Ontology type: schema:Chapter
2011
AUTHORSJamal Saboune , Mehdi Arezoomand , Luc Martel , Robert Laganiere
ABSTRACTThe goal of this work is to propose a solution to improve a driver’s safety while changing lanes on the highway. In fact, if the driver is not aware of the presence of a vehicle in his blindspot a crash can occur. In this article we propose a method to monitor the blindspot zone using video feeds and warn the driver of any dangerous situation. In order to fit in a real time embedded car safety system, we avoid using any complex techniques such as classification and learning. The blindspot monitoring algorithm we expose here is based on a features tracking approach by optical flow calculation. The features to track are chosen essentially given their motion patterns that must match those of a moving vehicle and are filtered in order to overcome the presence of noise. We can then take a decision on a car presence in the blindspot given the tracked features density. To illustrate our approach we present some results using video feeds captured on the highway. More... »
PAGES1-10
Image Analysis and Processing – ICIAP 2011
ISBN
978-3-642-24087-4
978-3-642-24088-1
http://scigraph.springernature.com/pub.10.1007/978-3-642-24088-1_1
DOIhttp://dx.doi.org/10.1007/978-3-642-24088-1_1
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1018236018
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/2008/0801",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Artificial Intelligence and Image Processing",
"type": "DefinedTerm"
},
{
"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"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of Ottawa",
"id": "https://www.grid.ac/institutes/grid.28046.38",
"name": [
"VIVA Lab, School of Information Technology and Engineering, University of Ottawa, K1N 6N5, Ottawa, Ontario, Canada"
],
"type": "Organization"
},
"familyName": "Saboune",
"givenName": "Jamal",
"id": "sg:person.013255072032.33",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013255072032.33"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Ottawa",
"id": "https://www.grid.ac/institutes/grid.28046.38",
"name": [
"VIVA Lab, School of Information Technology and Engineering, University of Ottawa, K1N 6N5, Ottawa, Ontario, Canada"
],
"type": "Organization"
},
"familyName": "Arezoomand",
"givenName": "Mehdi",
"type": "Person"
},
{
"affiliation": {
"alternateName": "Mtekvision (Canada)",
"id": "https://www.grid.ac/institutes/grid.450649.a",
"name": [
"Cognivue Corporation, J8X 4B5, Gatineau, Quebec, Canada"
],
"type": "Organization"
},
"familyName": "Martel",
"givenName": "Luc",
"id": "sg:person.014416263615.47",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014416263615.47"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of Ottawa",
"id": "https://www.grid.ac/institutes/grid.28046.38",
"name": [
"VIVA Lab, School of Information Technology and Engineering, University of Ottawa, K1N 6N5, Ottawa, Ontario, Canada"
],
"type": "Organization"
},
"familyName": "Laganiere",
"givenName": "Robert",
"id": "sg:person.01144533722.06",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01144533722.06"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/s001380050126",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1000018061",
"https://doi.org/10.1007/s001380050126"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-642-04772-5_42",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004237034",
"https://doi.org/10.1007/978-3-642-04772-5_42"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-642-12990-2_79",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013914455",
"https://doi.org/10.1007/978-3-642-12990-2_79"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-642-12990-2_79",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013914455",
"https://doi.org/10.1007/978-3-642-12990-2_79"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10514-005-0611-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016041408",
"https://doi.org/10.1007/s10514-005-0611-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s10514-005-0611-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1016041408",
"https://doi.org/10.1007/s10514-005-0611-7"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3390/s100100860",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1049799618"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1049/iet-its:20070031",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1056830144"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tits.2002.802932",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061657262"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvt.2005.844655",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061818563"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/tvt.2008.917220",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1061819694"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/icmla.2008.129",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093252267"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2004.1336460",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093255187"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2004.1336447",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093262853"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/icsse.2010.5551779",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093370010"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2000.898354",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093412503"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/cvpr.1994.323794",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093488775"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/itsc.2009.5309876",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093646313"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/icip.2005.1530126",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093678131"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/itsc.1997.660564",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093806394"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2004.1336470",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1093965185"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2010.5548101",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094109631"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2007.4290198",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094316467"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/iros.2005.1545321",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094448135"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/ivs.2000.898315",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1094864888"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/itsc.2004.1398993",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1095062052"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1109/avss.2005.1577253",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1095648006"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.5220/0001637503590364",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1099366725"
],
"type": "CreativeWork"
}
],
"datePublished": "2011",
"datePublishedReg": "2011-01-01",
"description": "The goal of this work is to propose a solution to improve a driver\u2019s safety while changing lanes on the highway. In fact, if the driver is not aware of the presence of a vehicle in his blindspot a crash can occur. In this article we propose a method to monitor the blindspot zone using video feeds and warn the driver of any dangerous situation. In order to fit in a real time embedded car safety system, we avoid using any complex techniques such as classification and learning. The blindspot monitoring algorithm we expose here is based on a features tracking approach by optical flow calculation. The features to track are chosen essentially given their motion patterns that must match those of a moving vehicle and are filtered in order to overcome the presence of noise. We can then take a decision on a car presence in the blindspot given the tracked features density. To illustrate our approach we present some results using video feeds captured on the highway.",
"editor": [
{
"familyName": "Maino",
"givenName": "Giuseppe",
"type": "Person"
},
{
"familyName": "Foresti",
"givenName": "Gian Luca",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-642-24088-1_1",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-642-24087-4",
"978-3-642-24088-1"
],
"name": "Image Analysis and Processing \u2013 ICIAP 2011",
"type": "Book"
},
"name": "A Visual Blindspot Monitoring System for Safe Lane Changes",
"pagination": "1-10",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1018236018"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-642-24088-1_1"
]
},
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"56e33a4c172eb967ec54736dea114826c041f482a7acbefe0ccfd7991346c091"
]
}
],
"publisher": {
"location": "Berlin, Heidelberg",
"name": "Springer Berlin Heidelberg",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-642-24088-1_1",
"https://app.dimensions.ai/details/publication/pub.1018236018"
],
"sdDataset": "chapters",
"sdDatePublished": "2019-04-16T09:13",
"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/v90/0000000371_0000000371/records_130805_00000001.jsonl",
"type": "Chapter",
"url": "https://link.springer.com/10.1007%2F978-3-642-24088-1_1"
}
]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.10.1007/978-3-642-24088-1_1'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-24088-1_1'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-24088-1_1'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-24088-1_1'
This table displays all metadata directly associated to this object as RDF triples.
175 TRIPLES
23 PREDICATES
53 URIs
20 LITERALS
8 BLANK NODES