Abstract

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.

Keywords

Artificial intelligenceComputer sciencePattern recognition (psychology)Facial recognition systemWavelet transformComputer visionGraphFeature extractionWaveletTheoretical computer science

Affiliated Institutions

Related Publications

Publication Info

Year
1997
Type
article
Volume
19
Issue
7
Pages
775-779
Citations
2882
Access
Closed

External Links

View on DOI.org

Social Impact

Altmetric
PlumX Metrics

Social media, news, blog, policy document mentions

Citation Metrics

2882
OpenAlex

Cite This

Laurenz Wiskott, Jean‐Marc Fellous, N. Kuiger et al. (1997). Face recognition by elastic bunch graph matching. IEEE Transactions on Pattern Analysis and Machine Intelligence , 19 (7) , 775-779. https://doi.org/10.1109/34.598235

Identifiers

DOI
10.1109/34.598235