Abstract
We present an attention-based face detection and localization system. The system is biologically motivated, combining face detection based on second-order circular patterns with the localization capabilities of the Selective Tuning (ST) model of visual attention [1]. One of the characteristics of this system is that the face detectors are relatively insensitive to the scale and location of the face, and thus additional processing needs to be performed to localize the face for recognition. We extend ST’s ability to recover spatial information to this object recognition system, and show how this can be used to precisely localize faces in images. The system presented in this paper exhibits temporal characteristics that are qualitatively similar to those of the primate visual system in that detection and categorization is performed early in the processing cycle, while detailed information needed for recognition is only available after additional processing, consistent with experimental data and with certain theories of visual object recognition [2].
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Rothenstein, A.L., Zaharescu, A., Tsotsos, J.K. (2006). Second-Order (Non-Fourier) Attention-Based Face Detection. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840930_54
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DOI: https://doi.org/10.1007/11840930_54
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