Ontology type: schema:ScholarlyArticle Open Access: True
2019-09-23
AUTHORS ABSTRACTBackgroundWe present a series of experiments on visual search in a highly complex environment, security closed-circuit television (CCTV). Using real surveillance footage from a large city transport hub, we ask viewers to search for target individuals. Search targets are presented in a number of ways, using naturally occurring images including their passports and photo ID, social media and custody images/videos. Our aim is to establish general principles for search efficiency within this realistic context.ResultsAcross four studies we find that providing multiple photos of the search target consistently improves performance. Three different photos of the target, taken at different times, give substantial performance improvements by comparison to a single target. By contrast, providing targets in moving videos or with biographical context does not lead to improvements in search accuracy.ConclusionsWe discuss the multiple-image advantage in relation to a growing understanding of the importance of within-person variability in face recognition. More... »
PAGES37
http://scigraph.springernature.com/pub.10.1186/s41235-019-0193-0
DOIhttp://dx.doi.org/10.1186/s41235-019-0193-0
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1121192787
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/31549263
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/2008/17",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Psychology and Cognitive Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1701",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Psychology",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1702",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Cognitive Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "Department of Psychology, University of York, YO10 5DD, York, UK",
"id": "http://www.grid.ac/institutes/grid.5685.e",
"name": [
"Department of Psychology, University of York, YO10 5DD, York, UK"
],
"type": "Organization"
},
"familyName": "Mileva",
"givenName": "Mila",
"id": "sg:person.013271347607.91",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013271347607.91"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Department of Psychology, University of York, YO10 5DD, York, UK",
"id": "http://www.grid.ac/institutes/grid.5685.e",
"name": [
"Department of Psychology, University of York, YO10 5DD, York, UK"
],
"type": "Organization"
},
"familyName": "Burton",
"givenName": "A. Mike",
"id": "sg:person.01261533174.87",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261533174.87"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.3758/bf03193433",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1024937754",
"https://doi.org/10.3758/bf03193433"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/brm.42.1.286",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1015940686",
"https://doi.org/10.3758/brm.42.1.286"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11292-007-9024-2",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005645455",
"https://doi.org/10.1007/s11292-007-9024-2"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/s13414-015-0903-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1035002253",
"https://doi.org/10.3758/s13414-015-0903-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03211397",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036789239",
"https://doi.org/10.3758/bf03211397"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s41235-018-0112-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1105142869",
"https://doi.org/10.1186/s41235-018-0112-9"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03211948",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1005083652",
"https://doi.org/10.3758/bf03211948"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03336915",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1012811312",
"https://doi.org/10.3758/bf03336915"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03194109",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1046523920",
"https://doi.org/10.3758/bf03194109"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03208228",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036058366",
"https://doi.org/10.3758/bf03208228"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03198293",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020426737",
"https://doi.org/10.3758/bf03198293"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03194105",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028229859",
"https://doi.org/10.3758/bf03194105"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1186/s41235-016-0042-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1074249646",
"https://doi.org/10.1186/s41235-016-0042-3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/bf03203630",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1031867147",
"https://doi.org/10.3758/bf03203630"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s00221-005-0283-8",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000878601",
"https://doi.org/10.1007/s00221-005-0283-8"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.3758/s13414-011-0153-3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1027291403",
"https://doi.org/10.3758/s13414-011-0153-3"
],
"type": "CreativeWork"
}
],
"datePublished": "2019-09-23",
"datePublishedReg": "2019-09-23",
"description": "BackgroundWe present a series of experiments on visual search in a highly complex environment, security closed-circuit television (CCTV). Using real surveillance footage from a large city transport hub, we ask viewers to search for target individuals. Search targets are presented in a number of ways, using naturally occurring images including their passports and photo ID, social media and custody images/videos. Our aim is to establish general principles for search efficiency within this realistic context.ResultsAcross four studies we find that providing multiple photos of the search target consistently improves performance. Three different photos of the target, taken at different times, give substantial performance improvements by comparison to a single target. By contrast, providing targets in moving videos or with biographical context does not lead to improvements in search accuracy.ConclusionsWe discuss the multiple-image advantage in relation to a growing understanding of the importance of within-person variability in face recognition.",
"genre": "article",
"id": "sg:pub.10.1186/s41235-019-0193-0",
"inLanguage": "en",
"isAccessibleForFree": true,
"isFundedItemOf": [
{
"id": "sg:grant.2752584",
"type": "MonetaryGrant"
},
{
"id": "sg:grant.3957492",
"type": "MonetaryGrant"
}
],
"isPartOf": [
{
"id": "sg:journal.1284451",
"issn": [
"2365-7464"
],
"name": "Cognitive Research: Principles and Implications",
"publisher": "Springer Nature",
"type": "Periodical"
},
{
"issueNumber": "1",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "4"
}
],
"keywords": [
"closed-circuit television",
"images/videos",
"search target",
"substantial performance improvement",
"surveillance footage",
"search accuracy",
"face search",
"search efficiency",
"face recognition",
"CCTV surveillance",
"multiple photos",
"complex environments",
"different photos",
"performance improvement",
"video",
"social media",
"realistic context",
"visual search",
"photo ID",
"series of experiments",
"target individuals",
"photos",
"search",
"number of ways",
"transport hub",
"single target",
"footage",
"images",
"ID",
"viewers",
"recognition",
"accuracy",
"context",
"environment",
"passport",
"performance",
"advantages",
"improvement",
"efficiency",
"surveillance",
"way",
"hub",
"general principles",
"television",
"experiments",
"principles",
"different times",
"number",
"time",
"target",
"comparison",
"importance",
"understanding",
"medium",
"series",
"relation",
"aim",
"individuals",
"variability",
"study",
"contrast",
"person variability",
"ConclusionsWe",
"biographical context",
"BackgroundWe",
"Four studies"
],
"name": "Face search in CCTV surveillance",
"pagination": "37",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1121192787"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1186/s41235-019-0193-0"
]
},
{
"name": "pubmed_id",
"type": "PropertyValue",
"value": [
"31549263"
]
}
],
"sameAs": [
"https://doi.org/10.1186/s41235-019-0193-0",
"https://app.dimensions.ai/details/publication/pub.1121192787"
],
"sdDataset": "articles",
"sdDatePublished": "2022-05-10T10:26",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/article/article_823.jsonl",
"type": "ScholarlyArticle",
"url": "https://doi.org/10.1186/s41235-019-0193-0"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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.10.1186/s41235-019-0193-0'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s41235-019-0193-0'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s41235-019-0193-0'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s41235-019-0193-0'
This table displays all metadata directly associated to this object as RDF triples.
206 TRIPLES
22 PREDICATES
109 URIs
84 LITERALS
7 BLANK NODES