{"id":"https://openalex.org/W2791606523","doi":"https://doi.org/10.1109/icip.2017.8296537","title":"Propagation based saliency detection for infrared pedestrian images","display_name":"Propagation based saliency detection for infrared pedestrian images","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2791606523","doi":"https://doi.org/10.1109/icip.2017.8296537","mag":"2791606523"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5101819994","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0002-8464-7797"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016025633","display_name":"Fugen Zhou","orcid":"https://orcid.org/0000-0002-9933-7388"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fugen Zhou","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386343","display_name":"Lu Li","orcid":"https://orcid.org/0000-0003-0465-2340"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Li","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043001105","display_name":"Xiangzhi Bai","orcid":"https://orcid.org/0000-0002-6115-8237"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangzhi Bai","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101819994"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51094297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"73?80","issue":null,"first_page":"1527","last_page":"1531"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9902999997138977,"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/pedestrian-detection","display_name":"Pedestrian detection","score":0.8130952715873718},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.783722996711731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7624750137329102},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7260538339614868},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7111367583274841},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.705628514289856},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.6077561378479004},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.5793318152427673},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5749355554580688},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5585960149765015},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5005395412445068},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4372912049293518},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.43045946955680847},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3378601372241974},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09012004733085632},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08586129546165466},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0656188428401947},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.05959683656692505}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.8130952715873718},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.783722996711731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7624750137329102},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7260538339614868},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7111367583274841},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.705628514289856},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.6077561378479004},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.5793318152427673},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5749355554580688},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5585960149765015},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5005395412445068},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4372912049293518},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.43045946955680847},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3378601372241974},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09012004733085632},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08586129546165466},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0656188428401947},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.05959683656692505},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"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/icip.2017.8296537","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.75,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W21025885","https://openalex.org/W1581590495","https://openalex.org/W1897243830","https://openalex.org/W1903001680","https://openalex.org/W1982075130","https://openalex.org/W1984452441","https://openalex.org/W2002781701","https://openalex.org/W2024713411","https://openalex.org/W2039313011","https://openalex.org/W2041719651","https://openalex.org/W2047670868","https://openalex.org/W2059753722","https://openalex.org/W2064365034","https://openalex.org/W2068909160","https://openalex.org/W2085324960","https://openalex.org/W2100470808","https://openalex.org/W2105666116","https://openalex.org/W2107363596","https://openalex.org/W2118246710","https://openalex.org/W2119823327","https://openalex.org/W2120807798","https://openalex.org/W2125647562","https://openalex.org/W2155661370","https://openalex.org/W2166650627","https://openalex.org/W2211996548","https://openalex.org/W2282640221","https://openalex.org/W4239147634","https://openalex.org/W6600850345","https://openalex.org/W6639624585"],"related_works":["https://openalex.org/W1990245967","https://openalex.org/W2054177013","https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W4383506493","https://openalex.org/W1994772959","https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W17460865","https://openalex.org/W2372578044"],"abstract_inverted_index":{"Saliency":[0],"detection":[1,24],"is":[2,9,30,48,56,68],"popular":[3],"in":[4],"image":[5],"processing,":[6],"but":[7],"it":[8],"still":[10],"a":[11],"challenging":[12],"problem":[13],"for":[14,26,87],"infrared":[15,27,88],"pedestrian":[16,28,89],"images.":[17,90],"In":[18],"this":[19],"paper,":[20],"an":[21,59],"effective":[22],"saliency":[23,65,85],"method":[25,67,86],"images":[29],"proposed.":[31],"Taking":[32],"into":[33],"consideration":[34],"the":[35,43,74,80,83],"characteristics":[36],"of":[37,82],"pedestrians":[38],"including":[39],"luminance":[40],"and":[41,61,72],"shape,":[42],"MSER-based":[44],"local":[45],"stableness":[46],"(MLS)":[47],"firstly":[49],"introduced.":[50],"Then":[51],"vertical":[52],"edge-weighted":[53],"contrast":[54],"(VEC)":[55],"calculated.":[57],"Finally,":[58],"intra-scale":[60],"inter-scale":[62],"neighborhood":[63],"based":[64],"propagation":[66],"constructed":[69],"to":[70],"optimize":[71],"integrate":[73],"two":[75],"features.":[76],"Extensive":[77],"experiments":[78],"demonstrate":[79],"effectiveness":[81],"proposed":[84]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}