3D Human-Gesture Interface for Fighting Games Using Motion Recognition Sensor View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2016-08

AUTHORS

Jongmin Kim, Hoill Jung, MyungA Kang, Kyungyong Chung

ABSTRACT

As augmented reality–related technologies become commercialized due to requests for 3D content, they are developing a pattern whereby users utilize and consume the realism and reality of 3D content. Rather than using absolute position information, the pattern characteristics of gestures are extracted by considering body-proportion characteristics around the shoulders. Even if performing the same gesture, position coordinate values of the skeleton measured by a motion recognition sensor can vary, depending on the length and direction of the arm. In this paper, we propose a 3D human-gesture interface for fighting games using a motion recognition sensor. Recognizing gestures in the motion recognition sensor environment, we applied the gestures to a fighting action game. The motion characteristics of gestures are extracted by using joint information obtained from the motion recognition sensor, and 3D human motion is modeled mathematically. Motion is effectively modeled and analyzed with a method of expressing it in space via principal component analysis and then matching it with the 3D human-gesture interface for new input. Also, we propose an advanced pattern matching algorithm as a way to reduce motion constraints in a motion recognition system. Finally, based on the results of motion recognition, an example used as the interface of a 3D fight action game is presented. By obtaining high-quality 3D motion, the developed technology provides more realistic 3D content through real-time processing technology. More... »

PAGES

927-940

References to SciGraph publications

  • 2016-03. Knowledge-based dietary nutrition recommendation for obese management in INFORMATION TECHNOLOGY AND MANAGEMENT
  • 2016-03. Knowledge-based health service considering user convenience using hybrid Wi-Fi P2P in INFORMATION TECHNOLOGY AND MANAGEMENT
  • 2014-12. Real-Time Tracking and Recognition Systems for Interactive Telemedicine Health Services in WIRELESS PERSONAL COMMUNICATIONS
  • 2015-06. Emergency situation monitoring service using context motion tracking of chronic disease patients in CLUSTER COMPUTING
  • 2016-01. Slope Based Intelligent 3D Disaster Simulation Using Physics Engine in WIRELESS PERSONAL COMMUNICATIONS
  • 2015-03. Sequential pattern profiling based bio-detection for smart health service in CLUSTER COMPUTING
  • 2005-12. Australian sign language recognition in MACHINE VISION AND APPLICATIONS
  • 1995-01. Visual learning and recognition of 3-d objects from appearance in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2004. Real-Time Person Tracking and Pointing Gesture Recognition for Human-Robot Interaction in COMPUTER VISION IN HUMAN-COMPUTER INTERACTION
  • 2015-10. Medical information service system based on human 3D anatomical model in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2015-10. Ontology-based inference system for adaptive object recognition in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2014-03. Development of head detection and tracking systems for visual surveillance in PERSONAL AND UBIQUITOUS COMPUTING
  • 2016-01. PHR Based Life Health Index Mobile Service Using Decision Support Model in WIRELESS PERSONAL COMMUNICATIONS
  • 2015-04. Design of access control system for telemedicine secure XML documents in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2014-09. Mobile healthcare application with EMR interoperability for diabetes patients in CLUSTER COMPUTING
  • 2014-01. 3D simulator for stability analysis of finite slope causing plane activity in MULTIMEDIA TOOLS AND APPLICATIONS
  • 2013-11. Home Health Gateway Based Healthcare Services Through U-Health Platform in WIRELESS PERSONAL COMMUNICATIONS
  • 2016-01. Continuous Gesture Recognition using HLAC and Low-Dimensional Space in WIRELESS PERSONAL COMMUNICATIONS
  • 2016-05. P2P context awareness based sensibility design recommendation using color and bio-signal analysis in PEER-TO-PEER NETWORKING AND APPLICATIONS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11277-016-3294-9

    DOI

    http://dx.doi.org/10.1007/s11277-016-3294-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1040685335


    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": {
              "name": [
                "Creative Economy Support Team, Jeonnam Center for Createive Economy and Innovation, 32, Deokchung 2-gil, 550-812, Yeosu-si, Jeollanam-do, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kim", 
            "givenName": "Jongmin", 
            "id": "sg:person.07404660645.54", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07404660645.54"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Sangji University", 
              "id": "https://www.grid.ac/institutes/grid.412417.5", 
              "name": [
                "Intelligent System Laboratory, School of Computer Information Engineering, Sangji University, 83, Sangjidae-gil, 220-702, Wonju-si, Gangwon-do, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Jung", 
            "givenName": "Hoill", 
            "id": "sg:person.012366363525.21", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012366363525.21"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Gwangju University", 
              "id": "https://www.grid.ac/institutes/grid.443795.8", 
              "name": [
                "Division of Computer Information Engineering, GwangJu University, 277, Hyodeok-ro, Nam-gu, Gwangju, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kang", 
            "givenName": "MyungA", 
            "id": "sg:person.011470752405.51", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011470752405.51"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Sangji University", 
              "id": "https://www.grid.ac/institutes/grid.412417.5", 
              "name": [
                "School of Computer Information Engineering, Sangji University, 83, Sangjidae-gil, Wonju-si, 220-702, Gangwon-Do, Korea"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chung", 
            "givenName": "Kyungyong", 
            "id": "sg:person.015747500237.74", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015747500237.74"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.3745/ktsde.2014.3.1.49", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002302077"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-540-24837-8_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004980091", 
              "https://doi.org/10.1007/978-3-540-24837-8_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s12083-015-0398-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005090418", 
              "https://doi.org/10.1007/s12083-015-0398-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-014-1938-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007000050", 
              "https://doi.org/10.1007/s11042-014-1938-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10586-015-0440-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008142134", 
              "https://doi.org/10.1007/s10586-015-0440-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10586-014-0370-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008304601", 
              "https://doi.org/10.1007/s10586-014-0370-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10586-013-0315-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017707170", 
              "https://doi.org/10.1007/s10586-013-0315-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01421486", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020275860", 
              "https://doi.org/10.1007/bf01421486"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf01421486", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020275860", 
              "https://doi.org/10.1007/bf01421486"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11277-015-2788-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022112124", 
              "https://doi.org/10.1007/s11277-015-2788-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11277-015-3068-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024476823", 
              "https://doi.org/10.1007/s11277-015-3068-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11277-015-3069-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026788277", 
              "https://doi.org/10.1007/s11277-015-3069-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10799-015-0218-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034525930", 
              "https://doi.org/10.1007/s10799-015-0218-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10799-015-0241-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035062182", 
              "https://doi.org/10.1007/s10799-015-0241-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-013-1584-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035328952", 
              "https://doi.org/10.1007/s11042-013-1584-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11277-013-1231-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037680085", 
              "https://doi.org/10.1007/s11277-013-1231-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-013-1356-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041006054", 
              "https://doi.org/10.1007/s11042-013-1356-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-005-0003-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045058076", 
              "https://doi.org/10.1007/s00138-005-0003-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-005-0003-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045058076", 
              "https://doi.org/10.1007/s00138-005-0003-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00138-005-0003-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045058076", 
              "https://doi.org/10.1007/s00138-005-0003-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11277-014-1784-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046771205", 
              "https://doi.org/10.1007/s11277-014-1784-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11042-013-1738-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052310261", 
              "https://doi.org/10.1007/s11042-013-1738-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00779-013-0668-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053592611", 
              "https://doi.org/10.1007/s00779-013-0668-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/34.598226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061156615"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cyber.2012.6392552", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1093558082"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/fskd.2011.6019899", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094556827"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/cgames.2012.6314563", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1094926413"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/afgr.1998.670952", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095289936"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/fskd.2008.610", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1095344711"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.5244/c.25.101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1099341318"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2016-08", 
        "datePublishedReg": "2016-08-01", 
        "description": "As augmented reality\u2013related technologies become commercialized due to requests for 3D content, they are developing a pattern whereby users utilize and consume the realism and reality of 3D content. Rather than using absolute position information, the pattern characteristics of gestures are extracted by considering body-proportion characteristics around the shoulders. Even if performing the same gesture, position coordinate values of the skeleton measured by a motion recognition sensor can vary, depending on the length and direction of the arm. In this paper, we propose a 3D human-gesture interface for fighting games using a motion recognition sensor. Recognizing gestures in the motion recognition sensor environment, we applied the gestures to a fighting action game. The motion characteristics of gestures are extracted by using joint information obtained from the motion recognition sensor, and 3D human motion is modeled mathematically. Motion is effectively modeled and analyzed with a method of expressing it in space via principal component analysis and then matching it with the 3D human-gesture interface for new input. Also, we propose an advanced pattern matching algorithm as a way to reduce motion constraints in a motion recognition system. Finally, based on the results of motion recognition, an example used as the interface of a 3D fight action game is presented. By obtaining high-quality 3D motion, the developed technology provides more realistic 3D content through real-time processing technology.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s11277-016-3294-9", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isPartOf": [
          {
            "id": "sg:journal.1052655", 
            "issn": [
              "0929-6212", 
              "1572-834X"
            ], 
            "name": "Wireless Personal Communications", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "89"
          }
        ], 
        "name": "3D Human-Gesture Interface for Fighting Games Using Motion Recognition Sensor", 
        "pagination": "927-940", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "c1cf2b3cc78de55b75cc84b5d3f38f2b2196968ff9aecdbe70e5ca4f30085595"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s11277-016-3294-9"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1040685335"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s11277-016-3294-9", 
          "https://app.dimensions.ai/details/publication/pub.1040685335"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T18:23", 
        "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_8675_00000523.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs11277-016-3294-9"
      }
    ]
     

    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/s11277-016-3294-9'

    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/s11277-016-3294-9'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11277-016-3294-9'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11277-016-3294-9'


     

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

    188 TRIPLES      21 PREDICATES      54 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s11277-016-3294-9 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author N4d8aa038bd0343eda7e88f16132c96a6
    4 schema:citation sg:pub.10.1007/978-3-540-24837-8_4
    5 sg:pub.10.1007/bf01421486
    6 sg:pub.10.1007/s00138-005-0003-1
    7 sg:pub.10.1007/s00779-013-0668-9
    8 sg:pub.10.1007/s10586-013-0315-2
    9 sg:pub.10.1007/s10586-014-0370-3
    10 sg:pub.10.1007/s10586-015-0440-1
    11 sg:pub.10.1007/s10799-015-0218-4
    12 sg:pub.10.1007/s10799-015-0241-5
    13 sg:pub.10.1007/s11042-013-1356-5
    14 sg:pub.10.1007/s11042-013-1584-8
    15 sg:pub.10.1007/s11042-013-1738-8
    16 sg:pub.10.1007/s11042-014-1938-x
    17 sg:pub.10.1007/s11277-013-1231-8
    18 sg:pub.10.1007/s11277-014-1784-1
    19 sg:pub.10.1007/s11277-015-2788-1
    20 sg:pub.10.1007/s11277-015-3068-9
    21 sg:pub.10.1007/s11277-015-3069-8
    22 sg:pub.10.1007/s12083-015-0398-z
    23 https://doi.org/10.1109/34.598226
    24 https://doi.org/10.1109/afgr.1998.670952
    25 https://doi.org/10.1109/cgames.2012.6314563
    26 https://doi.org/10.1109/cyber.2012.6392552
    27 https://doi.org/10.1109/fskd.2008.610
    28 https://doi.org/10.1109/fskd.2011.6019899
    29 https://doi.org/10.3745/ktsde.2014.3.1.49
    30 https://doi.org/10.5244/c.25.101
    31 schema:datePublished 2016-08
    32 schema:datePublishedReg 2016-08-01
    33 schema:description As augmented reality–related technologies become commercialized due to requests for 3D content, they are developing a pattern whereby users utilize and consume the realism and reality of 3D content. Rather than using absolute position information, the pattern characteristics of gestures are extracted by considering body-proportion characteristics around the shoulders. Even if performing the same gesture, position coordinate values of the skeleton measured by a motion recognition sensor can vary, depending on the length and direction of the arm. In this paper, we propose a 3D human-gesture interface for fighting games using a motion recognition sensor. Recognizing gestures in the motion recognition sensor environment, we applied the gestures to a fighting action game. The motion characteristics of gestures are extracted by using joint information obtained from the motion recognition sensor, and 3D human motion is modeled mathematically. Motion is effectively modeled and analyzed with a method of expressing it in space via principal component analysis and then matching it with the 3D human-gesture interface for new input. Also, we propose an advanced pattern matching algorithm as a way to reduce motion constraints in a motion recognition system. Finally, based on the results of motion recognition, an example used as the interface of a 3D fight action game is presented. By obtaining high-quality 3D motion, the developed technology provides more realistic 3D content through real-time processing technology.
    34 schema:genre research_article
    35 schema:inLanguage en
    36 schema:isAccessibleForFree false
    37 schema:isPartOf N724db7c255734b2fbcf21c156172d04e
    38 Nb0ee7e4c87ad4505ae7e3e691f1b5fa3
    39 sg:journal.1052655
    40 schema:name 3D Human-Gesture Interface for Fighting Games Using Motion Recognition Sensor
    41 schema:pagination 927-940
    42 schema:productId N3af31ef3b2b24e71be2603de519cbbd2
    43 Na67118898af642708a5c8d728e402a5d
    44 Nea419a357c164517aa9f5fda1eb84e9e
    45 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040685335
    46 https://doi.org/10.1007/s11277-016-3294-9
    47 schema:sdDatePublished 2019-04-10T18:23
    48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    49 schema:sdPublisher Na8e03a76b0914649a94729641d8f3513
    50 schema:url http://link.springer.com/10.1007%2Fs11277-016-3294-9
    51 sgo:license sg:explorer/license/
    52 sgo:sdDataset articles
    53 rdf:type schema:ScholarlyArticle
    54 N2db5b24f214e4da9b184df8a29fd256f rdf:first sg:person.011470752405.51
    55 rdf:rest Nb9a8ac25efef4095a7681fa9fc4274bc
    56 N3af31ef3b2b24e71be2603de519cbbd2 schema:name dimensions_id
    57 schema:value pub.1040685335
    58 rdf:type schema:PropertyValue
    59 N4d8aa038bd0343eda7e88f16132c96a6 rdf:first sg:person.07404660645.54
    60 rdf:rest Nc0b268e80ce947b5982128885427053d
    61 N5af172cadec5463eb3112f2987523397 schema:name Creative Economy Support Team, Jeonnam Center for Createive Economy and Innovation, 32, Deokchung 2-gil, 550-812, Yeosu-si, Jeollanam-do, Korea
    62 rdf:type schema:Organization
    63 N724db7c255734b2fbcf21c156172d04e schema:issueNumber 3
    64 rdf:type schema:PublicationIssue
    65 Na67118898af642708a5c8d728e402a5d schema:name readcube_id
    66 schema:value c1cf2b3cc78de55b75cc84b5d3f38f2b2196968ff9aecdbe70e5ca4f30085595
    67 rdf:type schema:PropertyValue
    68 Na8e03a76b0914649a94729641d8f3513 schema:name Springer Nature - SN SciGraph project
    69 rdf:type schema:Organization
    70 Nb0ee7e4c87ad4505ae7e3e691f1b5fa3 schema:volumeNumber 89
    71 rdf:type schema:PublicationVolume
    72 Nb9a8ac25efef4095a7681fa9fc4274bc rdf:first sg:person.015747500237.74
    73 rdf:rest rdf:nil
    74 Nc0b268e80ce947b5982128885427053d rdf:first sg:person.012366363525.21
    75 rdf:rest N2db5b24f214e4da9b184df8a29fd256f
    76 Nea419a357c164517aa9f5fda1eb84e9e schema:name doi
    77 schema:value 10.1007/s11277-016-3294-9
    78 rdf:type schema:PropertyValue
    79 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    80 schema:name Information and Computing Sciences
    81 rdf:type schema:DefinedTerm
    82 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    83 schema:name Artificial Intelligence and Image Processing
    84 rdf:type schema:DefinedTerm
    85 sg:journal.1052655 schema:issn 0929-6212
    86 1572-834X
    87 schema:name Wireless Personal Communications
    88 rdf:type schema:Periodical
    89 sg:person.011470752405.51 schema:affiliation https://www.grid.ac/institutes/grid.443795.8
    90 schema:familyName Kang
    91 schema:givenName MyungA
    92 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011470752405.51
    93 rdf:type schema:Person
    94 sg:person.012366363525.21 schema:affiliation https://www.grid.ac/institutes/grid.412417.5
    95 schema:familyName Jung
    96 schema:givenName Hoill
    97 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012366363525.21
    98 rdf:type schema:Person
    99 sg:person.015747500237.74 schema:affiliation https://www.grid.ac/institutes/grid.412417.5
    100 schema:familyName Chung
    101 schema:givenName Kyungyong
    102 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015747500237.74
    103 rdf:type schema:Person
    104 sg:person.07404660645.54 schema:affiliation N5af172cadec5463eb3112f2987523397
    105 schema:familyName Kim
    106 schema:givenName Jongmin
    107 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07404660645.54
    108 rdf:type schema:Person
    109 sg:pub.10.1007/978-3-540-24837-8_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004980091
    110 https://doi.org/10.1007/978-3-540-24837-8_4
    111 rdf:type schema:CreativeWork
    112 sg:pub.10.1007/bf01421486 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020275860
    113 https://doi.org/10.1007/bf01421486
    114 rdf:type schema:CreativeWork
    115 sg:pub.10.1007/s00138-005-0003-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045058076
    116 https://doi.org/10.1007/s00138-005-0003-1
    117 rdf:type schema:CreativeWork
    118 sg:pub.10.1007/s00779-013-0668-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053592611
    119 https://doi.org/10.1007/s00779-013-0668-9
    120 rdf:type schema:CreativeWork
    121 sg:pub.10.1007/s10586-013-0315-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017707170
    122 https://doi.org/10.1007/s10586-013-0315-2
    123 rdf:type schema:CreativeWork
    124 sg:pub.10.1007/s10586-014-0370-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008304601
    125 https://doi.org/10.1007/s10586-014-0370-3
    126 rdf:type schema:CreativeWork
    127 sg:pub.10.1007/s10586-015-0440-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008142134
    128 https://doi.org/10.1007/s10586-015-0440-1
    129 rdf:type schema:CreativeWork
    130 sg:pub.10.1007/s10799-015-0218-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034525930
    131 https://doi.org/10.1007/s10799-015-0218-4
    132 rdf:type schema:CreativeWork
    133 sg:pub.10.1007/s10799-015-0241-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035062182
    134 https://doi.org/10.1007/s10799-015-0241-5
    135 rdf:type schema:CreativeWork
    136 sg:pub.10.1007/s11042-013-1356-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041006054
    137 https://doi.org/10.1007/s11042-013-1356-5
    138 rdf:type schema:CreativeWork
    139 sg:pub.10.1007/s11042-013-1584-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035328952
    140 https://doi.org/10.1007/s11042-013-1584-8
    141 rdf:type schema:CreativeWork
    142 sg:pub.10.1007/s11042-013-1738-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052310261
    143 https://doi.org/10.1007/s11042-013-1738-8
    144 rdf:type schema:CreativeWork
    145 sg:pub.10.1007/s11042-014-1938-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1007000050
    146 https://doi.org/10.1007/s11042-014-1938-x
    147 rdf:type schema:CreativeWork
    148 sg:pub.10.1007/s11277-013-1231-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037680085
    149 https://doi.org/10.1007/s11277-013-1231-8
    150 rdf:type schema:CreativeWork
    151 sg:pub.10.1007/s11277-014-1784-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046771205
    152 https://doi.org/10.1007/s11277-014-1784-1
    153 rdf:type schema:CreativeWork
    154 sg:pub.10.1007/s11277-015-2788-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022112124
    155 https://doi.org/10.1007/s11277-015-2788-1
    156 rdf:type schema:CreativeWork
    157 sg:pub.10.1007/s11277-015-3068-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024476823
    158 https://doi.org/10.1007/s11277-015-3068-9
    159 rdf:type schema:CreativeWork
    160 sg:pub.10.1007/s11277-015-3069-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026788277
    161 https://doi.org/10.1007/s11277-015-3069-8
    162 rdf:type schema:CreativeWork
    163 sg:pub.10.1007/s12083-015-0398-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1005090418
    164 https://doi.org/10.1007/s12083-015-0398-z
    165 rdf:type schema:CreativeWork
    166 https://doi.org/10.1109/34.598226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061156615
    167 rdf:type schema:CreativeWork
    168 https://doi.org/10.1109/afgr.1998.670952 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095289936
    169 rdf:type schema:CreativeWork
    170 https://doi.org/10.1109/cgames.2012.6314563 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094926413
    171 rdf:type schema:CreativeWork
    172 https://doi.org/10.1109/cyber.2012.6392552 schema:sameAs https://app.dimensions.ai/details/publication/pub.1093558082
    173 rdf:type schema:CreativeWork
    174 https://doi.org/10.1109/fskd.2008.610 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095344711
    175 rdf:type schema:CreativeWork
    176 https://doi.org/10.1109/fskd.2011.6019899 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094556827
    177 rdf:type schema:CreativeWork
    178 https://doi.org/10.3745/ktsde.2014.3.1.49 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002302077
    179 rdf:type schema:CreativeWork
    180 https://doi.org/10.5244/c.25.101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099341318
    181 rdf:type schema:CreativeWork
    182 https://www.grid.ac/institutes/grid.412417.5 schema:alternateName Sangji University
    183 schema:name Intelligent System Laboratory, School of Computer Information Engineering, Sangji University, 83, Sangjidae-gil, 220-702, Wonju-si, Gangwon-do, Korea
    184 School of Computer Information Engineering, Sangji University, 83, Sangjidae-gil, Wonju-si, 220-702, Gangwon-Do, Korea
    185 rdf:type schema:Organization
    186 https://www.grid.ac/institutes/grid.443795.8 schema:alternateName Gwangju University
    187 schema:name Division of Computer Information Engineering, GwangJu University, 277, Hyodeok-ro, Nam-gu, Gwangju, Korea
    188 rdf:type schema:Organization
     




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


    ...