Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2005

AUTHORS

Alexei Yavlinsky , Edward Schofield , Stefan Rüger

ABSTRACT

This paper describes a simple framework for automatically annotating images using non-parametric models of distributions of image features. We show that under this framework quite simple image properties such as global colour and texture distributions provide a strong basis for reliably annotating images. We report results on subsets of two photographic libraries, the Corel Photo Archive and the Getty Image Archive. We also show how the popular Earth Mover’s Distance measure can be effectively incorporated within this framework. More... »

PAGES

507-517

References to SciGraph publications

Book

TITLE

Image and Video Retrieval

ISBN

978-3-540-27858-0
978-3-540-31678-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11526346_54

DOI

http://dx.doi.org/10.1007/11526346_54

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012604628


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": "Imperial College London", 
          "id": "https://www.grid.ac/institutes/grid.7445.2", 
          "name": [
            "Department of Computing, Imperial College London, South Kensington Campus, SW7 2AZ, London, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yavlinsky", 
        "givenName": "Alexei", 
        "id": "sg:person.013706101177.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013706101177.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Imperial College London", 
          "id": "https://www.grid.ac/institutes/grid.7445.2", 
          "name": [
            "Department of Computing, Imperial College London, South Kensington Campus, SW7 2AZ, London, UK", 
            "Telecommunications Research Center Vienna"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Schofield", 
        "givenName": "Edward", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Imperial College London", 
          "id": "https://www.grid.ac/institutes/grid.7445.2", 
          "name": [
            "Department of Computing, Imperial College London, South Kensington Campus, SW7 2AZ, London, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "R\u00fcger", 
        "givenName": "Stefan", 
        "id": "sg:person.013375677533.85", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013375677533.85"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1006/cviu.2001.0934", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008060631"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-27814-6_40", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017375184", 
          "https://doi.org/10.1007/978-3-540-27814-6_40"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-27814-6_40", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017375184", 
          "https://doi.org/10.1007/978-3-540-27814-6_40"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1011139631724", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019562355", 
          "https://doi.org/10.1023/a:1011139631724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-27814-6_9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037880900", 
          "https://doi.org/10.1007/978-3-540-27814-6_9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-540-27814-6_9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037880900", 
          "https://doi.org/10.1007/978-3-540-27814-6_9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/860435.860460", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038991414"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/3-540-47979-1_7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040055518", 
          "https://doi.org/10.1007/3-540-47979-1_7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/3-540-45479-9_5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042422709", 
          "https://doi.org/10.1007/3-540-45479-9_5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoms/1177704472", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046915289"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1145/860435.860459", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053524475"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1059115409", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tsmc.1978.4309999", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061793131"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aos/1018031201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064406003"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2001.937632", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094415605"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2004.1315274", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095228808"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2005", 
    "datePublishedReg": "2005-01-01", 
    "description": "This paper describes a simple framework for automatically annotating images using non-parametric models of distributions of image features. We show that under this framework quite simple image properties such as global colour and texture distributions provide a strong basis for reliably annotating images. We report results on subsets of two photographic libraries, the Corel Photo Archive and the Getty Image Archive. We also show how the popular Earth Mover\u2019s Distance measure can be effectively incorporated within this framework.", 
    "editor": [
      {
        "familyName": "Leow", 
        "givenName": "Wee-Kheng", 
        "type": "Person"
      }, 
      {
        "familyName": "Lew", 
        "givenName": "Michael S.", 
        "type": "Person"
      }, 
      {
        "familyName": "Chua", 
        "givenName": "Tat-Seng", 
        "type": "Person"
      }, 
      {
        "familyName": "Ma", 
        "givenName": "Wei-Ying", 
        "type": "Person"
      }, 
      {
        "familyName": "Chaisorn", 
        "givenName": "Lekha", 
        "type": "Person"
      }, 
      {
        "familyName": "Bakker", 
        "givenName": "Erwin M.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/11526346_54", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": {
      "isbn": [
        "978-3-540-27858-0", 
        "978-3-540-31678-7"
      ], 
      "name": "Image and Video Retrieval", 
      "type": "Book"
    }, 
    "name": "Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation", 
    "pagination": "507-517", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1012604628"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/11526346_54"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "3c0d2dbfecbdd92c5f8e9daa38092ec9de51ab6ac07898145ac67198c203e1e4"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/11526346_54", 
      "https://app.dimensions.ai/details/publication/pub.1012604628"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T07:58", 
    "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/v90/0000000359_0000000359/records_29181_00000000.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F11526346_54"
  }
]
 

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.10.1007/11526346_54'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/11526346_54'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/11526346_54'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/11526346_54'


 

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

150 TRIPLES      23 PREDICATES      41 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/11526346_54 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Nfb84800bed674722a779a9639a964b95
4 schema:citation sg:pub.10.1007/3-540-45479-9_5
5 sg:pub.10.1007/3-540-47979-1_7
6 sg:pub.10.1007/978-3-540-27814-6_40
7 sg:pub.10.1007/978-3-540-27814-6_9
8 sg:pub.10.1023/a:1011139631724
9 https://app.dimensions.ai/details/publication/pub.1059115409
10 https://doi.org/10.1006/cviu.2001.0934
11 https://doi.org/10.1109/cvpr.2004.1315274
12 https://doi.org/10.1109/iccv.2001.937632
13 https://doi.org/10.1109/tsmc.1978.4309999
14 https://doi.org/10.1145/860435.860459
15 https://doi.org/10.1145/860435.860460
16 https://doi.org/10.1214/aoms/1177704472
17 https://doi.org/10.1214/aos/1018031201
18 schema:datePublished 2005
19 schema:datePublishedReg 2005-01-01
20 schema:description This paper describes a simple framework for automatically annotating images using non-parametric models of distributions of image features. We show that under this framework quite simple image properties such as global colour and texture distributions provide a strong basis for reliably annotating images. We report results on subsets of two photographic libraries, the Corel Photo Archive and the Getty Image Archive. We also show how the popular Earth Mover’s Distance measure can be effectively incorporated within this framework.
21 schema:editor Nf5273335fd5c43e89452bfe65c6aadb3
22 schema:genre chapter
23 schema:inLanguage en
24 schema:isAccessibleForFree true
25 schema:isPartOf N515c8d7642d843cd9533952772a7a3b9
26 schema:name Automated Image Annotation Using Global Features and Robust Nonparametric Density Estimation
27 schema:pagination 507-517
28 schema:productId N0b977500b69d454a9ae0f020dc607a10
29 N29e37126356849e4b52d6027c58fdb9a
30 N3f5f32450c41471b8fd3d39a3bc62b8f
31 schema:publisher N87716cc0844f4ee4b5e6e0a9689537f8
32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012604628
33 https://doi.org/10.1007/11526346_54
34 schema:sdDatePublished 2019-04-16T07:58
35 schema:sdLicense https://scigraph.springernature.com/explorer/license/
36 schema:sdPublisher N6590646a400f45d8bf98d1bfd8fd28bb
37 schema:url https://link.springer.com/10.1007%2F11526346_54
38 sgo:license sg:explorer/license/
39 sgo:sdDataset chapters
40 rdf:type schema:Chapter
41 N009b06d1b1b949ee89f12d5ad1c4bcd0 schema:familyName Bakker
42 schema:givenName Erwin M.
43 rdf:type schema:Person
44 N0b977500b69d454a9ae0f020dc607a10 schema:name readcube_id
45 schema:value 3c0d2dbfecbdd92c5f8e9daa38092ec9de51ab6ac07898145ac67198c203e1e4
46 rdf:type schema:PropertyValue
47 N11b05a8460b94bcfa08f948b5d7471d9 rdf:first N79d7ee7e09ce41edbfde18986cefa7ba
48 rdf:rest Nac7accff51774789b36cab34665fab53
49 N29e37126356849e4b52d6027c58fdb9a schema:name dimensions_id
50 schema:value pub.1012604628
51 rdf:type schema:PropertyValue
52 N3f5f32450c41471b8fd3d39a3bc62b8f schema:name doi
53 schema:value 10.1007/11526346_54
54 rdf:type schema:PropertyValue
55 N4339c24f22614ebeb30431fc9cecc1d6 schema:familyName Leow
56 schema:givenName Wee-Kheng
57 rdf:type schema:Person
58 N4c2cb7d1e104443bb860a2ac194c4786 rdf:first N86de97084cc34ca2b59afdfc9f56beb9
59 rdf:rest N11b05a8460b94bcfa08f948b5d7471d9
60 N515c8d7642d843cd9533952772a7a3b9 schema:isbn 978-3-540-27858-0
61 978-3-540-31678-7
62 schema:name Image and Video Retrieval
63 rdf:type schema:Book
64 N56010185e5db4b5a80ea1ecfbec16e28 schema:familyName Lew
65 schema:givenName Michael S.
66 rdf:type schema:Person
67 N6590646a400f45d8bf98d1bfd8fd28bb schema:name Springer Nature - SN SciGraph project
68 rdf:type schema:Organization
69 N79d7ee7e09ce41edbfde18986cefa7ba schema:familyName Ma
70 schema:givenName Wei-Ying
71 rdf:type schema:Person
72 N86de97084cc34ca2b59afdfc9f56beb9 schema:familyName Chua
73 schema:givenName Tat-Seng
74 rdf:type schema:Person
75 N87716cc0844f4ee4b5e6e0a9689537f8 schema:location Berlin, Heidelberg
76 schema:name Springer Berlin Heidelberg
77 rdf:type schema:Organisation
78 Nac7accff51774789b36cab34665fab53 rdf:first Nb0d0762ddaf04785a4e49273b755a328
79 rdf:rest Nfe707e67cd054fe4bb0e05e113415d00
80 Nb0d0762ddaf04785a4e49273b755a328 schema:familyName Chaisorn
81 schema:givenName Lekha
82 rdf:type schema:Person
83 Nc0ad75aba1e04d439c14eeea9733d2b7 rdf:first N56010185e5db4b5a80ea1ecfbec16e28
84 rdf:rest N4c2cb7d1e104443bb860a2ac194c4786
85 Ncd1bda7f36594cf69c8072c3b88d05cb rdf:first Nfc873de7b68a496496cffad94a96fc18
86 rdf:rest Neda3b17798b24560b6c391912071538a
87 Neda3b17798b24560b6c391912071538a rdf:first sg:person.013375677533.85
88 rdf:rest rdf:nil
89 Nf5273335fd5c43e89452bfe65c6aadb3 rdf:first N4339c24f22614ebeb30431fc9cecc1d6
90 rdf:rest Nc0ad75aba1e04d439c14eeea9733d2b7
91 Nfb84800bed674722a779a9639a964b95 rdf:first sg:person.013706101177.52
92 rdf:rest Ncd1bda7f36594cf69c8072c3b88d05cb
93 Nfc873de7b68a496496cffad94a96fc18 schema:affiliation https://www.grid.ac/institutes/grid.7445.2
94 schema:familyName Schofield
95 schema:givenName Edward
96 rdf:type schema:Person
97 Nfe707e67cd054fe4bb0e05e113415d00 rdf:first N009b06d1b1b949ee89f12d5ad1c4bcd0
98 rdf:rest rdf:nil
99 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
100 schema:name Information and Computing Sciences
101 rdf:type schema:DefinedTerm
102 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
103 schema:name Artificial Intelligence and Image Processing
104 rdf:type schema:DefinedTerm
105 sg:person.013375677533.85 schema:affiliation https://www.grid.ac/institutes/grid.7445.2
106 schema:familyName Rüger
107 schema:givenName Stefan
108 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013375677533.85
109 rdf:type schema:Person
110 sg:person.013706101177.52 schema:affiliation https://www.grid.ac/institutes/grid.7445.2
111 schema:familyName Yavlinsky
112 schema:givenName Alexei
113 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013706101177.52
114 rdf:type schema:Person
115 sg:pub.10.1007/3-540-45479-9_5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042422709
116 https://doi.org/10.1007/3-540-45479-9_5
117 rdf:type schema:CreativeWork
118 sg:pub.10.1007/3-540-47979-1_7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040055518
119 https://doi.org/10.1007/3-540-47979-1_7
120 rdf:type schema:CreativeWork
121 sg:pub.10.1007/978-3-540-27814-6_40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017375184
122 https://doi.org/10.1007/978-3-540-27814-6_40
123 rdf:type schema:CreativeWork
124 sg:pub.10.1007/978-3-540-27814-6_9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037880900
125 https://doi.org/10.1007/978-3-540-27814-6_9
126 rdf:type schema:CreativeWork
127 sg:pub.10.1023/a:1011139631724 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019562355
128 https://doi.org/10.1023/a:1011139631724
129 rdf:type schema:CreativeWork
130 https://app.dimensions.ai/details/publication/pub.1059115409 schema:CreativeWork
131 https://doi.org/10.1006/cviu.2001.0934 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008060631
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1109/cvpr.2004.1315274 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095228808
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1109/iccv.2001.937632 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094415605
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1109/tsmc.1978.4309999 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061793131
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1145/860435.860459 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053524475
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1145/860435.860460 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038991414
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1214/aoms/1177704472 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046915289
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1214/aos/1018031201 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064406003
146 rdf:type schema:CreativeWork
147 https://www.grid.ac/institutes/grid.7445.2 schema:alternateName Imperial College London
148 schema:name Department of Computing, Imperial College London, South Kensington Campus, SW7 2AZ, London, UK
149 Telecommunications Research Center Vienna
150 rdf:type schema:Organization
 




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


...