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Person Identification Using Fast Face Learning of Lifting Dyadic Wavelet Filters

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Computer Recognition Systems

Part of the book series: Advances in Soft Computing ((AINSC,volume 30))

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Abstract

A person identification system based on fast face learning of lifting wavelet filters is proposed. The real power of our system lies in fast learning of lifting wavelet filters adaptive to facial parts such as eyes, nose and lips, in a set of training faces. In our system, free parameters in the lifting filter are learned fast by using Newton’s method. The learned parameters are memorized in a database together with the training faces. The lifting filters with the learned parameters in the database are applied to each of video frames which contain faces of a person, and the faces are detected by measuring some kind of distance. A person whose face is detected in a maximum number of frames is identified as a target person. To realize fast face detection, the learned filters are applied only to the skin areas separated from background by using color segmentation. Simulation results show that our person identification algorithm is accurate and fast.

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References

  1. Chai D. and Ngan K.N. (1998), Locating Facial Region of a Head-and-shoulders Color Image, Proceedings of the Third International Conference Automatic Face and Gesture Recognition, pp. 124–129.

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  2. Takano S., Niijima K. and Abdukirim T. (2003), Fast Face Detection by Lifting Dyadic Wavelet Filters, Proceedings of the IEEE International Conference on Image Processing, pp. 893–896.

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  3. Takano S., Niijima K. and Kuzume K. (2004), Personal Identification by Multiresolution Analysis of Lifting Dyadic Wavelets, Proceedings of the 12th European Signal Processing Conference, CD-ROM.

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  4. Yang M.-H., Kriegman D. and Ahuja N. (2002), Detecting Faces in Images: A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 24, no. 1, pp. 34–58.

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© 2005 Springer-Verlag Berlin Heidelberg

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Takano, S., Niijima, K. (2005). Person Identification Using Fast Face Learning of Lifting Dyadic Wavelet Filters. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_96

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  • DOI: https://doi.org/10.1007/3-540-32390-2_96

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25054-8

  • Online ISBN: 978-3-540-32390-7

  • eBook Packages: EngineeringEngineering (R0)

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