Abstract
We present a model that uses binocular visual input to detect landmarks and estimates their distance based on disparity between the two images. Feature detectors provide input to saliency maps that find landmarks as combinations of features. Interactions between feature detectors for the left and right images and between the saliency maps enables corresponding landmarks to be found. We test the model in the real world and show that it reliably detects landmarks and estimates their distances.
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© 2002 Springer-Verlag Berlin Heidelberg
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Conradt, J., Simon, P., Pescatore, M., Verschure, P.F.M.J. (2002). Saliency Maps Operating on Stereo Images Detect Landmarks and Their Distance. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_129
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DOI: https://doi.org/10.1007/3-540-46084-5_129
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