A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A wavelet approach to foveating images
SCG '97 Proceedings of the thirteenth annual symposium on Computational geometry
On Active Camera Control and Camera Motion Recovery with Foveate Wavelet Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Disparity estimation on log-polar images and vergence control
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
An MIMD Computing Platform for a Hierarchical Foveal Machine Vision System
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Tracking in a Space Variant Active Vision System
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Foveate wavelet transform and its applications in digital video processing, acquisition, and indexing
Visual simulation of retinal images through microstructures
Microelectronic Engineering
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Foveal vision has been used as a way for sampling and reducing the amount of data in Cartesian images for vision systems. For this sampling, there are different approaches as the Log Polar Transform, the Exponential Cartesian Geometry and the Foveal Wavelet Transform between others. In this paper a new approach to obtain the foveal sampling and its application to single object tracking is presented. The approach uses the log polar formulation for the sampling but preserves the Cartesian properties of the information in the original image. In this way, it is possible to overcome the problems of no-linearity of the Log Polar Geometry. Furthermore, it allows an easier object location as the hierarchical processing used in the Exponential Cartesian Geometries and it is easy to implement because it does not imply complex operations for the sampling of the images and the recovery of the original image through the foveated image, contrary to the Foveal Wavelet Transform. The proposed geometry has been tested in diverse images sequences where a single object is tracked successfully by appearance based methods which demonstrate the effectiveness of the proposal.