Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Edge Detection and Ridge Detection with Automatic Scale Selection
International Journal of Computer Vision
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Fundamental Frequency Gabor Filters for Object Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Simple Gabor feature space for invariant object recognition
Pattern Recognition Letters
Gabor parameter selection for local feature detection
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
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We propose models based on Gabor functions to address two related aspects in the object recognition problem: interest point selection and classification. We formulate the interest point selection problem by a cascade of bottom-up and top-down stages. We define a novel type of top-down saliency operator to incorporate low-level object related knowledge very soon in the recognition process, thus reducing the number of canditates. For the classification process, we represent each interest point by a vector of Gabor responses whose parameters are automatically selected. Both the selection and classification procedures are designed to be invariant to rotations and scaling. We apply the approach to the problem of facial landmark classification and present experimental result illustrating the performance of the proposed techniques.