CYKLS: Detect Pedestrian’s Dart Focusing on an Appearance Change View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012

AUTHORS

Masahiro Ogawa , Hideo Fukamachi , Ryuji Funayama , Toshiki Kindo

ABSTRACT

We propose a new method for detecting “pedestrians’ dart” to support drivers cognition in real traffic scenario. The main idea is to detect sudden appearance change of pedestrians before their consequent actions happen. Our new algorithm, called “Chronologically Yielded values of Kullback-Leibler divergence between Separate frames” (CYKLS), is a combination of two main procedures: (1) calculation of appearance change by Kullback-Leibler divergence between descriptors in some time interval frames, and (2) detection of non-periodic sequence by a new smoothing method in the field of time series analysis. We can detect pedestrians’ dart with 22% Equal Error Rate, using a dataset which includes 144 dart scenes. More... »

PAGES

556-565

References to SciGraph publications

Book

TITLE

Computer Vision – ECCV 2012. Workshops and Demonstrations

ISBN

978-3-642-33867-0
978-3-642-33868-7

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-33868-7_55

DOI

http://dx.doi.org/10.1007/978-3-642-33868-7_55

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1020307271


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/2008/1701", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Psychology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/17", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Psychology and Cognitive Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Toyota Motor Corporation (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.462975.b", 
          "name": [
            "Future Project div., Toyota Motor Co., 1200, Mishuku, Susono, Shizuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ogawa", 
        "givenName": "Masahiro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Toyota Motor Corporation (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.462975.b", 
          "name": [
            "Future Project div., Toyota Motor Co., 1200, Mishuku, Susono, Shizuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fukamachi", 
        "givenName": "Hideo", 
        "id": "sg:person.012773371067.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012773371067.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Toyota Motor Corporation (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.462975.b", 
          "name": [
            "Future Project div., Toyota Motor Co., 1200, Mishuku, Susono, Shizuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Funayama", 
        "givenName": "Ryuji", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Toyota Motor Corporation (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.462975.b", 
          "name": [
            "Future Project div., Toyota Motor Co., 1200, Mishuku, Susono, Shizuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kindo", 
        "givenName": "Toshiki", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/978-3-642-15561-1_42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015745824", 
          "https://doi.org/10.1007/978-3-642-15561-1_42"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-15561-1_42", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015745824", 
          "https://doi.org/10.1007/978-3-642-15561-1_42"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoms/1177729694", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026070931"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11550518_27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027019995", 
          "https://doi.org/10.1007/11550518_27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/11550518_27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027019995", 
          "https://doi.org/10.1007/11550518_27"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-02611-9_34", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038785677", 
          "https://doi.org/10.1007/978-3-642-02611-9_34"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-02611-9_34", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038785677", 
          "https://doi.org/10.1007/978-3-642-02611-9_34"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/b:visi.0000029664.99615.94", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052687286", 
          "https://doi.org/10.1023/b:visi.0000029664.99615.94"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2002.1017623", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061742396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tpami.2007.70825", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061743439"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2005.328", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094262424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cvpr.2010.5540156", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094783185"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iccv.2009.5459201", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095371836"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5244/c.25.21", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1099341364"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2012", 
    "datePublishedReg": "2012-01-01", 
    "description": "We propose a new method for detecting \u201cpedestrians\u2019 dart\u201d to support drivers cognition in real traffic scenario. The main idea is to detect sudden appearance change of pedestrians before their consequent actions happen. Our new algorithm, called \u201cChronologically Yielded values of Kullback-Leibler divergence between Separate frames\u201d (CYKLS), is a combination of two main procedures: (1) calculation of appearance change by Kullback-Leibler divergence between descriptors in some time interval frames, and (2) detection of non-periodic sequence by a new smoothing method in the field of time series analysis. We can detect pedestrians\u2019 dart with 22% Equal Error Rate, using a dataset which includes 144 dart scenes.", 
    "editor": [
      {
        "familyName": "Fusiello", 
        "givenName": "Andrea", 
        "type": "Person"
      }, 
      {
        "familyName": "Murino", 
        "givenName": "Vittorio", 
        "type": "Person"
      }, 
      {
        "familyName": "Cucchiara", 
        "givenName": "Rita", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-33868-7_55", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-642-33867-0", 
        "978-3-642-33868-7"
      ], 
      "name": "Computer Vision \u2013 ECCV 2012. Workshops and Demonstrations", 
      "type": "Book"
    }, 
    "name": "CYKLS: Detect Pedestrian\u2019s Dart Focusing on an Appearance Change", 
    "pagination": "556-565", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-33868-7_55"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "60c25d9275cb7a26c7d878cbbdcfcea40744b81f43c9912cc1afd7c716b2ea72"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1020307271"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-33868-7_55", 
      "https://app.dimensions.ai/details/publication/pub.1020307271"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T10:33", 
    "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/v90/0000000001_0000000264/records_8659_00000255.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-642-33868-7_55"
  }
]
 

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.10.1007/978-3-642-33868-7_55'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-33868-7_55'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-33868-7_55'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-33868-7_55'


 

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

130 TRIPLES      23 PREDICATES      38 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-33868-7_55 schema:about anzsrc-for:17
2 anzsrc-for:1701
3 schema:author N90273537c86147179ed2f17f2d2586f7
4 schema:citation sg:pub.10.1007/11550518_27
5 sg:pub.10.1007/978-3-642-02611-9_34
6 sg:pub.10.1007/978-3-642-15561-1_42
7 sg:pub.10.1023/b:visi.0000029664.99615.94
8 https://doi.org/10.1109/cvpr.2005.328
9 https://doi.org/10.1109/cvpr.2010.5540156
10 https://doi.org/10.1109/iccv.2009.5459201
11 https://doi.org/10.1109/tpami.2002.1017623
12 https://doi.org/10.1109/tpami.2007.70825
13 https://doi.org/10.1214/aoms/1177729694
14 https://doi.org/10.5244/c.25.21
15 schema:datePublished 2012
16 schema:datePublishedReg 2012-01-01
17 schema:description We propose a new method for detecting “pedestrians’ dart” to support drivers cognition in real traffic scenario. The main idea is to detect sudden appearance change of pedestrians before their consequent actions happen. Our new algorithm, called “Chronologically Yielded values of Kullback-Leibler divergence between Separate frames” (CYKLS), is a combination of two main procedures: (1) calculation of appearance change by Kullback-Leibler divergence between descriptors in some time interval frames, and (2) detection of non-periodic sequence by a new smoothing method in the field of time series analysis. We can detect pedestrians’ dart with 22% Equal Error Rate, using a dataset which includes 144 dart scenes.
18 schema:editor Nb0d8b89698164f2986a763ed0adcee87
19 schema:genre chapter
20 schema:inLanguage en
21 schema:isAccessibleForFree false
22 schema:isPartOf Ndf8d8698210549b38d3cf331be1b3756
23 schema:name CYKLS: Detect Pedestrian’s Dart Focusing on an Appearance Change
24 schema:pagination 556-565
25 schema:productId N35f9eb6bb670481583e360d0b49a9f2c
26 N5f0b4efc04f04fe1a1affdd539b8f14e
27 N977f848b8e1145acb6b69b86689bb983
28 schema:publisher N4d90bd03f1a84947bf6bc82b8deb948d
29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020307271
30 https://doi.org/10.1007/978-3-642-33868-7_55
31 schema:sdDatePublished 2019-04-15T10:33
32 schema:sdLicense https://scigraph.springernature.com/explorer/license/
33 schema:sdPublisher N5ac0aaee575143c1952c4ab952e27dd4
34 schema:url http://link.springer.com/10.1007/978-3-642-33868-7_55
35 sgo:license sg:explorer/license/
36 sgo:sdDataset chapters
37 rdf:type schema:Chapter
38 N229246c0b4dc4c29a0c542da27e04efc rdf:first Nbcc52605c40f49e4820149a4a4de4d11
39 rdf:rest Nb17183ba66a64ddcbe3a0fd65ae5c48a
40 N35f9eb6bb670481583e360d0b49a9f2c schema:name dimensions_id
41 schema:value pub.1020307271
42 rdf:type schema:PropertyValue
43 N3f55b2d9b1ea464d9ba9490d62de10b7 schema:familyName Cucchiara
44 schema:givenName Rita
45 rdf:type schema:Person
46 N4d90bd03f1a84947bf6bc82b8deb948d schema:location Berlin, Heidelberg
47 schema:name Springer Berlin Heidelberg
48 rdf:type schema:Organisation
49 N4f094287452c4d5190f36d22da993b2a schema:affiliation https://www.grid.ac/institutes/grid.462975.b
50 schema:familyName Kindo
51 schema:givenName Toshiki
52 rdf:type schema:Person
53 N5ac0aaee575143c1952c4ab952e27dd4 schema:name Springer Nature - SN SciGraph project
54 rdf:type schema:Organization
55 N5f0b4efc04f04fe1a1affdd539b8f14e schema:name readcube_id
56 schema:value 60c25d9275cb7a26c7d878cbbdcfcea40744b81f43c9912cc1afd7c716b2ea72
57 rdf:type schema:PropertyValue
58 N77010fe45ee24f52b8194b274b2350ce rdf:first sg:person.012773371067.05
59 rdf:rest Nd094205365af418f85dd3599e35895ab
60 N80cc2dcf839940acb8aa41d0aca56495 schema:familyName Fusiello
61 schema:givenName Andrea
62 rdf:type schema:Person
63 N8983964a64ad4c48894f704f58d49ecb schema:affiliation https://www.grid.ac/institutes/grid.462975.b
64 schema:familyName Ogawa
65 schema:givenName Masahiro
66 rdf:type schema:Person
67 N90273537c86147179ed2f17f2d2586f7 rdf:first N8983964a64ad4c48894f704f58d49ecb
68 rdf:rest N77010fe45ee24f52b8194b274b2350ce
69 N977f848b8e1145acb6b69b86689bb983 schema:name doi
70 schema:value 10.1007/978-3-642-33868-7_55
71 rdf:type schema:PropertyValue
72 Nb0d8b89698164f2986a763ed0adcee87 rdf:first N80cc2dcf839940acb8aa41d0aca56495
73 rdf:rest N229246c0b4dc4c29a0c542da27e04efc
74 Nb17183ba66a64ddcbe3a0fd65ae5c48a rdf:first N3f55b2d9b1ea464d9ba9490d62de10b7
75 rdf:rest rdf:nil
76 Nbcc52605c40f49e4820149a4a4de4d11 schema:familyName Murino
77 schema:givenName Vittorio
78 rdf:type schema:Person
79 Nd094205365af418f85dd3599e35895ab rdf:first Nd960f911e13d4d4ba630ab82625ed766
80 rdf:rest Nd5578e0f370341359dfe11964111174d
81 Nd5578e0f370341359dfe11964111174d rdf:first N4f094287452c4d5190f36d22da993b2a
82 rdf:rest rdf:nil
83 Nd960f911e13d4d4ba630ab82625ed766 schema:affiliation https://www.grid.ac/institutes/grid.462975.b
84 schema:familyName Funayama
85 schema:givenName Ryuji
86 rdf:type schema:Person
87 Ndf8d8698210549b38d3cf331be1b3756 schema:isbn 978-3-642-33867-0
88 978-3-642-33868-7
89 schema:name Computer Vision – ECCV 2012. Workshops and Demonstrations
90 rdf:type schema:Book
91 anzsrc-for:17 schema:inDefinedTermSet anzsrc-for:
92 schema:name Psychology and Cognitive Sciences
93 rdf:type schema:DefinedTerm
94 anzsrc-for:1701 schema:inDefinedTermSet anzsrc-for:
95 schema:name Psychology
96 rdf:type schema:DefinedTerm
97 sg:person.012773371067.05 schema:affiliation https://www.grid.ac/institutes/grid.462975.b
98 schema:familyName Fukamachi
99 schema:givenName Hideo
100 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012773371067.05
101 rdf:type schema:Person
102 sg:pub.10.1007/11550518_27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027019995
103 https://doi.org/10.1007/11550518_27
104 rdf:type schema:CreativeWork
105 sg:pub.10.1007/978-3-642-02611-9_34 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038785677
106 https://doi.org/10.1007/978-3-642-02611-9_34
107 rdf:type schema:CreativeWork
108 sg:pub.10.1007/978-3-642-15561-1_42 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015745824
109 https://doi.org/10.1007/978-3-642-15561-1_42
110 rdf:type schema:CreativeWork
111 sg:pub.10.1023/b:visi.0000029664.99615.94 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052687286
112 https://doi.org/10.1023/b:visi.0000029664.99615.94
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1109/cvpr.2005.328 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094262424
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1109/cvpr.2010.5540156 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094783185
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1109/iccv.2009.5459201 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095371836
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1109/tpami.2002.1017623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061742396
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1109/tpami.2007.70825 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061743439
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1214/aoms/1177729694 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026070931
125 rdf:type schema:CreativeWork
126 https://doi.org/10.5244/c.25.21 schema:sameAs https://app.dimensions.ai/details/publication/pub.1099341364
127 rdf:type schema:CreativeWork
128 https://www.grid.ac/institutes/grid.462975.b schema:alternateName Toyota Motor Corporation (Japan)
129 schema:name Future Project div., Toyota Motor Co., 1200, Mishuku, Susono, Shizuoka, Japan
130 rdf:type schema:Organization
 




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


...