{"id":"https://openalex.org/W2181448325","doi":"https://doi.org/10.1109/ipin.2015.7346945","title":"Activity recognition on handheld devices for pedestrian indoor navigation","display_name":"Activity recognition on handheld devices for pedestrian indoor navigation","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2181448325","doi":"https://doi.org/10.1109/ipin.2015.7346945","mag":"2181448325"},"language":"en","primary_location":{"id":"doi:10.1109/ipin.2015.7346945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipin.2015.7346945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN)","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/A5060315568","display_name":"Dmytro Bobkov","orcid":"https://orcid.org/0000-0002-5096-8891"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Dmytro Bobkov","raw_affiliation_strings":["Chair of Media Technology, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Media Technology, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037033673","display_name":"Ferdinand Grimm","orcid":"https://orcid.org/0000-0003-2804-4497"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ferdinand Grimm","raw_affiliation_strings":["Chair of Media Technology, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Media Technology, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077346002","display_name":"Eckehard Steinbach","orcid":"https://orcid.org/0000-0001-8853-2703"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Eckehard Steinbach","raw_affiliation_strings":["Chair of Media Technology, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Media Technology, Technische Universit\u00e4t M\u00fcnchen, Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048573629","display_name":"Sebastian Hilsenbeck","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sebastian Hilsenbeck","raw_affiliation_strings":["NavVis GmbH, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"NavVis GmbH, Munich, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014130848","display_name":"Georg Schroth","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Georg Schroth","raw_affiliation_strings":["NavVis GmbH, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"NavVis GmbH, Munich, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5060315568"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":1.1837,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81835257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9984999895095825,"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":0.996999979019165,"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/computer-science","display_name":"Computer science","score":0.8019664287567139},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7852239608764648},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.6827528476715088},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6145225167274475},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.5783511996269226},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5727379322052002},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5360171794891357},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5090934634208679},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4992842674255371},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.4708143174648285},{"id":"https://openalex.org/keywords/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.4369674026966095},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.41427043080329895},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3987594246864319},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38552939891815186},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.33594247698783875},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10088276863098145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8019664287567139},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7852239608764648},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.6827528476715088},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6145225167274475},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.5783511996269226},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5727379322052002},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5360171794891357},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5090934634208679},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4992842674255371},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4708143174648285},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.4369674026966095},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.41427043080329895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3987594246864319},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38552939891815186},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33594247698783875},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10088276863098145},{"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/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipin.2015.7346945","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipin.2015.7346945","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Indoor Positioning and Indoor Navigation (IPIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W23092218","https://openalex.org/W98188630","https://openalex.org/W572626464","https://openalex.org/W1503398984","https://openalex.org/W1505211736","https://openalex.org/W1570713908","https://openalex.org/W1575902124","https://openalex.org/W1606770439","https://openalex.org/W1649444134","https://openalex.org/W1896930264","https://openalex.org/W1970099751","https://openalex.org/W1976552421","https://openalex.org/W1991898702","https://openalex.org/W2002182716","https://openalex.org/W2009964772","https://openalex.org/W2017634428","https://openalex.org/W2038791641","https://openalex.org/W2054780155","https://openalex.org/W2060663350","https://openalex.org/W2062956715","https://openalex.org/W2071385528","https://openalex.org/W2084490355","https://openalex.org/W2090766960","https://openalex.org/W2094523840","https://openalex.org/W2105006037","https://openalex.org/W2105046342","https://openalex.org/W2108950108","https://openalex.org/W2109507061","https://openalex.org/W2110575115","https://openalex.org/W2121232806","https://openalex.org/W2124833832","https://openalex.org/W2125838338","https://openalex.org/W2135579862","https://openalex.org/W2158479011","https://openalex.org/W2207642662","https://openalex.org/W2338710621","https://openalex.org/W2949770959","https://openalex.org/W4297710664","https://openalex.org/W6600926226","https://openalex.org/W6604091132","https://openalex.org/W6636227860"],"related_works":["https://openalex.org/W2017210410","https://openalex.org/W1993009522","https://openalex.org/W1995792634","https://openalex.org/W3128072696","https://openalex.org/W103069296","https://openalex.org/W2135672910","https://openalex.org/W2405411278","https://openalex.org/W2578973671","https://openalex.org/W2215058820","https://openalex.org/W2945000716"],"abstract_inverted_index":{"We":[0],"propose":[1],"an":[2],"inertial":[3],"sensor-based":[4],"approach":[5],"to":[6,37,97,178],"activity":[7],"recognition":[8],"for":[9,169],"pedestrian":[10],"indoor":[11],"navigation.":[12],"In":[13,94,117],"the":[14,28,34,48,52,80,118,122,134,137],"considered":[15],"scenario":[16],"a":[17,23,60,73,147,164,174],"mobile":[18,92],"device":[19],"is":[20],"held":[21],"in":[22,25,39],"hand":[24],"front":[26],"of":[27,68,79,136,159,167],"user.":[29],"The":[30,157],"recognized":[31],"activities":[32,57],"are":[33],"ones":[35],"relevant":[36],"positioning":[38],"multi-floor":[40],"buildings:":[41],"walking":[42],"and":[43,89,102,113,127],"going":[44],"up":[45],"or":[46],"down":[47],"stairs.":[49],"To":[50],"model":[51],"time":[53],"dependency":[54],"between":[55,124],"consecutive":[56],"we":[58,71,83,100,120,131],"employ":[59],"Hidden":[61],"Markov":[62],"Model":[63],"(HMM).":[64],"For":[65,77],"efficient":[66],"quantization":[67],"continuous":[69],"features,":[70],"apply":[72],"random":[74],"forest":[75],"classifier.":[76],"verification":[78],"proposed":[81,161],"algorithm,":[82],"conducted":[84],"experiments":[85,119],"with":[86,146,151],"12":[87],"participants":[88],"4":[90],"different":[91],"devices.":[93],"our":[95,160],"comparison":[96],"state-of-the-art":[98,179],"approaches,":[99],"implement":[101],"evaluate":[103],"major":[104],"classification":[105,128,155,165],"algorithms,":[106],"such":[107],"as":[108],"nearest":[109],"neighbour,":[110],"decision":[111],"tree":[112],"dynamic":[114,148],"Bayesian":[115,149],"Network.":[116],"show":[121],"trade-off":[123],"computational":[125],"complexity":[126,135],"performance.":[129,156],"Furthermore,":[130],"demonstrate":[132],"that":[133],"HMM":[138],"can":[139],"be":[140],"significantly":[141],"reduced":[142],"by":[143],"replacing":[144],"it":[145],"network":[150],"negligible":[152],"impact":[153],"on":[154],"best":[158],"classifier":[162],"achieves":[163],"accuracy":[166],"91%":[168],"new":[170],"users,":[171],"which":[172],"offers":[173],"30%":[175],"improvement":[176],"compared":[177],"approaches.":[180]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
