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Face Detection and Localization in Color Images: An Efficient Neural Approach

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DOI: 10.4236/jsea.2011.412080    4,884 Downloads   8,398 Views   Citations

ABSTRACT

Automatic face detection and localization is a key problem in many computer vision tasks. In this paper, a simple yet effective approach for detecting and locating human faces in color images is proposed. The contribution of this paper is twofold. First, a particular reference to face detection techniques along with a background to neural networks is given. Second, and maybe most importantly, an adaptive cubic-spline neural network is designed to be used to detect and locate human faces in uncontrolled environments. The experimental results conducted on our test set show the effectiveness of the proposed approach and it can compare favorably with other state-of-the-art approaches in the literature.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, "Face Detection and Localization in Color Images: An Efficient Neural Approach," Journal of Software Engineering and Applications, Vol. 4 No. 12, 2011, pp. 682-687. doi: 10.4236/jsea.2011.412080.

References

[1] 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, 1998, pp. 39-51. doi:10.1109/34.655648
[2] K. Yow and R. Cipolla, “Feature-Based Human Face Detection,” Image and Vision Computing, Vol. 2, No. 15, 1997, pp. 713-735. doi:10.1016/S0262-8856(97)00003-6
[3] T. Cootes and C. Taylor, “Locating Faces Using Statistical Feature Detectors,” Proceeding of the Second International Conference on Automatic Face and Gesture Recognition, Killington, 14-16 October 1996, pp. 640-645. doi:10.1109/AFGR.1996.557265
[4] T. Leung, M. Burl and P. Perona, “Finding Faces in Cluttered Scenes Using Random Labeled Graph Matching,” Proceedings of the Fifth International Conference on Computer Vision, Cambridge, 20-23 June 1995, pp. 637-644.
[5] H. Rowley, S. Bluja and T. Kanade, “Neural Network-Based Face Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 1, 1998, pp. 23-38. doi:10.1109/34.655647
[6] K. Sung and T. Poggio, “Example-Based Learning for Viewbased Human Face Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 1, 1998, pp. 39-51. doi:10.1109/34.655648
[7] A. Colmenarez and T. Huang, “Face Detection with Information-Based Maximum Discrimination,” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, 17-19 June 1997, pp. 278-287.
[8] M. D. Mariscoi, L. Cinque and S. Levialdi, “Indexing Pictorial Documents by Their Content: A Survey of Current Techniques,” Image and Vision Computing, Vol. 15, No. 2, 1997, pp. 119-141. doi:10.1016/S0262-8856(96)01114-6
[9] B. Schiele and A. Waibel, “Gaze Tracking Based on Facecolor,” International Workshop on Face and Gesture Recognition, Zurich, 1995.
[10] Y. Dai and Y. Nakano, “Face-Texture Model Based on Sgld and Its Applications in Face Detection in a Color Scene,” Pattern Recognition, Vol. 29, No. 6, 1996, pp. 1007-1017. doi:10.1016/0031-3203(95)00139-5
[11] Q. Chen, H. Wu and M. Yachida, “Face Detection by Fuzzy Pattern Matching,” Proceedings of the Fifth International Conference on Computer Vision, Cambridge, 20-23 June 1995, pp. 591-596.
[12] J. Cai and A. Goshtasby, “Detecting Human Faces in Color Images,” Image and Vision Computing, Vol. 18, 1999, pp. 63-75. doi:10.1016/S0262-8856(99)00006-2
[13] Y. Miyake, H. Saitoh, H. Yaguchi and N. Tsukada, “Facial Pattern Detection and Color Correction from Television Picture and Newspaper Printing,” Journal of Imaging Technology, Vol. 16, No. 5, 1990, pp. 165-169.
[14] D. Androutsos, K. N. Plataniotois and A. N. Venet-sanopoulos, “A Novel Vector-Based Approach to Color Image Retrieval Using a Vector Angular-Based Distance Measure,” Computer Vision and Image Understanding, Vol. 75, No. 1-2, 1999, pp. 46-58. doi:10.1006/cviu.1999.0767
[15] S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, “Image Retrieval Using Cubic Spline Neural Networks,” International Journal of Video & Image Processing and Network Security (IJIPNS), Vol. 9, No. 10, 2009, pp. 17-22.
[16] S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, “Cubic-Spline Neural Network-Based System for Image Retrieval,” Proceedings of Sixth International IEEE Conference on Image Processing (ICIP’09), Cairo, 7-11 November 2009, pp. 273-276.
[17] S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, “A Robust Neural System for Objectionable Image Recognition,” Proceedings of Second International Conference on Machine Vision (ICMV2009), Dubai, 28-30 December 2009, pp. 32-36.
[18] S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, “A New Method for Image Classification Based on Multi- Level Neural Networks,” Proceedings of International Conference on Signal and Image Processing (IC-SIP2009), Amsterdam, 29 July-1 August 2009, pp. 197-200.
[19] B. Si, W. Gao, H. Lu and W. Zeng, “An Image Retrieval Method Based Regions of Interest,” High Technology Letters, Vol. 13, No. 5, 2003, pp. 13-18.
[20] S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, “An Image Classification Approach Using Multilevel Neural Networks,” Proceedings of IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS’09), Shanghai, 17-20 September 2009, pp. 180-183.
[21] S. Sadek, A. Al-Hamadi, B. Michaelis and U. Sayed, “An Efficient Approach for Region-based Image Classification and Retrieval,” Communications in Computer and Information Science, Vol. 61, 2009, pp. 56-64. doi:10.1007/978-3-642-10546-3_8
[22] D. Rumelhart, G. Hinton and R. Williams, “Learning Internal Representation by Error Propagation,” Parallel Distributed Processing: Explorations in the Microstructures of Cognition, Vol. 1, MIT Press, Cambridge, 1986.
[23] C. Bishop, “Neural Networks for Pattern Recognition,” Oxford University Press, Oxford, 1995.

  
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