Face processing: Human perception and principal components analysis View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

1996-01

AUTHORS

Peter J. B. Hancock, A. Mike Burton, Vicki Bruce

ABSTRACT

Principal components analysis (PCA) of face images is here related to subjects’ performance on the same images. In two experiments subjects were shown a set of faces and asked to rate them for distinctiveness. They were subsequently shown a superset of faces and asked to identify those that had appeared originally. Replicating previous work, we found that hits and false positives (FPs) did not correlate: Those faces easy to identify as being “seen” were unrelated to those faces easy to reject as being “unseen.” PCA was performed on three data sets: (1) face images with eye position standardized, (2) face images morphed to a standard template to remove shape information, and (3) the shape information from faces only. Analyses based on PCA of shape-free faces gave high predictions of FPs, whereas shape information itself contributed only to hits. Furthermore, whereas FPs were generally predictable from components early in the PCA, hits appeared to be accounted for by later components. We conclude that shape and “texture” (the image-based information remaining after morphing) may be used separately by the human face processing system, and that PCA of images offers a useful tool for understanding this system. More... »

PAGES

26-40

Identifiers

URI

http://scigraph.springernature.com/pub.10.3758/bf03197270

DOI

http://dx.doi.org/10.3758/bf03197270

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009736800

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/8822156


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/2008/17", 
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Attention", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Discrimination Learning", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Face", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mental Recall", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Pattern Recognition, Visual", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Psychophysics", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Psychology, University of Stirling, FK9 4LA, Stirling, Scotland, UK", 
          "id": "http://www.grid.ac/institutes/grid.11918.30", 
          "name": [
            "Department of Psychology, University of Stirling, FK9 4LA, Stirling, Scotland, UK"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hancock", 
        "givenName": "Peter J. B.", 
        "id": "sg:person.012352566236.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012352566236.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Glasgow, Glasgow, Scotland", 
          "id": "http://www.grid.ac/institutes/grid.8756.c", 
          "name": [
            "University of Glasgow, Glasgow, Scotland"
          ], 
          "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"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Stirling, Stirling, Scotland", 
          "id": "http://www.grid.ac/institutes/grid.11918.30", 
          "name": [
            "University of Stirling, Stirling, Scotland"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bruce", 
        "givenName": "Vicki", 
        "id": "sg:person.0775026766.00", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0775026766.00"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/978-1-4471-1921-0_52", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013064816", 
          "https://doi.org/10.1007/978-1-4471-1921-0_52"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.3758/bf03208892", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050506185", 
          "https://doi.org/10.3758/bf03208892"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-009-4420-6_42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018701013", 
          "https://doi.org/10.1007/978-94-009-4420-6_42"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.3758/bf03199666", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022512165", 
          "https://doi.org/10.3758/bf03199666"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1996-01", 
    "datePublishedReg": "1996-01-01", 
    "description": "Principal components analysis (PCA) of face images is here related to subjects\u2019 performance on the same images. In two experiments subjects were shown a set of faces and asked to rate them for distinctiveness. They were subsequently shown a superset of faces and asked to identify those that had appeared originally. Replicating previous work, we found that hits and false positives (FPs) did not correlate: Those faces easy to identify as being \u201cseen\u201d were unrelated to those faces easy to reject as being \u201cunseen.\u201d PCA was performed on three data sets: (1) face images with eye position standardized, (2) face images morphed to a standard template to remove shape information, and (3) the shape information from faces only. Analyses based on PCA of shape-free faces gave high predictions of FPs, whereas shape information itself contributed only to hits. Furthermore, whereas FPs were generally predictable from components early in the PCA, hits appeared to be accounted for by later components. We conclude that shape and \u201ctexture\u201d (the image-based information remaining after morphing) may be used separately by the human face processing system, and that PCA of images offers a useful tool for understanding this system.", 
    "genre": "article", 
    "id": "sg:pub.10.3758/bf03197270", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1016414", 
        "issn": [
          "0090-502X", 
          "1532-5946"
        ], 
        "name": "Memory & Cognition", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "24"
      }
    ], 
    "keywords": [
      "human face processing system", 
      "face processing system", 
      "shape information", 
      "set of faces", 
      "face images", 
      "human perception", 
      "experiment subjects", 
      "late components", 
      "face", 
      "same image", 
      "eye position", 
      "principal component analysis", 
      "processing system", 
      "perception", 
      "high prediction", 
      "distinctiveness", 
      "component analysis", 
      "subjects", 
      "information", 
      "previous work", 
      "standard template", 
      "images", 
      "false positives", 
      "performance", 
      "hits", 
      "prediction", 
      "set", 
      "components", 
      "analysis", 
      "useful tool", 
      "positives", 
      "work", 
      "tool", 
      "superset", 
      "data sets", 
      "system", 
      "position", 
      "shape", 
      "texture", 
      "template"
    ], 
    "name": "Face processing: Human perception and principal components analysis", 
    "pagination": "26-40", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1009736800"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.3758/bf03197270"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "8822156"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.3758/bf03197270", 
      "https://app.dimensions.ai/details/publication/pub.1009736800"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-05-10T09:46", 
    "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_307.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.3758/bf03197270"
  }
]
 

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.10.3758/bf03197270'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.3758/bf03197270'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.3758/bf03197270'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.3758/bf03197270'


 

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

177 TRIPLES      22 PREDICATES      81 URIs      69 LITERALS      17 BLANK NODES

Subject Predicate Object
1 sg:pub.10.3758/bf03197270 schema:about N2b1c692a55df4bb0bb31af668f8d0f94
2 N3a40a52f48cf45c4966a9f7656bc96d7
3 N56ba3b1075564705b50b204bf9fab7b0
4 N84885242684540ae871cd4381327e551
5 Nc60de725088448089a13ada2ec8ae6be
6 Nc7680d324d7e4513b6b4bcbe225929a5
7 Nd696fe70a74c4437abe84eefa899bf41
8 Neafc3cd98f254db3af7dce80231c79c0
9 Ned22c9b06f9447669391bad662c148c8
10 Nf8207160a44e4717967b5119f5208f55
11 anzsrc-for:17
12 anzsrc-for:1701
13 schema:author N3f9fa5d0fc91436e83b674d8350d6e2e
14 schema:citation sg:pub.10.1007/978-1-4471-1921-0_52
15 sg:pub.10.1007/978-94-009-4420-6_42
16 sg:pub.10.3758/bf03199666
17 sg:pub.10.3758/bf03208892
18 schema:datePublished 1996-01
19 schema:datePublishedReg 1996-01-01
20 schema:description Principal components analysis (PCA) of face images is here related to subjects’ performance on the same images. In two experiments subjects were shown a set of faces and asked to rate them for distinctiveness. They were subsequently shown a superset of faces and asked to identify those that had appeared originally. Replicating previous work, we found that hits and false positives (FPs) did not correlate: Those faces easy to identify as being “seen” were unrelated to those faces easy to reject as being “unseen.” PCA was performed on three data sets: (1) face images with eye position standardized, (2) face images morphed to a standard template to remove shape information, and (3) the shape information from faces only. Analyses based on PCA of shape-free faces gave high predictions of FPs, whereas shape information itself contributed only to hits. Furthermore, whereas FPs were generally predictable from components early in the PCA, hits appeared to be accounted for by later components. We conclude that shape and “texture” (the image-based information remaining after morphing) may be used separately by the human face processing system, and that PCA of images offers a useful tool for understanding this system.
21 schema:genre article
22 schema:inLanguage en
23 schema:isAccessibleForFree true
24 schema:isPartOf N03e9dcdf4c934fafb5cb478cd724ab4c
25 Nb357966194aa4eb586347d7add59b713
26 sg:journal.1016414
27 schema:keywords analysis
28 component analysis
29 components
30 data sets
31 distinctiveness
32 experiment subjects
33 eye position
34 face
35 face images
36 face processing system
37 false positives
38 high prediction
39 hits
40 human face processing system
41 human perception
42 images
43 information
44 late components
45 perception
46 performance
47 position
48 positives
49 prediction
50 previous work
51 principal component analysis
52 processing system
53 same image
54 set
55 set of faces
56 shape
57 shape information
58 standard template
59 subjects
60 superset
61 system
62 template
63 texture
64 tool
65 useful tool
66 work
67 schema:name Face processing: Human perception and principal components analysis
68 schema:pagination 26-40
69 schema:productId N2208faa4cbf142d4860cf9dd88df32c0
70 N8e922b268c2d46bd9536f10a5b6c0557
71 N93e1831142bb44b487b7c5989c3c8b21
72 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009736800
73 https://doi.org/10.3758/bf03197270
74 schema:sdDatePublished 2022-05-10T09:46
75 schema:sdLicense https://scigraph.springernature.com/explorer/license/
76 schema:sdPublisher N8a14d84ee9d444518ea534f51e109c39
77 schema:url https://doi.org/10.3758/bf03197270
78 sgo:license sg:explorer/license/
79 sgo:sdDataset articles
80 rdf:type schema:ScholarlyArticle
81 N03e9dcdf4c934fafb5cb478cd724ab4c schema:issueNumber 1
82 rdf:type schema:PublicationIssue
83 N2208faa4cbf142d4860cf9dd88df32c0 schema:name doi
84 schema:value 10.3758/bf03197270
85 rdf:type schema:PropertyValue
86 N2b1c692a55df4bb0bb31af668f8d0f94 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
87 schema:name Adult
88 rdf:type schema:DefinedTerm
89 N3a40a52f48cf45c4966a9f7656bc96d7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Male
91 rdf:type schema:DefinedTerm
92 N3f9fa5d0fc91436e83b674d8350d6e2e rdf:first sg:person.012352566236.75
93 rdf:rest N639afa074c5f4eb4aa761abfa7064292
94 N56ba3b1075564705b50b204bf9fab7b0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
95 schema:name Psychophysics
96 rdf:type schema:DefinedTerm
97 N639afa074c5f4eb4aa761abfa7064292 rdf:first sg:person.01261533174.87
98 rdf:rest N8e5b0c253637403f8d256543bbb945af
99 N84885242684540ae871cd4381327e551 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Female
101 rdf:type schema:DefinedTerm
102 N8a14d84ee9d444518ea534f51e109c39 schema:name Springer Nature - SN SciGraph project
103 rdf:type schema:Organization
104 N8e5b0c253637403f8d256543bbb945af rdf:first sg:person.0775026766.00
105 rdf:rest rdf:nil
106 N8e922b268c2d46bd9536f10a5b6c0557 schema:name dimensions_id
107 schema:value pub.1009736800
108 rdf:type schema:PropertyValue
109 N93e1831142bb44b487b7c5989c3c8b21 schema:name pubmed_id
110 schema:value 8822156
111 rdf:type schema:PropertyValue
112 Nb357966194aa4eb586347d7add59b713 schema:volumeNumber 24
113 rdf:type schema:PublicationVolume
114 Nc60de725088448089a13ada2ec8ae6be schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Humans
116 rdf:type schema:DefinedTerm
117 Nc7680d324d7e4513b6b4bcbe225929a5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Face
119 rdf:type schema:DefinedTerm
120 Nd696fe70a74c4437abe84eefa899bf41 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Discrimination Learning
122 rdf:type schema:DefinedTerm
123 Neafc3cd98f254db3af7dce80231c79c0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
124 schema:name Mental Recall
125 rdf:type schema:DefinedTerm
126 Ned22c9b06f9447669391bad662c148c8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Pattern Recognition, Visual
128 rdf:type schema:DefinedTerm
129 Nf8207160a44e4717967b5119f5208f55 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
130 schema:name Attention
131 rdf:type schema:DefinedTerm
132 anzsrc-for:17 schema:inDefinedTermSet anzsrc-for:
133 schema:name Psychology and Cognitive Sciences
134 rdf:type schema:DefinedTerm
135 anzsrc-for:1701 schema:inDefinedTermSet anzsrc-for:
136 schema:name Psychology
137 rdf:type schema:DefinedTerm
138 sg:journal.1016414 schema:issn 0090-502X
139 1532-5946
140 schema:name Memory & Cognition
141 schema:publisher Springer Nature
142 rdf:type schema:Periodical
143 sg:person.012352566236.75 schema:affiliation grid-institutes:grid.11918.30
144 schema:familyName Hancock
145 schema:givenName Peter J. B.
146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012352566236.75
147 rdf:type schema:Person
148 sg:person.01261533174.87 schema:affiliation grid-institutes:grid.8756.c
149 schema:familyName Burton
150 schema:givenName A. Mike
151 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01261533174.87
152 rdf:type schema:Person
153 sg:person.0775026766.00 schema:affiliation grid-institutes:grid.11918.30
154 schema:familyName Bruce
155 schema:givenName Vicki
156 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0775026766.00
157 rdf:type schema:Person
158 sg:pub.10.1007/978-1-4471-1921-0_52 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013064816
159 https://doi.org/10.1007/978-1-4471-1921-0_52
160 rdf:type schema:CreativeWork
161 sg:pub.10.1007/978-94-009-4420-6_42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018701013
162 https://doi.org/10.1007/978-94-009-4420-6_42
163 rdf:type schema:CreativeWork
164 sg:pub.10.3758/bf03199666 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022512165
165 https://doi.org/10.3758/bf03199666
166 rdf:type schema:CreativeWork
167 sg:pub.10.3758/bf03208892 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050506185
168 https://doi.org/10.3758/bf03208892
169 rdf:type schema:CreativeWork
170 grid-institutes:grid.11918.30 schema:alternateName Department of Psychology, University of Stirling, FK9 4LA, Stirling, Scotland, UK
171 University of Stirling, Stirling, Scotland
172 schema:name Department of Psychology, University of Stirling, FK9 4LA, Stirling, Scotland, UK
173 University of Stirling, Stirling, Scotland
174 rdf:type schema:Organization
175 grid-institutes:grid.8756.c schema:alternateName University of Glasgow, Glasgow, Scotland
176 schema:name University of Glasgow, Glasgow, Scotland
177 rdf:type schema:Organization
 




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


...