Artificial Intelligence - Special volume on computer vision
Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Introduction to Algorithms
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Enhancing security and privacy in biometrics-based authentication systems
IBM Systems Journal - End-to-end security
Interest point detection using imbalance oriented selection
Pattern Recognition
A hybrid representation of imbalanced points for two-layer matching
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Contour Extraction of Drosophila Embryos
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Imbalanced points are image points whose first-order intensity can be clustered into two imbalanced classes. An important property of imbalanced points is that they can be contiguous to each other. The property helps improve the localization accuracy of imbalanced points across imaging variations. Based on this local geometric coherency property, we propose a global-to-local scheme for imbalanced point matching. The proposed matching scheme first builds correspondence between components of coherent imbalanced points and then refines point correspondence within corresponding components. We test the global-to-local matching scheme, compared with several other well-known methods, on a set of groundtruth stereo images. Furthermore, we present a case study of the proposed scheme in face liveness detection. Our results show the promise of the global-to-local matching scheme.