Vision Objects

Results: 165



#Item
31Learning Kinematic Models for Articulated Objects ¨ Jurgen Sturm1 Christian Plagemann3

Learning Kinematic Models for Articulated Objects ¨ Jurgen Sturm1 Christian Plagemann3

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Source URL: vision.in.tum.de

Language: English - Date: 2011-07-05 10:35:48
    32With the MyScript® Music Software Development Kit (SDK), it is now possible to develop applications enabling the recognition of handwritten musical scores created with any digital writing device. Symbols such as notes,

    With the MyScript® Music Software Development Kit (SDK), it is now possible to develop applications enabling the recognition of handwritten musical scores created with any digital writing device. Symbols such as notes,

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    Source URL: myscript.com

    Language: English - Date: 2015-04-02 11:31:30
    33Detecting Strange Objects via Visual Attributes Babak Saleh ∗ ∗

    Detecting Strange Objects via Visual Attributes Babak Saleh ∗ ∗

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    Source URL: paul.rutgers.edu

    Language: English - Date: 2014-12-01 03:20:18
    34Semantic Segmentation With Object Clique Potentials Xiaojuan Qi Jianping Shi Shu Liu Renjie Liao The Chinese University of Hong Kong

    Semantic Segmentation With Object Clique Potentials Xiaojuan Qi Jianping Shi Shu Liu Renjie Liao The Chinese University of Hong Kong

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    Source URL: www.cse.cuhk.edu.hk

    Language: English - Date: 2015-09-29 05:12:00
    35International Journal of Computer Vision c 2007 Springer Science + Business Media, LLC. Manufactured in the United States.  DOI: s11263Appearance Sampling of Real Objects for Variable Illumination

    International Journal of Computer Vision c 2007 Springer Science + Business Media, LLC. Manufactured in the United States.  DOI: s11263Appearance Sampling of Real Objects for Variable Illumination

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    Source URL: www.hci.iis.u-tokyo.ac.jp

    Language: English - Date: 2008-06-30 09:56:34
      36Recognition and Tracking of 3D Objects by 1D Search  Daniel F. DeMenthon and Larry S. Davis Computer Vision Laboratory Center for Automation Research University of Maryland

      Recognition and Tracking of 3D Objects by 1D Search Daniel F. DeMenthon and Larry S. Davis Computer Vision Laboratory Center for Automation Research University of Maryland

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      Source URL: www.cfar.umd.edu

      Language: English - Date: 2004-12-06 15:54:05
        37Multiclass Discriminative Fields for Parts-Based Object Detection Sanjiv Kumar and Martial Hebert The Robotics Institute Carnegie Mellon University

        Multiclass Discriminative Fields for Parts-Based Object Detection Sanjiv Kumar and Martial Hebert The Robotics Institute Carnegie Mellon University

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        Source URL: www.sanjivk.com

        Language: English - Date: 2010-06-01 18:50:50
        38PTV VISUM TIPS & TRICKS: EDITING A POLYGON OF AREA OBJECTS PTV Visum uses area objects for zones, territories, POIs, main nodes, main zones and toll systems, and offers a comfortable editor for their closed polygons. Are

        PTV VISUM TIPS & TRICKS: EDITING A POLYGON OF AREA OBJECTS PTV Visum uses area objects for zones, territories, POIs, main nodes, main zones and toll systems, and offers a comfortable editor for their closed polygons. Are

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        Source URL: vision-traffic.ptvgroup.com

        Language: English - Date: 2014-01-20 02:11:36
          39Embedding High-Level Information into Low Level Vision: Efficient Object Search in Clutter Ching L. Teo, Austin Myers, Cornelia Ferm¨uller, Yiannis Aloimonos Abstract— The ability to search visually for objects of int

          Embedding High-Level Information into Low Level Vision: Efficient Object Search in Clutter Ching L. Teo, Austin Myers, Cornelia Ferm¨uller, Yiannis Aloimonos Abstract— The ability to search visually for objects of int

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          Source URL: www.poeticon.eu

          Language: English
            40Vision Research – 3848 www.elsevier.com/locate/visres Interaction between the perceived shape of two objects Eli Brenner a,*, Michael S. Landy b b

            Vision Research – 3848 www.elsevier.com/locate/visres Interaction between the perceived shape of two objects Eli Brenner a,*, Michael S. Landy b b

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            Source URL: www.cns.nyu.edu

            Language: English - Date: 2002-04-11 14:52:44