{"id":"https://openalex.org/W2735701112","doi":"https://doi.org/10.1109/i2mtc.2017.7969691","title":"A superpixel-based codebook model for real time foreground detection","display_name":"A superpixel-based codebook model for real time foreground detection","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2735701112","doi":"https://doi.org/10.1109/i2mtc.2017.7969691","mag":"2735701112"},"language":"en","primary_location":{"id":"doi:10.1109/i2mtc.2017.7969691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2017.7969691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","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/A5019841300","display_name":"Shicai Fan","orcid":"https://orcid.org/0000-0003-2548-3689"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shicai Fan","raw_affiliation_strings":["School of Automation Engineering & Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation Engineering & Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058120145","display_name":"Xiangfeng Zeng","orcid":"https://orcid.org/0000-0003-1564-8494"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangfeng Zeng","raw_affiliation_strings":["School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0796,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.33861541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9983000159263611,"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/T11019","display_name":"Image Enhancement 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/codebook","display_name":"Codebook","score":0.9714183807373047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8086017966270447},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.7044463157653809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6850542426109314},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.5929287672042847},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5604690313339233},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5365488529205322},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5336438417434692},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5157235264778137},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4881168305873871},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.4621241092681885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.455980122089386},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41940993070602417}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9714183807373047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8086017966270447},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.7044463157653809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6850542426109314},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.5929287672042847},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5604690313339233},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5365488529205322},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5336438417434692},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5157235264778137},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4881168305873871},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.4621241092681885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.455980122089386},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41940993070602417},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/i2mtc.2017.7969691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/i2mtc.2017.7969691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1971715095","https://openalex.org/W1972168313","https://openalex.org/W2043003144","https://openalex.org/W2046356300","https://openalex.org/W2052524720","https://openalex.org/W2069057506","https://openalex.org/W2104125540","https://openalex.org/W2112157293","https://openalex.org/W2114701396","https://openalex.org/W2118246710","https://openalex.org/W2125096361","https://openalex.org/W2140235142","https://openalex.org/W2158604775","https://openalex.org/W2334409186","https://openalex.org/W2360282719","https://openalex.org/W2371883281","https://openalex.org/W2390036456","https://openalex.org/W3001229039","https://openalex.org/W3094885158"],"related_works":["https://openalex.org/W2096936443","https://openalex.org/W2081863301","https://openalex.org/W2352648934","https://openalex.org/W2365109233","https://openalex.org/W145510127","https://openalex.org/W2374856816","https://openalex.org/W1977098967","https://openalex.org/W2378932494","https://openalex.org/W2352292447","https://openalex.org/W2391875658"],"abstract_inverted_index":{"A":[0],"superpixel-based":[1,54],"codebook":[2,33,55],"model":[3,56],"was":[4],"presented":[5],"to":[6,24,100],"improve":[7,64],"the":[8,18,25,31,36,39,42,53,60,65,70,76,83,90],"efficiency":[9],"of":[10,27,38],"foreground":[11,71,95],"detection":[12,72],"in":[13,94],"this":[14],"paper.":[15],"By":[16],"clustering":[17],"neighboring":[19],"pixels":[20],"into":[21],"superpixels":[22],"according":[23],"similarities":[26],"brightness":[28],"and":[29,41,63],"texture,":[30],"proposed":[32],"could":[34,57,88],"reduce":[35,59],"redundancy":[37],"codewords":[40],"postprocessing":[43],"complexity.":[44],"Simulation":[45],"results":[46],"on":[47,75,82],"some":[48],"benchmark":[49],"videos":[50],"indicate":[51],"that,":[52],"significantly":[58],"memory":[61],"consumption":[62],"processing":[66,79],"speed":[67],"without":[68],"sacrificing":[69],"precision.":[73],"Applied":[74],"embedded":[77],"video":[78],"systems":[80],"based":[81],"DM6437":[84],"processor,":[85],"our":[86],"algorithm":[87],"satisfy":[89],"real":[91,101],"time":[92],"requirement":[93],"detection,":[96],"which":[97],"is":[98],"straightforward":[99],"world":[102],"application.":[103]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}