{"id":"https://openalex.org/W2736155990","doi":"https://doi.org/10.1109/tiv.2017.2726764","title":"SpaFIND: an Effective and Low-cost Feature Descriptor for Pedestrian Protection Systems in Economy Cars","display_name":"SpaFIND: an Effective and Low-cost Feature Descriptor for Pedestrian Protection Systems in Economy Cars","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2736155990","doi":"https://doi.org/10.1109/tiv.2017.2726764","mag":"2736155990"},"language":"en","primary_location":{"id":"doi:10.1109/tiv.2017.2726764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2017.2726764","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Vehicles","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101406574","display_name":"Takeo Kato","orcid":"https://orcid.org/0000-0002-1098-8505"},"institutions":[{"id":"https://openalex.org/I4210165351","display_name":"Toyota Central Research and Development Laboratories (Japan)","ror":"https://ror.org/05mjgqe69","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210165351"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takeo Kato","raw_affiliation_strings":["Toyota Central R&D Labs., Inc., Nagakute, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Central R&D Labs., Inc., Nagakute, Japan","institution_ids":["https://openalex.org/I4210165351"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008333736","display_name":"Chunzhao Guo","orcid":"https://orcid.org/0000-0002-2992-6320"},"institutions":[{"id":"https://openalex.org/I4210165351","display_name":"Toyota Central Research and Development Laboratories (Japan)","ror":"https://ror.org/05mjgqe69","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210165351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chunzhao Guo","raw_affiliation_strings":["Toyota Central R&D Labs., Inc., Nagakute, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Central R&D Labs., Inc., Nagakute, Japan","institution_ids":["https://openalex.org/I4210165351"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015264512","display_name":"Kiyosumi Kidono","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165351","display_name":"Toyota Central Research and Development Laboratories (Japan)","ror":"https://ror.org/05mjgqe69","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210165351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyosumi Kidono","raw_affiliation_strings":["Toyota Central R&D Labs., Inc., Nagakute, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Central R&D Labs., Inc., Nagakute, Japan","institution_ids":["https://openalex.org/I4210165351"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101464193","display_name":"Yoshiko Kojima","orcid":"https://orcid.org/0000-0003-0777-3308"},"institutions":[{"id":"https://openalex.org/I4210165351","display_name":"Toyota Central Research and Development Laboratories (Japan)","ror":"https://ror.org/05mjgqe69","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210165351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiko Kojima","raw_affiliation_strings":["Toyota Central R&D Labs., Inc., Nagakute, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Central R&D Labs., Inc., Nagakute, Japan","institution_ids":["https://openalex.org/I4210165351"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112678813","display_name":"Takashi Naito","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165351","display_name":"Toyota Central Research and Development Laboratories (Japan)","ror":"https://ror.org/05mjgqe69","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210165351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takashi Naito","raw_affiliation_strings":["Toyota Central R&D Labs., Inc., Nagakute, Japan"],"affiliations":[{"raw_affiliation_string":"Toyota Central R&D Labs., Inc., Nagakute, Japan","institution_ids":["https://openalex.org/I4210165351"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101406574"],"corresponding_institution_ids":["https://openalex.org/I4210165351"],"apc_list":null,"apc_paid":null,"fwci":0.4101,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68859859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7732291221618652},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.70875084400177},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6800609827041626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6420959234237671},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.623573899269104},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5687049627304077},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.5533339381217957},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5397354960441589},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5248501300811768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.417659729719162},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41292357444763184},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26163390278816223},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.24531200528144836},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.162733793258667}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7732291221618652},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.70875084400177},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6800609827041626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6420959234237671},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.623573899269104},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5687049627304077},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.5533339381217957},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5397354960441589},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5248501300811768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.417659729719162},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41292357444763184},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26163390278816223},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.24531200528144836},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.162733793258667},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tiv.2017.2726764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tiv.2017.2726764","pdf_url":null,"source":{"id":"https://openalex.org/S4210199657","display_name":"IEEE Transactions on Intelligent Vehicles","issn_l":"2379-8858","issn":["2379-8858","2379-8904"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Vehicles","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1147573925","https://openalex.org/W1475617732","https://openalex.org/W1482428446","https://openalex.org/W1528445814","https://openalex.org/W1536943225","https://openalex.org/W1560380655","https://openalex.org/W1599933961","https://openalex.org/W1870256699","https://openalex.org/W1882819926","https://openalex.org/W1950935069","https://openalex.org/W1992825118","https://openalex.org/W2020105253","https://openalex.org/W2031454541","https://openalex.org/W2077513643","https://openalex.org/W2081021369","https://openalex.org/W2098064689","https://openalex.org/W2099355420","https://openalex.org/W2102691275","https://openalex.org/W2107775979","https://openalex.org/W2110169948","https://openalex.org/W2118585731","https://openalex.org/W2120419212","https://openalex.org/W2125556102","https://openalex.org/W2133755669","https://openalex.org/W2133984628","https://openalex.org/W2134380836","https://openalex.org/W2156274307","https://openalex.org/W2156547346","https://openalex.org/W2161969291","https://openalex.org/W2162741153","https://openalex.org/W2163272476","https://openalex.org/W2163605009","https://openalex.org/W2164598857","https://openalex.org/W2168356304","https://openalex.org/W2169771895","https://openalex.org/W2170101770","https://openalex.org/W2184393491","https://openalex.org/W2200528286","https://openalex.org/W2265127172","https://openalex.org/W2315630558","https://openalex.org/W2342242867","https://openalex.org/W2412490945","https://openalex.org/W2468368736","https://openalex.org/W2474389331","https://openalex.org/W2490270993","https://openalex.org/W2497039038","https://openalex.org/W2531915888","https://openalex.org/W2541268671","https://openalex.org/W2581083154","https://openalex.org/W2950703487","https://openalex.org/W2952520845","https://openalex.org/W2963315052","https://openalex.org/W6633519119","https://openalex.org/W6635891616","https://openalex.org/W6639461879","https://openalex.org/W6674902714","https://openalex.org/W6674977583","https://openalex.org/W6677656871","https://openalex.org/W6684191040","https://openalex.org/W6684811926","https://openalex.org/W6686211706","https://openalex.org/W6703958665","https://openalex.org/W6722946945","https://openalex.org/W6728695229"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W1977648593","https://openalex.org/W2348780717","https://openalex.org/W2780165746","https://openalex.org/W4235475963","https://openalex.org/W4252030899","https://openalex.org/W3087821047","https://openalex.org/W2071599417","https://openalex.org/W2602033589"],"abstract_inverted_index":{"Pedestrian":[0,120],"protection":[1],"systems":[2],"(PPSs)":[3],"are":[4],"crucial":[5],"for":[6,46,147],"reducing":[7],"road":[8],"traffic":[9],"fatalities.":[10],"However,":[11],"the":[12,20,59,69,76,82,96,103,110,118,134,137,145,158,167],"relatively":[13],"high":[14],"cost":[15],"of":[16,22,61,75,85,99,109,125,136,161],"today's":[17],"PPSs":[18,162],"prevents":[19],"majority":[21],"economy":[23,55,164],"cars":[24,165],"from":[25],"receiving":[26],"their":[27],"benefits.":[28],"In":[29],"this":[30,100],"paper,":[31],"we":[32,105],"propose":[33],"an":[34],"effective":[35],"and":[36,66,128],"low-cost":[37,139],"sparse":[38],"feature":[39,65],"interaction":[40],"descriptor":[41],"(SpaFIND)":[42],"that":[43],"is":[44,95],"designed":[45],"real-time":[47],"pedestrian":[48],"detection":[49,126],"with":[50,151],"limited":[51,152],"computational":[52,92,129,153],"power":[53],"in":[54,123,163,166],"cars.":[56],"SpaFIND":[57,79,140],"extends":[58],"histogram":[60],"oriented":[62],"gradients":[63],"(HOG)":[64],"selectively":[67],"computes":[68],"pairwise":[70],"relationships":[71],"between":[72],"neighboring":[73],"components":[74],"HOG.":[77],"Therefore,":[78],"can":[80,143],"capture":[81],"second-order":[83],"properties":[84],"object":[86],"appearance":[87],"while":[88],"maintaining":[89],"a":[90,149],"low":[91],"load,":[93],"which":[94,142],"main":[97],"contribution":[98],"paper.":[101],"During":[102],"experiments,":[104],"performed":[106],"comparative":[107],"evaluations":[108],"proposed":[111,138],"system":[112],"against":[113],"several":[114],"baseline":[115],"methods":[116],"on":[117],"Caltech":[119],"Detection":[121],"Benchmark":[122],"terms":[124],"accuracy":[127],"load.":[130],"The":[131],"results":[132],"demonstrated":[133],"effectiveness":[135],"feature,":[141],"meet":[144],"requirements":[146],"implementing":[148],"PPS":[150],"power,":[154],"thereby":[155],"contributing":[156],"to":[157],"massive":[159],"deployment":[160],"immediate":[168],"future.":[169]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
