Issue No. 07 - July (1997 vol. 19)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.598235
We present a system for recognizing human faces from single images out of a large database containing one image per person. Faces are represented by labeled graphs, based on a Gabor wavelet transform. Image graphs of new faces are extracted by an elastic graph matching process and can be compared by a simple similarity function. The system differs from the preceding one (Lades et al., 1993) in three respects. Phase information is used for accurate node positioning. Object-adapted graphs are used to handle large rotations in depth. Image graph extraction is based on a novel data structure, the bunch graph, which is constructed from a small get of sample image graphs.
spatial data structures, face recognition, wavelet transforms, visual databases, graph theory,data structure, face recognition, elastic bunch graph matching, large database, labeled graphs, Gabor wavelet transform, image graphs, phase information, node positioning, object-adapted graphs,Face recognition, Image databases, Image recognition, Wavelet transforms, Data mining, Data structures, Wavelet coefficients, Biology computing, Computer science, Frequency
"Face recognition by elastic bunch graph matching", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 19, no. , pp. 775-779, July 1997, doi:10.1109/34.598235