... | @@ -85,6 +85,30 @@ details about the architecture can be found at |
... | @@ -85,6 +85,30 @@ details about the architecture can be found at |
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![](/uploads/0a418e4bd11db51af90a8851f50260bc/itti_model.png)
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![](/uploads/0a418e4bd11db51af90a8851f50260bc/itti_model.png)
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Fig 1. Itti model from \[1\].
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Fig 1. Itti model from \[1\].
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As it can be seen in Fig 1, the original model combines features
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estimated for different spatial resolutions. The maps for a specific
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input example are shown in Fig
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2.
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![](/uploads/1e8b88854e472d807198bd55a95c7559/feature_maps.png)
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Fig 2. Feature maps and sorted most salient locations (see \[2\]).
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After several normalizations, they are integrated into a unique final
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saliency map.
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The final map can be estimated using more diverse cues. In \[2\] we also
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propose the integration of [optical
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flow](https://www.ohwr.org/project/optical-flow-cores/wiki) and [stereo
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disparity](https://www.ohwr.org/project/stereo-disparity-cores/wiki).
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The integration of the motion can be done straightforward as the other
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features in the bottom-up system. Nevertheless, optical flow (as complex
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information of speed and direction of the motion) and disparity can be
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also integrated as top-down stream, in this case to modulate the final
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saliency map.
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Saliency can be used in many different fields such as robotics,
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autonomous navigation, and aid devices for low-vision patients.
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## Contacts
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## Contacts
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