Phase-based disparity measurement
CVGIP: Image Understanding
Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Person identification based on multiscale matching of cortical images
HPCN Europe '95 Proceedings of the International Conference and Exhibition on High-Performance Computing and Networking
Edge and Keypoint Detection in Facial Regions
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Face Detection and Facial Feature Extraction in Color Image
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
Multi-scale cortical keypoint representation for attention and object detection
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Visual routines for eye location using learning and evolution
IEEE Transactions on Evolutionary Computation
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
A multi-scale visual salient feature points extraction method based on Gabor wavelets
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Face recognition by cortical multi-scale line and edge representations
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
3D human face description: landmarks measures and geometrical features
Image and Vision Computing
| Hi-index | 0.00 |
End-stopped cells in cortical area V1, which combine outputs of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. In this paper we study the importance of the multi-scale keypoint representation, i.e. retinotopic keypoint maps which are tuned to different spatial frequencies (scale or Level-of-Detail). We show that this representation provides important information for Focus-of-Attention (FoA) and object detection. In particular, we show that hierarchically-structured saliency maps for FoA can be obtained, and that combinations over scales in conjunction with spatial symmetries can lead to face detection through grouping operators that deal with keypoints at the eyes, nose and mouth, especially when non-classical receptive field inhibition is employed. Although a face detector can be based on feedforward and feedback loops within area V1, such an operator must be embedded into dorsal and ventral data streams to and from higher areas for obtaining translation-, rotation- and scale-invariant face (object) detection.