{"id":"https://openalex.org/W4386919807","doi":"https://doi.org/10.1109/sas58821.2023.10254180","title":"Pipeline for Automation of LiDAR Data Annotation","display_name":"Pipeline for Automation of LiDAR Data Annotation","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4386919807","doi":"https://doi.org/10.1109/sas58821.2023.10254180"},"language":"en","primary_location":{"id":"doi:10.1109/sas58821.2023.10254180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sas58821.2023.10254180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Sensors Applications Symposium (SAS)","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/A5003822824","display_name":"Bhaskar Anand","orcid":"https://orcid.org/0000-0002-2035-9446"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bhaskar Anand","raw_affiliation_strings":["Indian Institute of Technology Hyderabad,Department of Electrical Engineering,Hyderabad,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Hyderabad,Department of Electrical Engineering,Hyderabad,India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069669674","display_name":"P. Rajalakshmi","orcid":"https://orcid.org/0000-0002-7252-6728"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajalakshmi P","raw_affiliation_strings":["Indian Institute of Technology Hyderabad,Department of Electrical Engineering,Hyderabad,India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Hyderabad,Department of Electrical Engineering,Hyderabad,India","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5003822824"],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":0.2514,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51187828,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9889000058174133,"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":0.9878000020980835,"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/annotation","display_name":"Annotation","score":0.7718627452850342},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7631645202636719},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.7367673516273499},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.7121162414550781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.663662314414978},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3017951250076294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2626223564147949},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19106987118721008},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15896859765052795},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12284809350967407},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.057646751403808594}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.7718627452850342},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7631645202636719},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.7367673516273499},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.7121162414550781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.663662314414978},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3017951250076294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2626223564147949},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19106987118721008},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15896859765052795},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12284809350967407},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.057646751403808594}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sas58821.2023.10254180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sas58821.2023.10254180","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Sensors Applications Symposium (SAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320325255","display_name":"Ministry of Electronics and Information technology","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2953913750","https://openalex.org/W2963121255","https://openalex.org/W2963292632","https://openalex.org/W2964216646","https://openalex.org/W2965376383","https://openalex.org/W2968296999","https://openalex.org/W2979375228","https://openalex.org/W2991375205","https://openalex.org/W3004066040","https://openalex.org/W3101378328","https://openalex.org/W3203344299","https://openalex.org/W3209102426","https://openalex.org/W6739778489","https://openalex.org/W6750365713"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W2351984678","https://openalex.org/W2140032575","https://openalex.org/W2011860471","https://openalex.org/W2012196540","https://openalex.org/W3011451421"],"abstract_inverted_index":{"Light":[0],"Detection":[1],"and":[2,111,173,179],"Ranging":[3],"(LiDAR)":[4],"sensor":[5],"plays":[6],"a":[7,70,86],"vital":[8],"role":[9],"in":[10,131],"the":[11,23,44,49,57,104,127,136],"area":[12],"of":[13,22,32,138,177],"autonomous":[14],"vehicles.":[15],"LiDAR":[16,40,54,59,64,92,105,132,146],"not":[17],"only":[18],"provides":[19,27,118],"depth":[20],"information":[21],"object":[24,33,55,113],"but":[25],"also":[26],"three-dimensional":[28],"geometry.":[29],"The":[30,97,115,161],"task":[31,67],"detection":[34],"can":[35],"be":[36,62,184],"directly":[37],"performed":[38],"on":[39,101],"data,":[41,172],"thus":[42],"complementing":[43],"camera.":[45],"However,":[46],"to":[47,120,154,157,183],"train":[48],"deep":[50],"learning":[51],"models":[52],"for":[53,108,141],"detection,":[56],"acquired":[58,143],"data":[60,65,93,133,142,156],"must":[61],"annotated.":[63,186],"annotation":[66,134,139],"includes":[68],"creating":[69],"cuboid-shaped":[71],"bounding":[72],"box":[73],"around":[74],"objects":[75],"like":[76],"cars,":[77],"trucks,":[78],"pedestrians,":[79],"etc.":[80],"In":[81],"this":[82,159],"paper,":[83],"we":[84],"present":[85],"generic":[87],"automation":[88,123],"pipeline":[89,98,117,162],"that":[90],"eases":[91],"annotation's":[94],"tedious":[95],"task.":[96],"was":[99,163],"implemented":[100],"MATLAB":[102],"using":[103],"Labeler":[106],"application":[107],"Car,":[109],"Truck,":[110],"Pedestrian":[112],"classes.":[114],"proposed":[116],"flexibility":[119],"add":[121],"more":[122,174],"labels":[124],"as":[125],"per":[126],"requirement.":[128],"Another":[129],"challenge":[130],"is":[135],"non-adaptability":[137],"tools":[140],"from":[144,170],"other":[145],"sensors.":[147],"A":[148],"preprocessing":[149],"step":[150],"has":[151],"been":[152],"applied":[153],"raw":[155],"address":[158],"problem.":[160],"tested":[164],"by":[165],"annotating":[166],"50":[167],"point":[168],"clouds":[169],"Pandaset":[171],"than":[175],"80%":[176],"Cars":[178],"Trucks":[180],"were":[181],"found":[182],"correctly":[185]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}