A space-variant representation of images is of great importance for active vision systems capable of interacting with the environment. A precise processing of the visual signal is achieved in the fovea, and, at the same time, a coarse computation in the periphery provides enough information to detect new saliences on which to bring the focus of attention. In this work, different techniques to implement the blind-spot model for the log-polar mapping are quantitatively analyzed to assess the visual quality of the transformed images and to evaluate the associated computational load. The technique with the best trade-off between these two aspects is expected to show the most efficient behaviour in robotic vision systems, where the execution time and the reliability of the visual information are crucial.
A Quantitative Comparison of Speed and Reliability for Log-Polar Mapping Techniques
CHESSA, MANUELA;SABATINI, SILVIO PAOLO;SOLARI, FABIO;TATTI, FABIO
2011-01-01
Abstract
A space-variant representation of images is of great importance for active vision systems capable of interacting with the environment. A precise processing of the visual signal is achieved in the fovea, and, at the same time, a coarse computation in the periphery provides enough information to detect new saliences on which to bring the focus of attention. In this work, different techniques to implement the blind-spot model for the log-polar mapping are quantitatively analyzed to assess the visual quality of the transformed images and to evaluate the associated computational load. The technique with the best trade-off between these two aspects is expected to show the most efficient behaviour in robotic vision systems, where the execution time and the reliability of the visual information are crucial.
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