{"id":"https://openalex.org/W2903110595","doi":"https://doi.org/10.1109/icpr.2018.8545622","title":"Learning Training Samples for Occlusion Edge Detection and Its Application in Depth Ordering Inference","display_name":"Learning Training Samples for Occlusion Edge Detection and Its Application in Depth Ordering Inference","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2903110595","doi":"https://doi.org/10.1109/icpr.2018.8545622","mag":"2903110595"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2018.8545622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","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/A5019452689","display_name":"Yu Zhou","orcid":"https://orcid.org/0000-0002-6674-6484"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Zhou","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062956294","display_name":"Jianxiang Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxiang Ma","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082092902","display_name":"Anlong Ming","orcid":"https://orcid.org/0000-0003-2952-7757"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anlong Ming","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039363991","display_name":"Xiang Bai","orcid":"https://orcid.org/0000-0002-3449-5940"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Bai","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019452689"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.7312,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77320378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"541","last_page":"546"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9975000023841858,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9975000023841858,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9972000122070312,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9970999956130981,"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/discriminative-model","display_name":"Discriminative model","score":0.8200204372406006},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.7246906757354736},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.684701681137085},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.607439398765564},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5643538236618042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.560804009437561},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5014541149139404},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.45642656087875366},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4266320765018463},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.425041139125824},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3289351761341095},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2623007893562317},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.1832486391067505},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14964893460273743}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8200204372406006},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.7246906757354736},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.684701681137085},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.607439398765564},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5643538236618042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.560804009437561},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5014541149139404},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.45642656087875366},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4266320765018463},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.425041139125824},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3289351761341095},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2623007893562317},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.1832486391067505},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14964893460273743},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2018.8545622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2018.8545622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 24th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1486988219","https://openalex.org/W1502212970","https://openalex.org/W1976047850","https://openalex.org/W1997453445","https://openalex.org/W2005020305","https://openalex.org/W2037495825","https://openalex.org/W2046033161","https://openalex.org/W2058044859","https://openalex.org/W2066521378","https://openalex.org/W2080920426","https://openalex.org/W2110158442","https://openalex.org/W2113606819","https://openalex.org/W2129812935","https://openalex.org/W2146352414","https://openalex.org/W2151996626","https://openalex.org/W2157652882","https://openalex.org/W2162349892","https://openalex.org/W2264350531","https://openalex.org/W2296492035","https://openalex.org/W2303791627","https://openalex.org/W2536208356","https://openalex.org/W6605121731","https://openalex.org/W6629039392","https://openalex.org/W6630053423","https://openalex.org/W6665017643","https://openalex.org/W6676903177"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2110523656","https://openalex.org/W1964408341"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,14,29,33,53,73,84,92,97,106,124,129,135,141],"problem":[4],"of":[5,17,35,108,137],"occlusion":[6,36,99],"edge":[7,37],"detection,":[8],"which":[9],"is":[10,26,39,61,77],"applied":[11],"to":[12,63],"infer":[13],"depth":[15,112],"order":[16,113],"objects":[18],"in":[19,47],"a":[20,48,65,80],"monocular":[21],"image.":[22],"The":[23,88],"key":[24],"observation":[25],"that,":[27],"given":[28],"fixed":[30],"regression":[31,60],"objective,":[32],"accuracy":[34],"detection":[38],"effectively":[40],"boosted":[41],"by":[42],"selecting":[43],"appropriate":[44],"training":[45,74],"samples":[46],"discriminative":[49,69],"feature":[50,70],"subspace.":[51],"Specifically,":[52],"\u2113":[54],"<sub":[55],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[56],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[57],"-regularized":[58],"logistic":[59],"employed":[62],"learn":[64],"more":[66],"sparse":[67],"yet":[68],"subspace,":[71],"while":[72],"sample":[75],"selection":[76],"formulated":[78],"as":[79],"quadratic":[81],"optimization":[82],"with":[83],"robust":[85],"Huber":[86],"loss.":[87],"presented":[89],"formulation":[90],"avoids":[91],"noises":[93],"efficiently,":[94],"and":[95,128],"hence":[96],"desirable":[98],"edges":[100],"can":[101],"be":[102],"detected.":[103],"We":[104],"validate":[105],"effectiveness":[107],"our":[109,138],"approach":[110,139],"on":[111,119],"inference":[114],"problem.":[115],"Experiments":[116],"are":[117],"conducted":[118],"two":[120],"famous":[121],"datasets,":[122],"i.e.,":[123],"Cornell":[125],"depth-order":[126],"dataset":[127],"NYU2":[130],"dataset.":[131],"Promising":[132],"results":[133],"demonstrate":[134],"superiority":[136],"over":[140],"state-of-the-art":[142],"approaches.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
