Abstract
This work proposed a new multi-view combined visual similarity retrieval approach for face database. The search and retrieval employ a novel facial corner coding and matching approach, which delivers fast searching speed for database retrieval. The experimental results demonstrate that the facial corners can be a useful identity feature for human face database retrieval. The profile view of a face provides a complementary structure of the face that is not seen in the frontal view. The proposed multi-view modified Hausdorff distance combines the facial corners of multiple views and achieved an improved accuracy. This technique is not limited to two view combined retrieval but a generic approach for multiple view combined similarity retrieval.
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Gao, Y., Leung, M.K.H. (2002). Multi-View Combined Visual Similarity Retrieval for Face Database. In: Zhou, X., Pu, P. (eds) Visual and Multimedia Information Management. VDB 2002. IFIP — The International Federation for Information Processing, vol 88. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35592-4_26
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DOI: https://doi.org/10.1007/978-0-387-35592-4_26
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