Face Recognition by Elastic Bunch Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Robust Real-Time Face Detection
International Journal of Computer Vision
The Application of DWT and SVD in Image Retrieval
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 2 - Volume 02
FaceTracer: A Search Engine for Large Collections of Images with Faces
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
A Matching Method Based on SVD for Image Retrieval
ICMTMA '09 Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01
Robust visual similarity retrieval in single model face databases
Pattern Recognition
Face matching and retrieval using soft biometrics
IEEE Transactions on Information Forensics and Security
Scalable Face Image Retrieval with Identity-Based Quantization and Multireference Reranking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition using difference vector plus KPCA
Digital Signal Processing
Face Matching and Retrieval in Forensics Applications
IEEE MultiMedia
Face image retrieval by shape manipulation
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Face Verification Using Template Matching
IEEE Transactions on Information Forensics and Security - Part 2
An SVD---Bypass latent semantic analysis for image retrieval
MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
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In this paper, an efficient method based on singular values and potential-field representation is proposed for face-image retrieval. Firstly, we theoretically prove that the leading singular values of an image can be used as a rotation-shift-scale-invariant global feature. Then, for the feature-extraction stage, we exploit these special properties of the singular values to devise a compact, global feature for face-image representation. We also use the singular values of the potential field derived from edge gradients to enhance the retrieval performance. Experimental results based on the GTAV database show that the use of singular values as rotation-shift-scale-invariant global features is able to produce plausible retrieval results.