{"id":"https://openalex.org/W1979170624","doi":"https://doi.org/10.1145/2811411.2811511","title":"Pyramidal channel features for pedestrian detector","display_name":"Pyramidal channel features for pedestrian detector","publication_year":2015,"publication_date":"2015-10-09","ids":{"openalex":"https://openalex.org/W1979170624","doi":"https://doi.org/10.1145/2811411.2811511","mag":"1979170624"},"language":"en","primary_location":{"id":"doi:10.1145/2811411.2811511","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2811411.2811511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on research in adaptive and convergent systems","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/A5100989543","display_name":"Young Chul Lim","orcid":"https://orcid.org/0009-0003-5229-360X"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Young Chul Lim","raw_affiliation_strings":["Daegu Gyeongbuk Institute of Science &amp; Technology, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Daegu Gyeongbuk Institute of Science &amp; Technology, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103203864","display_name":"Min-Sung Kang","orcid":"https://orcid.org/0000-0002-8459-5843"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minsung Kang","raw_affiliation_strings":["Daegu Gyeongbuk Institute of Science &amp; Technology, Daegu, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Daegu Gyeongbuk Institute of Science &amp; Technology, Daegu, Republic of Korea","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100989543"],"corresponding_institution_ids":["https://openalex.org/I193352282"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56736793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"195","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9972000122070312,"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":0.9205614924430847},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.8425348997116089},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.8038114905357361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7207066416740417},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6621423959732056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.613186776638031},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5695744752883911},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5285460352897644},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5085378885269165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5033292174339294},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.44405099749565125},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.428104043006897},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24122920632362366},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13041359186172485},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12805280089378357},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.113170325756073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09939983487129211}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.9205614924430847},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.8425348997116089},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8038114905357361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207066416740417},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6621423959732056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.613186776638031},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5695744752883911},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5285460352897644},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5085378885269165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5033292174339294},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.44405099749565125},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.428104043006897},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24122920632362366},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13041359186172485},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12805280089378357},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.113170325756073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09939983487129211},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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:10.1145/2811411.2811511","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2811411.2811511","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Conference on research in adaptive and convergent systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1906375339","https://openalex.org/W1999853363","https://openalex.org/W2031454541","https://openalex.org/W2034779469","https://openalex.org/W2081021369","https://openalex.org/W2125556102","https://openalex.org/W2159386181","https://openalex.org/W2161969291","https://openalex.org/W2548197316","https://openalex.org/W2949847849","https://openalex.org/W3097096317","https://openalex.org/W6600577311","https://openalex.org/W6650282857"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W1977648593","https://openalex.org/W2348780717","https://openalex.org/W2780165746","https://openalex.org/W2602033589","https://openalex.org/W4235475963","https://openalex.org/W4252030899","https://openalex.org/W2071599417","https://openalex.org/W2069019032"],"abstract_inverted_index":{"Most":[0],"state-of-the-art":[1,68],"pedestrian":[2,30,39],"detectors":[3],"diversify":[4],"features":[5,47],"to":[6],"improve":[7],"the":[8,14,18,29,59],"detection":[9,31,40],"performance.":[10,32],"Among":[11],"such":[12],"features,":[13],"gradient":[15,73],"histogram":[16],"is":[17],"most":[19],"informative.":[20],"This":[21],"work":[22],"investigates":[23],"how":[24],"diverse":[25],"orientation":[26],"information":[27],"influences":[28],"In":[33],"this":[34],"paper,":[35],"we":[36],"propose":[37],"a":[38,52],"method":[41,65],"which":[42,48],"uses":[43],"pyramidal":[44],"aggregated":[45],"channel":[46],"are":[49],"generated":[50],"with":[51],"layer-by-layer":[53],"assembly":[54],"scheme.":[55],"Experimental":[56],"results":[57],"on":[58],"INRIA":[60],"dataset":[61],"show":[62],"that":[63],"our":[64],"can":[66],"reach":[67],"performance":[69],"despite":[70],"using":[71],"only":[72],"features.":[74]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
