Abstract
This paper presents a robust and simple metric approach named Force Work Induced Metric (FWIM) according to a Physical model. A novel image local descriptor based on FWIM (FWIM-LD) is then introduced for face verification. FWIM-LD captures the local structure information between central pixel and its neighbors effectively. PCA thus is used to obtain the low-dimensional and significant features. Subsequently, we employ the binary-like face representation method to further improve the face verification rate. Experimental results on the challenging benchmark “Labeled Faces in the Wild” (LFW) dataset demonstrate that the proposed method achieves better performance than the state-of-the-art algorithms.
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Qian, J., Yang, J., Yang, Z., Wang, W. (2013). Force Work Induced Metric for Face Verification. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_37
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DOI: https://doi.org/10.1007/978-3-642-36669-7_37
Publisher Name: Springer, Berlin, Heidelberg
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