Abstract
While traditional face recognition is typically based on still images, face recognition from video sequences has become popular recently. To achieve the high accuracy of the face detection, we introduce a visual perception model that aims at quantifying the local tolerance to noise for arbitrary imagery. Based on this model, extract the features of video frame, the two-dimensional statistical parameters and new standard deviation from DCT coefficients without its inverse transform was computed. Results are reported for a database comprising 940 face images of 34 video clips under a variety of challenging circumstances. These results indicate significant performance improvements over previous methods and demonstrate the usefulness of the confidence data.
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© 2012 Springer-Verlag GmbH Berlin Heidelberg
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Wang, J. (2012). Video-Based Face Detection Using New Standard Deviation. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29387-0_29
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DOI: https://doi.org/10.1007/978-3-642-29387-0_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29386-3
Online ISBN: 978-3-642-29387-0
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