Face Localization in the Neural Abstraction Pyramid
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Author: Sven Behnke
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In Proceedings of Seventh International Conference on Knowledge-Based Intelligent
Information & Engineering Systems (KES'03), Oxford, UK, LNAI 2774,
vol. 2, pp. 139-145, September 2003.
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Abstract:
One of the major parts in human-computer interface applications, such
as face recognition and video-telephony, consists in the localization of
a face in an image.
I propose to use hierarchical neural networks with local recurrent
connectivity to solve this task, even in presence of complex backgrounds,
difficult lighting, and noise. The network is trained using a database
of gray-scale still images and manually determined eye coordinates. It
is able to produce reliable and accurate eye coordinates for unknown images
by iteratively refining an initial solution.
Since the network processes an entire image, no time consuming scanning
across positions and scales is needed. Its fast update allows for real-time
face tracking.
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Full paper: kes03.pdf
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