{"id":"https://openalex.org/W2061072542","doi":"https://doi.org/10.1163/156855399x00144","title":"Moving obstacle detection and recognition by optical flow pattern analysis for mobile robots","display_name":"Moving obstacle detection and recognition by optical flow pattern analysis for mobile robots","publication_year":1997,"publication_date":"1997-01-01","ids":{"openalex":"https://openalex.org/W2061072542","doi":"https://doi.org/10.1163/156855399x00144","mag":"2061072542"},"language":"en","primary_location":{"id":"doi:10.1163/156855399x00144","is_oa":false,"landing_page_url":"https://doi.org/10.1163/156855399x00144","pdf_url":null,"source":{"id":"https://openalex.org/S192584203","display_name":"Advanced Robotics","issn_l":"0169-1864","issn":["0169-1864","1568-5535"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advanced Robotics","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/A5112292903","display_name":"Mutsumi Watanabe","orcid":null},"institutions":[{"id":"https://openalex.org/I197065826","display_name":"Kobe Pharmaceutical University","ror":"https://ror.org/00088z429","country_code":"JP","type":"education","lineage":["https://openalex.org/I197065826"]},{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Mutsumi Watanabe","raw_affiliation_strings":["a    Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan"],"affiliations":[{"raw_affiliation_string":"a    Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","institution_ids":["https://openalex.org/I197065826"]},{"raw_affiliation_string":"Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","institution_ids":["https://openalex.org/I1292669757"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032298307","display_name":"N. Takeda","orcid":null},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]},{"id":"https://openalex.org/I197065826","display_name":"Kobe Pharmaceutical University","ror":"https://ror.org/00088z429","country_code":"JP","type":"education","lineage":["https://openalex.org/I197065826"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobuyuki Takeda","raw_affiliation_strings":["b    Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan"],"affiliations":[{"raw_affiliation_string":"b    Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","institution_ids":["https://openalex.org/I197065826"]},{"raw_affiliation_string":"Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","institution_ids":["https://openalex.org/I1292669757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015672702","display_name":"Kazunori Onoguchi","orcid":null},"institutions":[{"id":"https://openalex.org/I1292669757","display_name":"Toshiba (Japan)","ror":"https://ror.org/0326v3z14","country_code":"JP","type":"company","lineage":["https://openalex.org/I1292669757"]},{"id":"https://openalex.org/I197065826","display_name":"Kobe Pharmaceutical University","ror":"https://ror.org/00088z429","country_code":"JP","type":"education","lineage":["https://openalex.org/I197065826"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazunori Onoguchi","raw_affiliation_strings":["c    Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan"],"affiliations":[{"raw_affiliation_string":"c    Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","institution_ids":["https://openalex.org/I197065826"]},{"raw_affiliation_string":"Toshiba Kansai Research Laboratories, 8-6-26, Motoyama-Minarrei-Machi, Higashinada-ku, Kobe 658, Japan","institution_ids":["https://openalex.org/I1292669757"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112292903"],"corresponding_institution_ids":["https://openalex.org/I1292669757","https://openalex.org/I197065826"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.17624987,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"7-8","first_page":"791","last_page":"816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7974690198898315},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7749409675598145},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.7205166816711426},{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.6948438286781311},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6124459505081177},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5661991238594055},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5249714255332947},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.5013034343719482},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.48704078793525696},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47485995292663574},{"id":"https://openalex.org/keywords/inertia","display_name":"Inertia","score":0.4740409851074219},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.4665166139602661},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.41562968492507935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3712223172187805},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21770194172859192},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16690880060195923},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11775729060173035},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11621853709220886},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0986858606338501}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7974690198898315},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7749409675598145},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.7205166816711426},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.6948438286781311},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6124459505081177},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5661991238594055},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5249714255332947},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.5013034343719482},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.48704078793525696},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47485995292663574},{"id":"https://openalex.org/C110407247","wikidata":"https://www.wikidata.org/wiki/Q122508","display_name":"Inertia","level":2,"score":0.4740409851074219},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.4665166139602661},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.41562968492507935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3712223172187805},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21770194172859192},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16690880060195923},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11775729060173035},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11621853709220886},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0986858606338501},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1163/156855399x00144","is_oa":false,"landing_page_url":"https://doi.org/10.1163/156855399x00144","pdf_url":null,"source":{"id":"https://openalex.org/S192584203","display_name":"Advanced Robotics","issn_l":"0169-1864","issn":["0169-1864","1568-5535"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advanced Robotics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1901706607","https://openalex.org/W2043003144","https://openalex.org/W2069239883","https://openalex.org/W2092229301","https://openalex.org/W2095905764","https://openalex.org/W2102116384","https://openalex.org/W2104836257","https://openalex.org/W2142859597","https://openalex.org/W2145086237","https://openalex.org/W2163085736","https://openalex.org/W2164820175","https://openalex.org/W2166967166","https://openalex.org/W2914331897"],"related_works":["https://openalex.org/W2794103424","https://openalex.org/W4245435724","https://openalex.org/W1996530509","https://openalex.org/W3028317537","https://openalex.org/W2389515972","https://openalex.org/W2055301889","https://openalex.org/W1566521282","https://openalex.org/W2017159956","https://openalex.org/W2281433634","https://openalex.org/W3009037905"],"abstract_inverted_index":{"\u2014This":[0],"paper":[1],"presents":[2],"a":[3,34,37,48],"new":[4],"idea":[5],"for":[6,11,80,136],"an":[7,113],"obstacle":[8],"recognition":[9,149],"method":[10],"mobile":[12],"robots":[13],"by":[14,46,124,142],"analyzing":[15],"optical":[16,25,72],"flow":[17,26,73],"information":[18],"acquired":[19],"from":[20,33],"dynamic":[21],"images.":[22],"First,":[23],"the":[24,64,68,71,81,90,95,101,104,122,126,129,137,156,159],"field":[27],"is":[28,61,110,117],"detected":[29],"in":[30,63,84,121,150],"image":[31],"sequences":[32],"camera":[35],"on":[36],"moving":[38,41],"observer":[39],"and":[40,75,100,128],"object":[42,114],"candidates":[43],"are":[44,78,140],"extracted":[45],"using":[47],"normalized":[49],"square":[50],"residual":[51,57],"error":[52],"[focus":[53],"of":[54,66,98,103,147,158],"expansion":[55],"(FOE)":[56],"error]":[58],"value":[59],"that":[60,116],"calculated":[62],"process":[65],"estimating":[67],"FOE.":[69],"Next,":[70],"directions":[74],"intensity":[76],"values":[77,93,131],"stored":[79],"pixels":[82],"involved":[83],"each":[85,108],"candidate":[86,109],"region":[87],"to":[88,119],"calculate":[89],"distribution":[91],"width":[92],"around":[94],"principal":[96,105],"axes":[97],"inertia":[99],"direction":[102,130],"axes.":[106],"Finally,":[107],"classified":[111],"into":[112],"category":[115],"expected":[118],"appear":[120],"scene":[123],"comparing":[125],"proportion":[127],"with":[132],"standard":[133],"data":[134],"ranges":[135],"objects":[138],"which":[139],"determined":[141],"preliminary":[143],"experiments.":[144],"Experimental":[145],"results":[146],"car/bicycle/pedestrian":[148],"real":[151],"outdoor":[152],"scenes":[153],"have":[154],"shown":[155],"effectiveness":[157],"proposed":[160],"method.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
