{"id":"https://openalex.org/W2954935528","doi":"https://doi.org/10.1109/aim.2019.8868536","title":"Exploiting the ACCuracy-ACCeleration tradeoff: VINS-assisted real-time object detection on moving systems","display_name":"Exploiting the ACCuracy-ACCeleration tradeoff: VINS-assisted real-time object detection on moving systems","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2954935528","doi":"https://doi.org/10.1109/aim.2019.8868536","mag":"2954935528"},"language":"en","primary_location":{"id":"doi:10.1109/aim.2019.8868536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aim.2019.8868536","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)","raw_type":"proceedings-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/A5083348881","display_name":"Betty Le Dem","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Betty Le Dem","raw_affiliation_strings":["Pr. Nakazawa Laboratory, University of Keio"],"affiliations":[{"raw_affiliation_string":"Pr. Nakazawa Laboratory, University of Keio","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100998539","display_name":"Kazuo Nakazawa","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuo Nakazawa","raw_affiliation_strings":["Associate Professor of Department of System Design Engineering, Keio University, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Associate Professor of Department of System Design Engineering, Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083348881"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.07248596,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"483","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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":0.9983999729156494,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.8503129482269287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7808054685592651},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.775896430015564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7088426351547241},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6740670204162598},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.641545832157135},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.610323965549469},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.5088406205177307},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5057735443115234},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.5039958357810974},{"id":"https://openalex.org/keywords/viola\u2013jones-object-detection-framework","display_name":"Viola\u2013Jones object detection framework","score":0.4473065733909607},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44563955068588257},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4238992929458618},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4215490221977234},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2624807357788086},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.18365007638931274},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.14097657799720764}],"concepts":[{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.8503129482269287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7808054685592651},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.775896430015564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7088426351547241},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6740670204162598},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.641545832157135},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.610323965549469},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.5088406205177307},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5057735443115234},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.5039958357810974},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.4473065733909607},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44563955068588257},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4238992929458618},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4215490221977234},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2624807357788086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.18365007638931274},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.14097657799720764},{"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/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/aim.2019.8868536","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aim.2019.8868536","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-02063181v2","is_oa":false,"landing_page_url":"https://hal.science/hal-02063181","pdf_url":null,"source":{"id":"https://openalex.org/S4406922454","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2019","raw_type":"Preprints, Working Papers, ..."}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1924569945","https://openalex.org/W2024676408","https://openalex.org/W2036439337","https://openalex.org/W2117228865","https://openalex.org/W2118877769","https://openalex.org/W2163605009","https://openalex.org/W2167340365","https://openalex.org/W2207670488","https://openalex.org/W2252355370","https://openalex.org/W2465948386","https://openalex.org/W2564095182","https://openalex.org/W2739423245","https://openalex.org/W2745859992","https://openalex.org/W2781064046","https://openalex.org/W2793066252","https://openalex.org/W2796347433","https://openalex.org/W2811184430","https://openalex.org/W2883702102","https://openalex.org/W2894976583","https://openalex.org/W2900757645","https://openalex.org/W2901136733","https://openalex.org/W2951614162","https://openalex.org/W2962694681","https://openalex.org/W2962970995","https://openalex.org/W2963037989","https://openalex.org/W2963162156","https://openalex.org/W2963288928","https://openalex.org/W2963416037","https://openalex.org/W2963912898","https://openalex.org/W2964327083","https://openalex.org/W3104218139","https://openalex.org/W4293584584","https://openalex.org/W4298299490","https://openalex.org/W6677548441","https://openalex.org/W6684191040","https://openalex.org/W6748766184","https://openalex.org/W6756486208","https://openalex.org/W6756579179"],"related_works":["https://openalex.org/W2979950214","https://openalex.org/W87609089","https://openalex.org/W3024737167","https://openalex.org/W2414561716","https://openalex.org/W3161199934","https://openalex.org/W2303855011","https://openalex.org/W2312326526","https://openalex.org/W2412578866","https://openalex.org/W3105866016","https://openalex.org/W4312703710"],"abstract_inverted_index":{"In":[0],"recent":[1,47],"years,":[2],"Convolutional":[3],"Neural":[4],"Networks":[5],"(CNNs)":[6],"have":[7],"repeatedly":[8],"shown":[9],"state-of-the-art":[10],"performance":[11],"for":[12,29,79,137],"their":[13,22,27],"accuracy":[14],"in":[15,106,121],"the":[16,33,44,62,73,80,107,112],"task":[17],"of":[18,56,75,82],"object":[19,84,143,148,163],"detection,":[20,144],"but":[21],"heavy":[23],"computational":[24],"costs":[25],"impede":[26],"ability":[28],"real-time":[30,83],"detection":[31,85,108],"when":[32,39,111],"supporting":[34],"system":[35,86,118,135],"is":[36,41,119],"moving,":[37],"particularly":[38],"it":[40,123],"accelerating.":[42],"At":[43],"same":[45],"time,":[46],"progress":[48],"on":[49,87],"visual":[50,99],"inertial":[51,76],"systems":[52],"takes":[53],"great":[54],"advantage":[55],"movement":[57],"information":[58],"to":[59,71,154,160],"robustly":[60],"estimate":[61],"robot":[63,113,139],"state":[64,140],"and":[65,102,129,142],"its":[66],"surrounding.":[67],"This":[68],"paper":[69],"proposes":[70],"exploit":[72],"advantages":[74],"odometry":[77,100],"research":[78],"purpose":[81],"mobile":[88],"robots.":[89],"We":[90],"combine":[91],"a":[92,97,161],"CNN":[93],"detector":[94],"with":[95],"VINS-Mono,":[96],"moving":[98],"system,":[101],"show":[103],"reliable":[104],"improvement":[105],"process,":[109],"especially":[110],"accelerates":[114],"or":[115,165],"decelerates.":[116],"Our":[117],"ready-to-use":[120],"that":[122],"has":[124],"very":[125],"low":[126],"deployment":[127],"cost":[128],"requires":[130],"no":[131],"calibration.":[132],"The":[133],"resulting":[134],"allows":[136],"simultaneous":[138],"estimation":[141],"as":[145,147],"well":[146],"tracking.":[149],"Lastly,":[150],"this":[151],"architecture":[152],"proves":[153],"be":[155],"flexible":[156],"because":[157],"not":[158],"restrained":[159],"specific":[162],"type":[164],"detector.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-29T08:15:47.926485","created_date":"2025-10-10T00:00:00"}