Qualitative Shape—Some Computational Aspects View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1992

AUTHORS

Jan-Olof Eklundh , Tony Lindeberg , Harald Winroth

ABSTRACT

Theories and methodologies for representing and abstracting shape from visual information are a major concern in computational vision. Important contributions have been made on e.g. theories of dynamic shape, on the detection of salient structures like symmetries and discontinuities and also on the use of mathematical techniques of optimization and approximation.Here we will survey some of these approaches and discuss what they make explicit and how that can be computed. In particular, we will consider such techniques in view of the figure-ground problem and the desirability of qualitative vs. quantitative descriptions. More... »

PAGES

231-248

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4899-0715-8_23

DOI

http://dx.doi.org/10.1007/978-1-4899-0715-8_23

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038900975


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/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden", 
          "id": "http://www.grid.ac/institutes/grid.5037.1", 
          "name": [
            "Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Eklundh", 
        "givenName": "Jan-Olof", 
        "id": "sg:person.014400652155.17", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014400652155.17"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden", 
          "id": "http://www.grid.ac/institutes/grid.5037.1", 
          "name": [
            "Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lindeberg", 
        "givenName": "Tony", 
        "id": "sg:person.015666316421.55", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015666316421.55"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden", 
          "id": "http://www.grid.ac/institutes/grid.5037.1", 
          "name": [
            "Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Winroth", 
        "givenName": "Harald", 
        "id": "sg:person.07527336740.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07527336740.06"
        ], 
        "type": "Person"
      }
    ], 
    "datePublished": "1992", 
    "datePublishedReg": "1992-01-01", 
    "description": "Theories and methodologies for representing and abstracting shape from visual information are a major concern in computational vision. Important contributions have been made on e.g. theories of dynamic shape, on the detection of salient structures like symmetries and discontinuities and also on the use of mathematical techniques of optimization and approximation.Here we will survey some of these approaches and discuss what they make explicit and how that can be computed. In particular, we will consider such techniques in view of the figure-ground problem and the desirability of qualitative vs. quantitative descriptions.", 
    "editor": [
      {
        "familyName": "Arcelli", 
        "givenName": "Carlo", 
        "type": "Person"
      }, 
      {
        "familyName": "Cordella", 
        "givenName": "Luigi P.", 
        "type": "Person"
      }, 
      {
        "familyName": "di Baja", 
        "givenName": "Gabriella Sanniti", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-1-4899-0715-8_23", 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-1-4899-0717-2", 
        "978-1-4899-0715-8"
      ], 
      "name": "Visual Form", 
      "type": "Book"
    }, 
    "keywords": [
      "figure-ground problem", 
      "mathematical techniques", 
      "computational vision", 
      "computational aspects", 
      "visual information", 
      "such techniques", 
      "salient structure", 
      "dynamic shape", 
      "qualitative shape", 
      "theory", 
      "approximation", 
      "major concern", 
      "symmetry", 
      "optimization", 
      "vision", 
      "shape", 
      "technique", 
      "discontinuities", 
      "information", 
      "problem", 
      "detection", 
      "methodology", 
      "approach", 
      "important contribution", 
      "structure", 
      "view", 
      "aspects", 
      "use", 
      "concern", 
      "contribution", 
      "qualitative", 
      "desirability"
    ], 
    "name": "Qualitative Shape\u2014Some Computational Aspects", 
    "pagination": "231-248", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1038900975"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-1-4899-0715-8_23"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-1-4899-0715-8_23", 
      "https://app.dimensions.ai/details/publication/pub.1038900975"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2022-11-24T21:19", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221124/entities/gbq_results/chapter/chapter_49.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/10.1007/978-1-4899-0715-8_23"
  }
]
 

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.10.1007/978-1-4899-0715-8_23'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-1-4899-0715-8_23'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-1-4899-0715-8_23'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-1-4899-0715-8_23'


 

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

115 TRIPLES      22 PREDICATES      57 URIs      50 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-1-4899-0715-8_23 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N6a41cd61ddff4545a198246249208c18
4 schema:datePublished 1992
5 schema:datePublishedReg 1992-01-01
6 schema:description Theories and methodologies for representing and abstracting shape from visual information are a major concern in computational vision. Important contributions have been made on e.g. theories of dynamic shape, on the detection of salient structures like symmetries and discontinuities and also on the use of mathematical techniques of optimization and approximation.Here we will survey some of these approaches and discuss what they make explicit and how that can be computed. In particular, we will consider such techniques in view of the figure-ground problem and the desirability of qualitative vs. quantitative descriptions.
7 schema:editor Nf2d11956a27a4866b0ab79ab0c2dc8aa
8 schema:genre chapter
9 schema:isAccessibleForFree false
10 schema:isPartOf N5f0795b7de64471eab5283a1e29ca94d
11 schema:keywords approach
12 approximation
13 aspects
14 computational aspects
15 computational vision
16 concern
17 contribution
18 desirability
19 detection
20 discontinuities
21 dynamic shape
22 figure-ground problem
23 important contribution
24 information
25 major concern
26 mathematical techniques
27 methodology
28 optimization
29 problem
30 qualitative
31 qualitative shape
32 salient structure
33 shape
34 structure
35 such techniques
36 symmetry
37 technique
38 theory
39 use
40 view
41 vision
42 visual information
43 schema:name Qualitative Shape—Some Computational Aspects
44 schema:pagination 231-248
45 schema:productId N74c3cb567edc423c9c93a951ea02f990
46 Nf269fba8f1c94d0389bf624001bc01ce
47 schema:publisher N67699dd923364b4b990be261daf91fde
48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038900975
49 https://doi.org/10.1007/978-1-4899-0715-8_23
50 schema:sdDatePublished 2022-11-24T21:19
51 schema:sdLicense https://scigraph.springernature.com/explorer/license/
52 schema:sdPublisher N7a0a46ebd1514ce182b7a6439b020d34
53 schema:url https://doi.org/10.1007/978-1-4899-0715-8_23
54 sgo:license sg:explorer/license/
55 sgo:sdDataset chapters
56 rdf:type schema:Chapter
57 N03cb5825ceda45fe851d30a746408cd9 rdf:first N1060e87469c34906ad70e9e599a0ace1
58 rdf:rest rdf:nil
59 N070066de3fa64b64bbe1e7d5bd1973c6 rdf:first Na6513b54a8854570930f9af42a7b18b8
60 rdf:rest N03cb5825ceda45fe851d30a746408cd9
61 N1060e87469c34906ad70e9e599a0ace1 schema:familyName di Baja
62 schema:givenName Gabriella Sanniti
63 rdf:type schema:Person
64 N5635d67f07d842f6a5867b7e42adc0c1 rdf:first sg:person.07527336740.06
65 rdf:rest rdf:nil
66 N58a50f55307d4e348e73331c32639b1f schema:familyName Arcelli
67 schema:givenName Carlo
68 rdf:type schema:Person
69 N5f0795b7de64471eab5283a1e29ca94d schema:isbn 978-1-4899-0715-8
70 978-1-4899-0717-2
71 schema:name Visual Form
72 rdf:type schema:Book
73 N67699dd923364b4b990be261daf91fde schema:name Springer Nature
74 rdf:type schema:Organisation
75 N6a41cd61ddff4545a198246249208c18 rdf:first sg:person.014400652155.17
76 rdf:rest Nd33577b86a9048b8b9376756af025a66
77 N74c3cb567edc423c9c93a951ea02f990 schema:name doi
78 schema:value 10.1007/978-1-4899-0715-8_23
79 rdf:type schema:PropertyValue
80 N7a0a46ebd1514ce182b7a6439b020d34 schema:name Springer Nature - SN SciGraph project
81 rdf:type schema:Organization
82 Na6513b54a8854570930f9af42a7b18b8 schema:familyName Cordella
83 schema:givenName Luigi P.
84 rdf:type schema:Person
85 Nd33577b86a9048b8b9376756af025a66 rdf:first sg:person.015666316421.55
86 rdf:rest N5635d67f07d842f6a5867b7e42adc0c1
87 Nf269fba8f1c94d0389bf624001bc01ce schema:name dimensions_id
88 schema:value pub.1038900975
89 rdf:type schema:PropertyValue
90 Nf2d11956a27a4866b0ab79ab0c2dc8aa rdf:first N58a50f55307d4e348e73331c32639b1f
91 rdf:rest N070066de3fa64b64bbe1e7d5bd1973c6
92 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
93 schema:name Information and Computing Sciences
94 rdf:type schema:DefinedTerm
95 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
96 schema:name Artificial Intelligence and Image Processing
97 rdf:type schema:DefinedTerm
98 sg:person.014400652155.17 schema:affiliation grid-institutes:grid.5037.1
99 schema:familyName Eklundh
100 schema:givenName Jan-Olof
101 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014400652155.17
102 rdf:type schema:Person
103 sg:person.015666316421.55 schema:affiliation grid-institutes:grid.5037.1
104 schema:familyName Lindeberg
105 schema:givenName Tony
106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015666316421.55
107 rdf:type schema:Person
108 sg:person.07527336740.06 schema:affiliation grid-institutes:grid.5037.1
109 schema:familyName Winroth
110 schema:givenName Harald
111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07527336740.06
112 rdf:type schema:Person
113 grid-institutes:grid.5037.1 schema:alternateName Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden
114 schema:name Computational Vision and Active Perception Laboratory (CVAP), Royal Institute of Technology, S-100 44, Stockholm, Sweden
115 rdf:type schema:Organization
 




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


...