1.
Jürgen ’Juxi’ Leitner S. Harding, P. Chandrashekhariah M. Frank, G. Spina, A. Förster, J. Triesch, J. Schmidhuber idsia / usi / supsi, machine intelligence, fias autonomous learning of robust visual objectdetection & identification on a humanoid #icdl/epirob 2012

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our iCub setup is formanipulation

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thanks to G. Metta and IIT for this picture visual perception

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thechallenge

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IDSIA’s three partsHarding et al., GPTP 2012, Leitner et al., IROS 2012 Leitner et al., BICA 2012 Leitner et al., ICDL 2012

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currentcv approaches

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detecting objects Harding et al., GPTP 2012

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our learning approach

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INP INP INP + dilate min avg cartesian genetic programming

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INP INP INP + dilate min avgFunc,on" 3"Connec,on"1" "#2"Connec,on"2"A"real"number" "#1" 4.3" cartesian genetic """ " programming

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icImage GreenTeaBoxDetector::runFilter() {! icImage node0 = InputImages[6];! icImage node1 = InputImages[1];! icImage node2 = node0.absdiff(node1);! icImage node5 = node2.SmoothBilateral(11);! icImage node12 = InputImages[0];! icImage node16 = node12.Sqrt();! icImage node33 = node16.erode(6);! icImage node34 = node33.log();! icImage node36 = node34.min(node5);! icImage node49 = node36.Normalize(); //cleanup ... icImage out = node49.threshold(230.7218f);! return out; }detection

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detect

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detect

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BUT: supervised learning approach

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FIAScollaborationsaliencymap feature segmentation

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presegmentation

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combinedapproach

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MoBeEframework Frank et al., ICINCO, 2012.

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conclusion salient object detection + rough feature-based segmentation = automatic training set generation for cgp-based, robust filter-learning

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thanks for listeningjuxi@idsia.ch http://Juxi.net/projects http://robotics.idsia.ch video at http://robotics.idsia.ch/im-clever/