "Rotation Invariant Neural
Network-Based Face Detection", Proc. IEEE Conf. on Computer Vision
and Pattern Recognition, 1998, pp. 38-44.
[5] H. Schneiderman, and T. Kanade, "A Statistical Method for 3D Object
Detection Applied to Faces and Cars", Proc. IEEE Conference on
Computer Vision and Pattern Recognition, Vol. 1, 2000, pp. 746-751.
[6] H. Kruppa, M. A. Bauer, and B. Schiele, "Skin Patch Detection in Real-
World Images", Proc of the DAGM-Symposium, 2002, pp. 109-116.
[7] P. Viola and M. Jones., "Robust real-time face detection", International
Journal of Computer Vision (IJCV) 57(2), 2004, pp. 137-154.
[8] T. Theocharides, G. Link, N. Vijaykrishnan, M. J. Irwin, and W. Wolf,
"Embedded Hardware Face Detection", Proc. 17th International
Conference on VLSI Design, Jan. 2004, p.133.
[9] A. C. Loui, C. N. Judice, and S. Liu, "An Image Database for
Benchmarking of Automatic Face Detection and Recognition
Algorithms", Proc. IEEE Conference on Image Processing, Vol. 1, 1998,
pp.146-150.
[10] P. Sharma, and R.B. Reilly, "A Color Face Image Database for
Benchmarking of Automatic Facial Detection Algorithms", Proc. 4th
European Conference of Video/Image Processing and Multimedia
Communications, July 2003, pp, 423 - 428.
[11] P. J. Phillips, P. Rauss, and S. Der, "FERET (Face Recognition
Technology) Recognition Algorithm Development and Test Report",
Technical Report ARL-TR 995, U.S. Army Research Laboratory,
October 1996.
[12] K-K. Sung, and T. Poggio, "Example-Based Learning for View-based
Human Face Detection", IEEE Transactions on Pattern Analysis and
Machine Intelligence, Vol. 20, No. 1, Jan. 1998, pp. 39-51.
[13] A. Martinez, and R. Benavente, "The AR Face Database," Technical
Report CVC 24, Purdue Univ., 1998.
[14] R-L. Hsu, and M. Abdel-Mottaleb, "Face Detection in Colour Images",
IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.
24, No. 5, May 2002, pp. 696 - 706.
[15] C. Garcia, and G. Tziritas, "Face Detection Using Quantized Skin
Colour Regions Merging and Wavelet Packet Analysis", IEEE
Transactions on Multimedia, Vol. 1, No. 3, September 1999, pp. 264 -
277.
[16] C. Lin, "Face Detection by Colour and Multilayer Feedforward Neural
Network", Proc. IEEE International Conference on Information
Acquisition, June-July 2005, pp. 518-523.
[17] K. Sandeep and A.N. Rajagopalan,"Human Face Detection in Cluttered
Color Images using Skin Color and Edge Information", Proc. Indian
Conference on Computer Vision, Graphics and Image Processing, Dec.
2002.
[18] U.S. Census Bureau, 2000 Census of Population, Public Law 94-171
http://factfinder.census.gov/.
[19] Y. Wei, X. Bing, and C. Chareonsak, "FPGA Implementation of
ADABOOST Algorithm for Detection of Face Biometrics", Proc. IEEE
International Workshop on Biomedical Circuits and Systems, Dec. 2004,
pp. S1/6.17-20.
[20] E. Osuna, R. Freund, and F. Girosit, "Training Support Vector
Machines: An Application to Face Detection", Proc. IEEE Computer
Society Conference on Computer Vision and Pattern Recognition, June
1997, pp. 130-136.
[21] Yongmen Li, S. Gong, and H. Liddell, "Support Vector Regression and
Classification-based Multi-view Face Detection and Recognition", Proc.
4th IEEE International Conference on Automatic Face and Gesture
Recognition, March 2000, pp. 300-305.
[22] Adobe Photoshop CS2, http://www.adobe.com/products/photoshop/.
[23] O. Bernier, M. Collobert, R. Feraud, V. Lemaire, J. E. Viallet, and D.
Collobert, "MULTRAK: A System for Automatic Multiperson
Localization and Tracking in Real-time", Proc. International Conference
on Image Processing, ICIP 98. Vol. 1, Oct. 1998, pp. 136-140.
[24] S.Z. Li and Z. Zhang, "FloatBoost Learning and Statistical Face
Detection", IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. 26, Issue 9, Sept. 2004, pp. 1112-1123.
[25] S.Z. Li, L. Zhu, Z. Zhang, and H.-J. Zhang, "Learning to Detect Multiview
Faces in Real-time", Proc. 2nd International Conference on
Development and Learning, June 2002, pp. 172-177.
[26] Microsoft Office Excel, http://office.microsoft.com/enus/
excel/default.aspx.
[27] Microsoft Office Access, http://office.microsoft.com/enus/
access/default.aspx.
[28] Matlab Online, http://www.mathworks.com/products/matlab/.
[29] T. Theocharides, N. Vijaykrishnan, and M. J. Irwin, "A Parallel
Architecture for Hardware Face Detection", Proc. IEEE Computer
Society Annual Symposium on Emerging VLSI Technologies and
Architectures, March 2006.
[30] Computer Vision laboratory, Faculty of Computer and Information
Science, University of Ljubljana, Slovenia, http://www.lrv.fri.unilj.
si/facedb.html.
@article{"International Journal of Information, Control and Computer Sciences:57327", author = "Abdallah S. Abdallah and Mohamad A bou El-Nasr and A. Lynn Abbott", title = "A New Color Image Database for Benchmarking of Automatic Face Detection and Human Skin Segmentation Techniques", abstract = "This paper presents a new color face image database
for benchmarking of automatic face detection algorithms and human
skin segmentation techniques. It is named the VT-AAST image
database, and is divided into four parts. Part one is a set of 286 color
photographs that include a total of 1027 faces in the original format
given by our digital cameras, offering a wide range of difference in
orientation, pose, environment, illumination, facial expression and
race. Part two contains the same set in a different file format. The
third part is a set of corresponding image files that contain human
colored skin regions resulting from a manual segmentation
procedure. The fourth part of the database has the same regions
converted into grayscale. The database is available on-line for
noncommercial use. In this paper, descriptions of the database
development, organization, format as well as information needed for
benchmarking of algorithms are depicted in detail.", keywords = "Image database, color image analysis, facedetection, skin segmentation.", volume = "1", number = "12", pages = "3897-5", }
