Generating A Virtual World To Assess Real-World Video Analysis Performance


Ontology type: sgo:Patent     


Patent Info

DATE

N/A

AUTHORS

WANG, Qiao , GAIDON, ADRIEN , VIG, ELEONORA

ABSTRACT

A system and method are suited for assessing video performance analysis. A computer graphics engine clones real-world data in a virtual world by decomposing the real-world data into visual components and objects in one or more object categories and populates the virtual world with virtual visual components and virtual objects. A scripting component controls the virtual visual components and the virtual objects in the virtual world based on the set of real-world data. A synthetic clone of the video sequence is generated based on the script controlling the virtual visual components and the virtual objects. The real-world data is compared with the synthetic clone of the video sequence and a transferability of conclusions from the virtual world to the real-world is assessed based on this comparison. More... »

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/2008/2746", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2790", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "WANG, Qiao", 
        "type": "Person"
      }, 
      {
        "name": "GAIDON, ADRIEN", 
        "type": "Person"
      }, 
      {
        "name": "VIG, ELEONORA", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1155/2008/246309", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031475974"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2010.232", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061743945"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2013.163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061744473"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2013.185", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061744492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2013.175", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094480864"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2014.81", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094727707"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2015.7299006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094779026"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2005.495", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094899531"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/ivcnz.2015.7761558", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095109699"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2012.6248074", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095200328"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2011.6126508", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095268909"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "description": "

A system and method are suited for assessing video performance analysis. A computer graphics engine clones real-world data in a virtual world by decomposing the real-world data into visual components and objects in one or more object categories and populates the virtual world with virtual visual components and virtual objects. A scripting component controls the virtual visual components and the virtual objects in the virtual world based on the set of real-world data. A synthetic clone of the video sequence is generated based on the script controlling the virtual visual components and the virtual objects. The real-world data is compared with the synthetic clone of the video sequence and a transferability of conclusions from the virtual world to the real-world is assessed based on this comparison.\n

", "id": "sg:patent.EP-3211596-A1", "keywords": [ "virtual world", "method", "performance analysis", "real-world data", "component", "object category", "populate", "virtual object", "scripting", "video sequence", "script", "transferability", "conclusion", "real world", "comparison" ], "name": "GENERATING A VIRTUAL WORLD TO ASSESS REAL-WORLD VIDEO ANALYSIS PERFORMANCE", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.420144.7", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/EP-3211596-A1" ], "sdDataset": "patents", "sdDatePublished": "2019-03-07T15:37", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com.uberresearch.data.dev.patents-pipeline/full_run_10/sn-export/5eb3e5a348d7f117b22cc85fb0b02730/0000100128-0000348334/json_export_e5ffef63.jsonl", "type": "Patent" } ]
 

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/patent.EP-3211596-A1'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.EP-3211596-A1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.EP-3211596-A1'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.EP-3211596-A1'


 

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

80 TRIPLES      14 PREDICATES      40 URIs      22 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.EP-3211596-A1 schema:about anzsrc-for:2746
2 anzsrc-for:2790
3 schema:author N9b056630442d4a4f9d57101c2ee397e4
4 schema:citation https://doi.org/10.1109/cvpr.2005.495
5 https://doi.org/10.1109/cvpr.2012.6248074
6 https://doi.org/10.1109/cvpr.2014.81
7 https://doi.org/10.1109/cvpr.2015.7299006
8 https://doi.org/10.1109/iccv.2011.6126508
9 https://doi.org/10.1109/iccv.2013.175
10 https://doi.org/10.1109/ivcnz.2015.7761558
11 https://doi.org/10.1109/tpami.2010.232
12 https://doi.org/10.1109/tpami.2013.163
13 https://doi.org/10.1109/tpami.2013.185
14 https://doi.org/10.1155/2008/246309
15 schema:description <p id="pa01" num="0001">A system and method are suited for assessing video performance analysis. A computer graphics engine clones real-world data in a virtual world by decomposing the real-world data into visual components and objects in one or more object categories and populates the virtual world with virtual visual components and virtual objects. A scripting component controls the virtual visual components and the virtual objects in the virtual world based on the set of real-world data. A synthetic clone of the video sequence is generated based on the script controlling the virtual visual components and the virtual objects. The real-world data is compared with the synthetic clone of the video sequence and a transferability of conclusions from the virtual world to the real-world is assessed based on this comparison. <img id="iaf01" file="imgaf001.tif" wi="134" he="89" img-content="drawing" img-format="tif"/></p>
16 schema:keywords comparison
17 component
18 conclusion
19 method
20 object category
21 performance analysis
22 populate
23 real world
24 real-world data
25 script
26 scripting
27 transferability
28 video sequence
29 virtual object
30 virtual world
31 schema:name GENERATING A VIRTUAL WORLD TO ASSESS REAL-WORLD VIDEO ANALYSIS PERFORMANCE
32 schema:recipient https://www.grid.ac/institutes/grid.420144.7
33 schema:sameAs https://app.dimensions.ai/details/patent/EP-3211596-A1
34 schema:sdDatePublished 2019-03-07T15:37
35 schema:sdLicense https://scigraph.springernature.com/explorer/license/
36 schema:sdPublisher N7d2fed2afa8a4a699927e8a1502be932
37 sgo:license sg:explorer/license/
38 sgo:sdDataset patents
39 rdf:type sgo:Patent
40 N1831f29c280b41d9a8ced609879df4fd schema:name GAIDON, ADRIEN
41 rdf:type schema:Person
42 N42bf0fb7eef44d7786ef62db2fd1b755 schema:name VIG, ELEONORA
43 rdf:type schema:Person
44 N7d2fed2afa8a4a699927e8a1502be932 schema:name Springer Nature - SN SciGraph project
45 rdf:type schema:Organization
46 N9b056630442d4a4f9d57101c2ee397e4 rdf:first Nf5e078f751fe48f6abfbf078c12f20d0
47 rdf:rest Nee0af9756dfb4323862709e3df93f343
48 Nd77f4ed82f6041fe94cb97c2f35fcb7e rdf:first N42bf0fb7eef44d7786ef62db2fd1b755
49 rdf:rest rdf:nil
50 Nee0af9756dfb4323862709e3df93f343 rdf:first N1831f29c280b41d9a8ced609879df4fd
51 rdf:rest Nd77f4ed82f6041fe94cb97c2f35fcb7e
52 Nf5e078f751fe48f6abfbf078c12f20d0 schema:name WANG, Qiao
53 rdf:type schema:Person
54 anzsrc-for:2746 schema:inDefinedTermSet anzsrc-for:
55 rdf:type schema:DefinedTerm
56 anzsrc-for:2790 schema:inDefinedTermSet anzsrc-for:
57 rdf:type schema:DefinedTerm
58 https://doi.org/10.1109/cvpr.2005.495 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094899531
59 rdf:type schema:CreativeWork
60 https://doi.org/10.1109/cvpr.2012.6248074 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095200328
61 rdf:type schema:CreativeWork
62 https://doi.org/10.1109/cvpr.2014.81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094727707
63 rdf:type schema:CreativeWork
64 https://doi.org/10.1109/cvpr.2015.7299006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094779026
65 rdf:type schema:CreativeWork
66 https://doi.org/10.1109/iccv.2011.6126508 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095268909
67 rdf:type schema:CreativeWork
68 https://doi.org/10.1109/iccv.2013.175 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094480864
69 rdf:type schema:CreativeWork
70 https://doi.org/10.1109/ivcnz.2015.7761558 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095109699
71 rdf:type schema:CreativeWork
72 https://doi.org/10.1109/tpami.2010.232 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743945
73 rdf:type schema:CreativeWork
74 https://doi.org/10.1109/tpami.2013.163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061744473
75 rdf:type schema:CreativeWork
76 https://doi.org/10.1109/tpami.2013.185 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061744492
77 rdf:type schema:CreativeWork
78 https://doi.org/10.1155/2008/246309 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031475974
79 rdf:type schema:CreativeWork
80 https://www.grid.ac/institutes/grid.420144.7 schema:Organization
 




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


...