Abstract
In this work, we address the issue of encoding and recognition of face sequences that arise from continuous head movement. We detect and track a moving head before segmenting face images from on-line camera inputs. We measure temporal changes in the pattern vectors of eigenface projections of successive image frames of a face sequence and introduce the concept of “temporal signature” of a face class. We exploit two different supervised learning algorithms with feedforward and partially recurrent neural networks to learn possible temporal signatures. We discuss our experimental results and draw conclusions.
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© 1995 British Computer Society
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Gong, S., Psarrou, A., Katsoulis, I., Palavouzis, P. (1995). Tracking and Recognition of Face Sequences. In: Paker, Y., Wilbur, S. (eds) Image Processing for Broadcast and Video Production. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3035-2_8
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DOI: https://doi.org/10.1007/978-1-4471-3035-2_8
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