Action recognition in depth videos using hierarchical gaussian descriptor View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-08

AUTHORS

Xuan Son Nguyen, Abdel-Illah Mouaddib, Thanh Phuong Nguyen, Laurent Jeanpierre

ABSTRACT

In this paper, we propose a new approach based on distribution descriptors for action recognition in depth videos. Our local features are computed from binary patterns which incorporate the shape and motion cues for effective action recognition. Given pixel-level features, our approach estimates video local statistics in a hierarchical manner, where the distribution of pixel-level features and that of frame-level descriptors are modeled using single Gaussians. In this way, our approach constructs video descriptors directly from low-level features without resorting to codebook learning required by Bag-of-features (BoF) based approaches. In order to capture the spatial geometry and temporal order of a video, we use a spatio-temporal pyramid representation for each video. Our approach is validated on six benchmark datasets, i.e. MSRAction3D, MSRGesture3D, DHA, SKIG, UTD-MHAD and CAD-120. The experimental results show that our approach gives good performance on all the datasets. In particular, it achieves state-of-the-art accuracies on DHA, SKIG and UTD-MHAD datasets. More... »

PAGES

21617-21652

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11042-017-5593-x

DOI

http://dx.doi.org/10.1007/s11042-017-5593-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100349038


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen", 
          "id": "https://www.grid.ac/institutes/grid.463910.9", 
          "name": [
            "CNRS, GREYC, Universit\u00e9 de Caen Basse-Normandie, UMR 6072, 14000, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nguyen", 
        "givenName": "Xuan Son", 
        "id": "sg:person.07751164452.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07751164452.41"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen", 
          "id": "https://www.grid.ac/institutes/grid.463910.9", 
          "name": [
            "CNRS, GREYC, Universit\u00e9 de Caen Basse-Normandie, UMR 6072, 14000, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mouaddib", 
        "givenName": "Abdel-Illah", 
        "id": "sg:person.07672270453.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07672270453.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Universite De Toulon Et Du Var", 
          "id": "https://www.grid.ac/institutes/grid.12611.35", 
          "name": [
            "CNRS, ENSAM, LSIS, Aix Marseille Universit\u00e9, UMR 7296, 13397, Marseille, France", 
            "CNRS, LSIS, Universit\u00e9 de Toulon, UMR 7296, 83957, La Garde, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nguyen", 
        "givenName": "Thanh Phuong", 
        "id": "sg:person.013450506437.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013450506437.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen", 
          "id": "https://www.grid.ac/institutes/grid.463910.9", 
          "name": [
            "CNRS, GREYC, Universit\u00e9 de Caen Basse-Normandie, UMR 6072, 14000, Caen, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jeanpierre", 
        "givenName": "Laurent", 
        "id": "sg:person.011636545631.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011636545631.52"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1145/2393347.2396382", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002533850"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neucom.2015.08.096", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003311308"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1553374.1553453", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004476131"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/2964284.2967191", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006787465"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-33709-3_62", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008332607", 
          "https://doi.org/10.1007/978-3-642-33709-3_62"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.patcog.2016.03.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009945424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/2393347.2396381", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012660552"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11263-013-0636-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012698338", 
          "https://doi.org/10.1007/s11263-013-0636-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neunet.2014.09.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013219854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/1873951.1874249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013699282"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0278364913478446", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018300252"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/0278364913478446", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018300252"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2015.2491925", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023540006"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1010933404324", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024739340", 
          "https://doi.org/10.1023/a:1010933404324"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.imavis.2016.04.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027186783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.imavis.2016.04.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027186783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.imavis.2016.04.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027186783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cviu.2015.05.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030634890"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neucom.2014.06.085", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033932812"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-12307-8_32", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034068713", 
          "https://doi.org/10.1007/978-3-642-12307-8_32"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-12307-8_32", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034068713", 
          "https://doi.org/10.1007/978-3-642-12307-8_32"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmva.1999.1853", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035495854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-14715-9_5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035987277", 
          "https://doi.org/10.1007/978-3-642-14715-9_5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-14715-9_5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035987277", 
          "https://doi.org/10.1007/978-3-642-14715-9_5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-33712-3_34", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037872665", 
          "https://doi.org/10.1007/978-3-642-33712-3_34"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00371-016-1345-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040622850", 
          "https://doi.org/10.1007/s00371-016-1345-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00371-016-1345-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040622850", 
          "https://doi.org/10.1007/s00371-016-1345-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11042-015-3188-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041706779", 
          "https://doi.org/10.1007/s11042-015-3188-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.sigpro.2014.08.038", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047671980"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/thms.2014.2362520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061614914"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/thms.2015.2504550", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061615013"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tip.2013.2252622", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061643522"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tip.2014.2321495", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061643956"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/titb.2007.899496", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061656575"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2005.188", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061742845"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2006.244", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061743071"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2007.1110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061743235"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2008.75", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061743671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2015.2430335", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061744872"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2016.2560816", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061745093"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tsmca.2012.2223670", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061795976"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/050637996", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062846456"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/embc.2014.6944743", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079027156"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tcsvt.2017.2655521", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086111453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tip.2017.2718189", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1086151781"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2016.115", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093410244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2016.152", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093470227"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2014.82", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093487177"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2014.108", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093505622"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvprw.2012.6239232", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093549918"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2013.227", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093561416"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvprw.2013.78", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093705125"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2013.365", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093801553"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2013.365", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093801553"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/wacv.2013.6475006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1093832938"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2015.519", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094331467"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/dicta.2014.7008101", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094483082"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icip.2015.7350781", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094540780"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/vsmm.2010.5665969", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094573097"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icra.2017.7989361", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094652589"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2015.460", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094735069"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icpr.1994.576366", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094758643"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/wacv.2015.150", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094775239"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2016.167", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094804690"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2012.6247813", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094880165"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2015.7298714", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094903557"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2012.6247965", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095110079"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/3dv.2014.10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095183094"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/bsn.2009.46", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095316091"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icpr.2014.772", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095438317"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccvw.2013.19", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095460052"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2013.98", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095557931"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2013.98", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095557931"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2015.169", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095573598"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icpr.2016.7899668", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095617602"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvprw.2010.5543273", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095719282"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2017.137", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095837219"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2017.498", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095838715"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2017.391", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095839726"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/3132734.3132739", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095925651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2017.115", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100060077"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2017.621", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100060639"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccvw.2017.123", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100559314"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-08", 
    "datePublishedReg": "2018-08-01", 
    "description": "In this paper, we propose a new approach based on distribution descriptors for action recognition in depth videos. Our local features are computed from binary patterns which incorporate the shape and motion cues for effective action recognition. Given pixel-level features, our approach estimates video local statistics in a hierarchical manner, where the distribution of pixel-level features and that of frame-level descriptors are modeled using single Gaussians. In this way, our approach constructs video descriptors directly from low-level features without resorting to codebook learning required by Bag-of-features (BoF) based approaches. In order to capture the spatial geometry and temporal order of a video, we use a spatio-temporal pyramid representation for each video. Our approach is validated on six benchmark datasets, i.e. MSRAction3D, MSRGesture3D, DHA, SKIG, UTD-MHAD and CAD-120. The experimental results show that our approach gives good performance on all the datasets. In particular, it achieves state-of-the-art accuracies on DHA, SKIG and UTD-MHAD datasets.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11042-017-5593-x", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1044869", 
        "issn": [
          "1380-7501", 
          "1573-7721"
        ], 
        "name": "Multimedia Tools and Applications", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "16", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "77"
      }
    ], 
    "name": "Action recognition in depth videos using hierarchical gaussian descriptor", 
    "pagination": "21617-21652", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d4e52434aafebdac38cbdc11550d16818be6eea61ff7331f1c10a47a5ee5f773"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11042-017-5593-x"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1100349038"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11042-017-5593-x", 
      "https://app.dimensions.ai/details/publication/pub.1100349038"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T01:55", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8700_00000493.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/s11042-017-5593-x"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11042-017-5593-x'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11042-017-5593-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11042-017-5593-x'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11042-017-5593-x'


 

This table displays all metadata directly associated to this object as RDF triples.

319 TRIPLES      21 PREDICATES      102 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11042-017-5593-x schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N386fa19fe67444e79c6286d232a490e4
4 schema:citation sg:pub.10.1007/978-3-642-12307-8_32
5 sg:pub.10.1007/978-3-642-14715-9_5
6 sg:pub.10.1007/978-3-642-33709-3_62
7 sg:pub.10.1007/978-3-642-33712-3_34
8 sg:pub.10.1007/s00371-016-1345-6
9 sg:pub.10.1007/s11042-015-3188-y
10 sg:pub.10.1007/s11263-013-0636-x
11 sg:pub.10.1023/a:1010933404324
12 https://doi.org/10.1006/jmva.1999.1853
13 https://doi.org/10.1016/j.cviu.2015.05.010
14 https://doi.org/10.1016/j.imavis.2016.04.004
15 https://doi.org/10.1016/j.neucom.2014.06.085
16 https://doi.org/10.1016/j.neucom.2015.08.096
17 https://doi.org/10.1016/j.neunet.2014.09.003
18 https://doi.org/10.1016/j.patcog.2016.03.004
19 https://doi.org/10.1016/j.sigpro.2014.08.038
20 https://doi.org/10.1109/3dv.2014.10
21 https://doi.org/10.1109/bsn.2009.46
22 https://doi.org/10.1109/cvpr.2012.6247813
23 https://doi.org/10.1109/cvpr.2012.6247965
24 https://doi.org/10.1109/cvpr.2013.365
25 https://doi.org/10.1109/cvpr.2013.98
26 https://doi.org/10.1109/cvpr.2014.108
27 https://doi.org/10.1109/cvpr.2014.82
28 https://doi.org/10.1109/cvpr.2015.7298714
29 https://doi.org/10.1109/cvpr.2016.115
30 https://doi.org/10.1109/cvpr.2016.152
31 https://doi.org/10.1109/cvpr.2016.167
32 https://doi.org/10.1109/cvpr.2017.137
33 https://doi.org/10.1109/cvpr.2017.391
34 https://doi.org/10.1109/cvpr.2017.498
35 https://doi.org/10.1109/cvprw.2010.5543273
36 https://doi.org/10.1109/cvprw.2012.6239232
37 https://doi.org/10.1109/cvprw.2013.78
38 https://doi.org/10.1109/dicta.2014.7008101
39 https://doi.org/10.1109/embc.2014.6944743
40 https://doi.org/10.1109/iccv.2013.227
41 https://doi.org/10.1109/iccv.2015.169
42 https://doi.org/10.1109/iccv.2015.460
43 https://doi.org/10.1109/iccv.2015.519
44 https://doi.org/10.1109/iccv.2017.115
45 https://doi.org/10.1109/iccv.2017.621
46 https://doi.org/10.1109/iccvw.2013.19
47 https://doi.org/10.1109/iccvw.2017.123
48 https://doi.org/10.1109/icip.2015.7350781
49 https://doi.org/10.1109/icpr.1994.576366
50 https://doi.org/10.1109/icpr.2014.772
51 https://doi.org/10.1109/icpr.2016.7899668
52 https://doi.org/10.1109/icra.2017.7989361
53 https://doi.org/10.1109/tcsvt.2017.2655521
54 https://doi.org/10.1109/thms.2014.2362520
55 https://doi.org/10.1109/thms.2015.2504550
56 https://doi.org/10.1109/tip.2013.2252622
57 https://doi.org/10.1109/tip.2014.2321495
58 https://doi.org/10.1109/tip.2017.2718189
59 https://doi.org/10.1109/titb.2007.899496
60 https://doi.org/10.1109/tpami.2005.188
61 https://doi.org/10.1109/tpami.2006.244
62 https://doi.org/10.1109/tpami.2007.1110
63 https://doi.org/10.1109/tpami.2008.75
64 https://doi.org/10.1109/tpami.2015.2430335
65 https://doi.org/10.1109/tpami.2015.2491925
66 https://doi.org/10.1109/tpami.2016.2560816
67 https://doi.org/10.1109/tsmca.2012.2223670
68 https://doi.org/10.1109/vsmm.2010.5665969
69 https://doi.org/10.1109/wacv.2013.6475006
70 https://doi.org/10.1109/wacv.2015.150
71 https://doi.org/10.1137/050637996
72 https://doi.org/10.1145/1553374.1553453
73 https://doi.org/10.1145/1873951.1874249
74 https://doi.org/10.1145/2393347.2396381
75 https://doi.org/10.1145/2393347.2396382
76 https://doi.org/10.1145/2964284.2967191
77 https://doi.org/10.1145/3132734.3132739
78 https://doi.org/10.1177/0278364913478446
79 schema:datePublished 2018-08
80 schema:datePublishedReg 2018-08-01
81 schema:description In this paper, we propose a new approach based on distribution descriptors for action recognition in depth videos. Our local features are computed from binary patterns which incorporate the shape and motion cues for effective action recognition. Given pixel-level features, our approach estimates video local statistics in a hierarchical manner, where the distribution of pixel-level features and that of frame-level descriptors are modeled using single Gaussians. In this way, our approach constructs video descriptors directly from low-level features without resorting to codebook learning required by Bag-of-features (BoF) based approaches. In order to capture the spatial geometry and temporal order of a video, we use a spatio-temporal pyramid representation for each video. Our approach is validated on six benchmark datasets, i.e. MSRAction3D, MSRGesture3D, DHA, SKIG, UTD-MHAD and CAD-120. The experimental results show that our approach gives good performance on all the datasets. In particular, it achieves state-of-the-art accuracies on DHA, SKIG and UTD-MHAD datasets.
82 schema:genre research_article
83 schema:inLanguage en
84 schema:isAccessibleForFree false
85 schema:isPartOf N3427aadff30e417fa3cce740c7c927de
86 Nc5286f510f3a445ea60ebd7e9c1278d0
87 sg:journal.1044869
88 schema:name Action recognition in depth videos using hierarchical gaussian descriptor
89 schema:pagination 21617-21652
90 schema:productId Na4c4d336e1f24542a27e74de168f7c86
91 Na84298df9f174d568f2c1750072fc379
92 Nf761bac0e46047dba36af8fc14ad6b2b
93 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100349038
94 https://doi.org/10.1007/s11042-017-5593-x
95 schema:sdDatePublished 2019-04-11T01:55
96 schema:sdLicense https://scigraph.springernature.com/explorer/license/
97 schema:sdPublisher N6991aaffa1c64f709b5b1498e54891cc
98 schema:url http://link.springer.com/10.1007/s11042-017-5593-x
99 sgo:license sg:explorer/license/
100 sgo:sdDataset articles
101 rdf:type schema:ScholarlyArticle
102 N3427aadff30e417fa3cce740c7c927de schema:volumeNumber 77
103 rdf:type schema:PublicationVolume
104 N386fa19fe67444e79c6286d232a490e4 rdf:first sg:person.07751164452.41
105 rdf:rest Ndc7ebba5b6b846eca4e2e1c3d8da9864
106 N5815f99000814555940b2c627802ba80 rdf:first sg:person.013450506437.08
107 rdf:rest Nc9a0b9c7870b465bb975e7dd98a42ba6
108 N6991aaffa1c64f709b5b1498e54891cc schema:name Springer Nature - SN SciGraph project
109 rdf:type schema:Organization
110 Na4c4d336e1f24542a27e74de168f7c86 schema:name readcube_id
111 schema:value d4e52434aafebdac38cbdc11550d16818be6eea61ff7331f1c10a47a5ee5f773
112 rdf:type schema:PropertyValue
113 Na84298df9f174d568f2c1750072fc379 schema:name doi
114 schema:value 10.1007/s11042-017-5593-x
115 rdf:type schema:PropertyValue
116 Nc5286f510f3a445ea60ebd7e9c1278d0 schema:issueNumber 16
117 rdf:type schema:PublicationIssue
118 Nc9a0b9c7870b465bb975e7dd98a42ba6 rdf:first sg:person.011636545631.52
119 rdf:rest rdf:nil
120 Ndc7ebba5b6b846eca4e2e1c3d8da9864 rdf:first sg:person.07672270453.40
121 rdf:rest N5815f99000814555940b2c627802ba80
122 Nf761bac0e46047dba36af8fc14ad6b2b schema:name dimensions_id
123 schema:value pub.1100349038
124 rdf:type schema:PropertyValue
125 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
126 schema:name Information and Computing Sciences
127 rdf:type schema:DefinedTerm
128 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
129 schema:name Artificial Intelligence and Image Processing
130 rdf:type schema:DefinedTerm
131 sg:journal.1044869 schema:issn 1380-7501
132 1573-7721
133 schema:name Multimedia Tools and Applications
134 rdf:type schema:Periodical
135 sg:person.011636545631.52 schema:affiliation https://www.grid.ac/institutes/grid.463910.9
136 schema:familyName Jeanpierre
137 schema:givenName Laurent
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011636545631.52
139 rdf:type schema:Person
140 sg:person.013450506437.08 schema:affiliation https://www.grid.ac/institutes/grid.12611.35
141 schema:familyName Nguyen
142 schema:givenName Thanh Phuong
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013450506437.08
144 rdf:type schema:Person
145 sg:person.07672270453.40 schema:affiliation https://www.grid.ac/institutes/grid.463910.9
146 schema:familyName Mouaddib
147 schema:givenName Abdel-Illah
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07672270453.40
149 rdf:type schema:Person
150 sg:person.07751164452.41 schema:affiliation https://www.grid.ac/institutes/grid.463910.9
151 schema:familyName Nguyen
152 schema:givenName Xuan Son
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07751164452.41
154 rdf:type schema:Person
155 sg:pub.10.1007/978-3-642-12307-8_32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034068713
156 https://doi.org/10.1007/978-3-642-12307-8_32
157 rdf:type schema:CreativeWork
158 sg:pub.10.1007/978-3-642-14715-9_5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035987277
159 https://doi.org/10.1007/978-3-642-14715-9_5
160 rdf:type schema:CreativeWork
161 sg:pub.10.1007/978-3-642-33709-3_62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008332607
162 https://doi.org/10.1007/978-3-642-33709-3_62
163 rdf:type schema:CreativeWork
164 sg:pub.10.1007/978-3-642-33712-3_34 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037872665
165 https://doi.org/10.1007/978-3-642-33712-3_34
166 rdf:type schema:CreativeWork
167 sg:pub.10.1007/s00371-016-1345-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040622850
168 https://doi.org/10.1007/s00371-016-1345-6
169 rdf:type schema:CreativeWork
170 sg:pub.10.1007/s11042-015-3188-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1041706779
171 https://doi.org/10.1007/s11042-015-3188-y
172 rdf:type schema:CreativeWork
173 sg:pub.10.1007/s11263-013-0636-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1012698338
174 https://doi.org/10.1007/s11263-013-0636-x
175 rdf:type schema:CreativeWork
176 sg:pub.10.1023/a:1010933404324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024739340
177 https://doi.org/10.1023/a:1010933404324
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1006/jmva.1999.1853 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035495854
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/j.cviu.2015.05.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030634890
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1016/j.imavis.2016.04.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027186783
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1016/j.neucom.2014.06.085 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033932812
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1016/j.neucom.2015.08.096 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003311308
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1016/j.neunet.2014.09.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013219854
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1016/j.patcog.2016.03.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009945424
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1016/j.sigpro.2014.08.038 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047671980
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1109/3dv.2014.10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095183094
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1109/bsn.2009.46 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095316091
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1109/cvpr.2012.6247813 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094880165
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1109/cvpr.2012.6247965 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095110079
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1109/cvpr.2013.365 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093801553
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1109/cvpr.2013.98 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095557931
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1109/cvpr.2014.108 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093505622
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1109/cvpr.2014.82 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093487177
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1109/cvpr.2015.7298714 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094903557
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1109/cvpr.2016.115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093410244
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1109/cvpr.2016.152 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093470227
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1109/cvpr.2016.167 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094804690
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1109/cvpr.2017.137 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095837219
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1109/cvpr.2017.391 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095839726
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1109/cvpr.2017.498 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095838715
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1109/cvprw.2010.5543273 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095719282
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1109/cvprw.2012.6239232 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093549918
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1109/cvprw.2013.78 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093705125
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1109/dicta.2014.7008101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094483082
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1109/embc.2014.6944743 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079027156
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1109/iccv.2013.227 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093561416
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1109/iccv.2015.169 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095573598
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1109/iccv.2015.460 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094735069
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1109/iccv.2015.519 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094331467
242 rdf:type schema:CreativeWork
243 https://doi.org/10.1109/iccv.2017.115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100060077
244 rdf:type schema:CreativeWork
245 https://doi.org/10.1109/iccv.2017.621 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100060639
246 rdf:type schema:CreativeWork
247 https://doi.org/10.1109/iccvw.2013.19 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095460052
248 rdf:type schema:CreativeWork
249 https://doi.org/10.1109/iccvw.2017.123 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100559314
250 rdf:type schema:CreativeWork
251 https://doi.org/10.1109/icip.2015.7350781 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094540780
252 rdf:type schema:CreativeWork
253 https://doi.org/10.1109/icpr.1994.576366 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094758643
254 rdf:type schema:CreativeWork
255 https://doi.org/10.1109/icpr.2014.772 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095438317
256 rdf:type schema:CreativeWork
257 https://doi.org/10.1109/icpr.2016.7899668 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095617602
258 rdf:type schema:CreativeWork
259 https://doi.org/10.1109/icra.2017.7989361 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094652589
260 rdf:type schema:CreativeWork
261 https://doi.org/10.1109/tcsvt.2017.2655521 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086111453
262 rdf:type schema:CreativeWork
263 https://doi.org/10.1109/thms.2014.2362520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061614914
264 rdf:type schema:CreativeWork
265 https://doi.org/10.1109/thms.2015.2504550 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061615013
266 rdf:type schema:CreativeWork
267 https://doi.org/10.1109/tip.2013.2252622 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061643522
268 rdf:type schema:CreativeWork
269 https://doi.org/10.1109/tip.2014.2321495 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061643956
270 rdf:type schema:CreativeWork
271 https://doi.org/10.1109/tip.2017.2718189 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086151781
272 rdf:type schema:CreativeWork
273 https://doi.org/10.1109/titb.2007.899496 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061656575
274 rdf:type schema:CreativeWork
275 https://doi.org/10.1109/tpami.2005.188 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061742845
276 rdf:type schema:CreativeWork
277 https://doi.org/10.1109/tpami.2006.244 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743071
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1109/tpami.2007.1110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743235
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1109/tpami.2008.75 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743671
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1109/tpami.2015.2430335 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061744872
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1109/tpami.2015.2491925 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023540006
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1109/tpami.2016.2560816 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061745093
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1109/tsmca.2012.2223670 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061795976
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1109/vsmm.2010.5665969 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094573097
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1109/wacv.2013.6475006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093832938
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1109/wacv.2015.150 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094775239
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1137/050637996 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062846456
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1145/1553374.1553453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004476131
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1145/1873951.1874249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013699282
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1145/2393347.2396381 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012660552
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1145/2393347.2396382 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002533850
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1145/2964284.2967191 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006787465
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1145/3132734.3132739 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095925651
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1177/0278364913478446 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018300252
312 rdf:type schema:CreativeWork
313 https://www.grid.ac/institutes/grid.12611.35 schema:alternateName Universite De Toulon Et Du Var
314 schema:name CNRS, ENSAM, LSIS, Aix Marseille Université, UMR 7296, 13397, Marseille, France
315 CNRS, LSIS, Université de Toulon, UMR 7296, 83957, La Garde, France
316 rdf:type schema:Organization
317 https://www.grid.ac/institutes/grid.463910.9 schema:alternateName Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
318 schema:name CNRS, GREYC, Université de Caen Basse-Normandie, UMR 6072, 14000, Caen, France
319 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...