{"id":"https://openalex.org/W7134060706","doi":"https://doi.org/10.48550/arxiv.2603.04938","title":"Person Detection and Tracking from an Overhead Crane LiDAR","display_name":"Person Detection and Tracking from an Overhead Crane LiDAR","publication_year":2026,"publication_date":"2026-03-05","ids":{"openalex":"https://openalex.org/W7134060706","doi":"https://doi.org/10.48550/arxiv.2603.04938"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.04938","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066749549","display_name":"Nilusha Jayawickrama","orcid":"https://orcid.org/0000-0003-1188-5521"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jayawickrama, Nilusha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128234570","display_name":"Henrik Toikka","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Toikka, Henrik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5061093557","display_name":"Risto Ojala","orcid":"https://orcid.org/0000-0003-0865-1775"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ojala, Risto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.7932999730110168,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7932999730110168,"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":0.08110000193119049,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.014600000344216824,"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/lidar","display_name":"Lidar","score":0.7477999925613403},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7078999876976013},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5673999786376953},{"id":"https://openalex.org/keywords/workspace","display_name":"Workspace","score":0.5428000092506409},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.536899983882904},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.5047000050544739},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4860999882221222}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7477999925613403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7465999722480774},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7078999876976013},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5673999786376953},{"id":"https://openalex.org/C58581272","wikidata":"https://www.wikidata.org/wiki/Q12741163","display_name":"Workspace","level":3,"score":0.5428000092506409},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.536899983882904},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.5047000050544739},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4860999882221222},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.46320000290870667},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.42320001125335693},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39430001378059387},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34540000557899475},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.31360000371932983},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.3077999949455261},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.27140000462532043}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.04938","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.04938","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.04938","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:doi:10.48550/arxiv.2603.04938","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"person":[3,78,153],"detection":[4,154],"and":[5,33,54,64,74,125,149,155,171],"tracking":[6],"in":[7,140,173],"an":[8,17],"industrial":[9],"indoor":[10],"workspace":[11],"using":[12,72],"a":[13,24,44,61,112],"LiDAR":[14,31,47],"mounted":[15],"on":[16],"overhead":[18,21,46,150],"crane.":[19],"The":[20,99,136],"viewpoint":[22],"introduces":[23],"strong":[25],"domain":[26,143],"shift":[27],"from":[28],"common":[29],"vehicle-centric":[30],"benchmarks,":[32],"limited":[34],"availability":[35],"of":[36,95],"suitable":[37],"public":[38],"training":[39,63],"data.":[40],"Henceforth,":[41],"we":[42,167],"curate":[43],"site-specific":[45],"dataset":[48,170],"with":[49,86,123],"3D":[50,58],"human":[51],"bounding-box":[52],"annotations":[53],"adapt":[55],"selected":[56],"candidate":[57],"detectors":[59],"under":[60],"unified":[62],"evaluation":[65,88],"protocol.":[66],"We":[67,157],"further":[68,177],"integrate":[69],"lightweight":[70],"tracking-by-detection":[71],"AB3DMOT":[73],"SimpleTrack":[75],"to":[76,89,109,118,175],"maintain":[77],"identities":[79],"over":[80],"time.":[81],"Detection":[82],"performance":[83],"is":[84],"reported":[85],"distance-sliced":[87],"quantify":[90],"the":[91,96,129,142],"practical":[92,163],"operating":[93],"envelope":[94],"sensing":[97,151],"setup.":[98],"best":[100],"adapted":[101],"detector":[102],"configurations":[103],"achieve":[104],"average":[105],"precision":[106],"(AP)":[107],"up":[108],"0.84":[110],"within":[111],"5.0":[113],"m":[114],"horizontal":[115],"radius,":[116],"increasing":[117],"0.97":[119],"at":[120],"1.0":[121],"m,":[122],"VoxelNeXt":[124],"SECOND":[126],"emerging":[127],"as":[128],"most":[130],"reliable":[131],"backbones":[132],"across":[133],"this":[134],"range.":[135],"acquired":[137],"results":[138],"contribute":[139],"bridging":[141],"gap":[144],"between":[145],"standard":[146],"driving":[147],"datasets":[148],"for":[152],"tracking.":[156],"also":[158],"report":[159],"latency":[160],"measurements,":[161],"highlighting":[162],"real-time":[164],"feasibility.":[165],"Finally,":[166],"release":[168],"our":[169],"implementations":[172],"GitHub":[174],"support":[176],"research":[178]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-07T00:00:00"}
