Abstract
We present an efficient technique for face detection that filters the face-like regions from a gray image and then detects the faces using Support Vector Machines (SVM) from these potential regions. The technique focusses on extracting the probable eye-regions since eyes are the most prominent features of a face. The probable location of eyes is used to segment a square region constituting face-like region from the image. The extracted regions are verified using a single SVM for making binary decision: face/non-face. Experimental results show that the proposed face detection system is several orders of magnitude faster than the existing SVM-based systems.
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© 2004 Springer-Verlag Berlin Heidelberg
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Suguna, R., Sudha, N., Chandra Sekhar, C. (2004). A Fast and Efficient Face Detection Technique Using Support Vector Machine. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_51
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DOI: https://doi.org/10.1007/978-3-540-30499-9_51
Publisher Name: Springer, Berlin, Heidelberg
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