Representation of local geometry in the visual system
Biological Cybernetics
International Journal of Computer Vision
The Structure of Locally Orderless Images
International Journal of Computer Vision
Object Recognition Using Multidimensional Receptive Field Histograms
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Face recognition: component-based versus global approaches
Computer Vision and Image Understanding - Special issue on Face recognition
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Learning to Detect Objects in Images via a Sparse, Part-Based Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition with Features Inspired by Visual Cortex
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Oriented filters for object recognition: an empirical study
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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This paper presents a technique to enable deformable objects to be matched throughout video sequences based on the information provided by multi-scale Gaussian derivative filter banks. We show that this technique is robust enough for viewpoint changes, lighting changes, large motions of the matched object and small changes in rotation and scale. Unlike other well-known color-based techniques, this technique only uses the gray level values of the image. The proposed algorithm is mainly based on the definition of a particular multi-scale template model and a similarity measure for template matching. The matching approach has been tested on video sequences acquired with a conventional webcam showing a promising behavior with this kind of low-quality images