{"id":"https://openalex.org/W2127494692","doi":"https://doi.org/10.1109/ivs.2013.6629530","title":"From stixels to objects — A conditional random field based approach","display_name":"From stixels to objects — A conditional random field based approach","publication_year":2013,"publication_date":"2013-06-01","ids":{"openalex":"https://openalex.org/W2127494692","doi":"https://doi.org/10.1109/ivs.2013.6629530","mag":"2127494692"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2013.6629530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2013.6629530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5005457699","display_name":"Friedrich Erbs","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friedrich Erbs","raw_affiliation_strings":["Daimler AG, Boeblingen, Germany","Image Understanding, Daimler AG, Boeblingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Boeblingen, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"Image Understanding, Daimler AG, Boeblingen, Germany","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048742004","display_name":"Beate Schwarz","orcid":"https://orcid.org/0000-0002-3230-1153"},"institutions":[{"id":"https://openalex.org/I31582689","display_name":"Stuttgart Technical University of Applied Sciences","ror":"https://ror.org/039gdg280","country_code":"DE","type":"education","lineage":["https://openalex.org/I31582689"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Beate Schwarz","raw_affiliation_strings":["Department of Mathematics, HFT Stuttgart, Stuttgart, Germany","Dept. of Math., HFT Stuttgart, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, HFT Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I31582689"]},{"raw_affiliation_string":"Dept. of Math., HFT Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I31582689"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109566845","display_name":"Uwe Franke","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Uwe Franke","raw_affiliation_strings":["Daimler AG, Boeblingen, Germany","Image Understanding, Daimler AG, Boeblingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Daimler AG, Boeblingen, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"Image Understanding, Daimler AG, Boeblingen, Germany","institution_ids":["https://openalex.org/I891521709"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"586","last_page":"591"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10036","display_name":"Advanced Neural Network Applications","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":0.9980999827384949,"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/conditional-random-field","display_name":"Conditional random field","score":0.7704089283943176},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7369544506072998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6467112302780151},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6186593770980835},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6016979813575745},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5370982885360718},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.454396516084671},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4499800503253937},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4236701726913452},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.41782858967781067},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3730575442314148},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.30218732357025146},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.17299777269363403}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7704089283943176},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7369544506072998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6467112302780151},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6186593770980835},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6016979813575745},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5370982885360718},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.454396516084671},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4499800503253937},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4236701726913452},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.41782858967781067},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3730575442314148},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.30218732357025146},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.17299777269363403},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2013.6629530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2013.6629530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1554984376","https://openalex.org/W1557515246","https://openalex.org/W1610707153","https://openalex.org/W1879762224","https://openalex.org/W1913356549","https://openalex.org/W1971410590","https://openalex.org/W1973536668","https://openalex.org/W1983989471","https://openalex.org/W1999305212","https://openalex.org/W2003844821","https://openalex.org/W2019329118","https://openalex.org/W2025991977","https://openalex.org/W2026197844","https://openalex.org/W2034430035","https://openalex.org/W2047166686","https://openalex.org/W2049633694","https://openalex.org/W2101309634","https://openalex.org/W2121141217","https://openalex.org/W2123969523","https://openalex.org/W2147880316","https://openalex.org/W2148852318","https://openalex.org/W2151095208","https://openalex.org/W2164556573","https://openalex.org/W2165114467","https://openalex.org/W2171650716","https://openalex.org/W2807981689","https://openalex.org/W3184458996","https://openalex.org/W4244914727","https://openalex.org/W6650328104","https://openalex.org/W7048738093"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W2093471820","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2347460059","https://openalex.org/W2111726165","https://openalex.org/W1984858032","https://openalex.org/W2616891703","https://openalex.org/W2965594636"],"abstract_inverted_index":{"Detection":[0],"and":[1,29,34,60,71,110,143,150],"tracking":[2],"of":[3,63,68,74,93,139,152],"moving":[4,69],"traffic":[5,26,162],"participants":[6],"like":[7],"vehicles,":[8],"pedestrians":[9],"or":[10],"bicycles":[11],"from":[12],"a":[13,17,22,43,80,120],"mobile":[14],"platform":[15],"using":[16],"stereo":[18],"camera":[19],"system":[20],"plays":[21],"key":[23],"role":[24],"in":[25,89,119,159],"scene":[27],"understanding":[28],"for":[30],"future":[31],"driver":[32],"assistance":[33],"safety":[35],"systems.":[36],"To":[37],"this":[38,40,106],"end,":[39],"work":[41],"presents":[42],"Bayesian":[44],"segmentation":[45],"approach":[46,107,155],"based":[47],"on":[48],"the":[49,72,94,137,153],"Dynamic":[50],"Stixel":[51],"World,":[52],"an":[53,64,132],"efficient":[54],"super-pixel":[55],"object":[56],"representation.":[57],"The":[58,148],"existence":[59],"state":[61],"estimation":[62],"(initially)":[65],"unknown":[66],"number":[67],"objects":[70],"detection":[73],"stationary":[75],"background":[76],"is":[77,156],"formulated":[78],"as":[79,113,115],"time-recursive":[81],"energy":[82],"minimization":[83],"problem":[84],"that":[85],"can":[86],"be":[87],"solved":[88],"real-time":[90],"by":[91],"means":[92],"alpha-expansion":[95],"multi-class":[96],"graph":[97],"cut":[98],"optimization":[99],"scheme.":[100],"In":[101],"order":[102],"to":[103],"handle":[104],"noise,":[105],"integrates":[108],"3D":[109],"motion":[111],"features":[112],"well":[114],"spatio-temporal":[116],"prior":[117],"knowledge":[118],"probabilistic":[121],"conditional":[122],"random":[123],"field":[124],"(CRF)":[125],"framework.":[126],"An":[127],"optional":[128],"fusion":[129],"step":[130],"with":[131],"additional":[133],"radar":[134],"sensor":[135],"combines":[136],"advantages":[138],"both":[140],"measuring":[141],"instruments":[142],"yields":[144],"superior":[145],"overall":[146],"results.":[147],"performance":[149],"robustness":[151],"presented":[154],"evaluated":[157],"quantitatively":[158],"various":[160],"challenging":[161],"scenes.":[163]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}