{"id":"https://openalex.org/W2050528399","doi":"https://doi.org/10.1109/icmew.2014.6890530","title":"Integrating Bayesian Classifier into Random Walk optimizer for interactive image segmentation on mobile phones","display_name":"Integrating Bayesian Classifier into Random Walk optimizer for interactive image segmentation on mobile phones","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2050528399","doi":"https://doi.org/10.1109/icmew.2014.6890530","mag":"2050528399"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2014.6890530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2014.6890530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","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/A5101728035","display_name":"Yan Gao","orcid":"https://orcid.org/0000-0002-2719-6299"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Gao","raw_affiliation_strings":["Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology Beijing Institute of Technology, Beijing, China","Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085061478","display_name":"Xiabi Liu","orcid":"https://orcid.org/0000-0003-1633-0648"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiabi Liu","raw_affiliation_strings":["Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology Beijing Institute of Technology, Beijing, China","Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Lab of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976999759674072,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9973999857902527,"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/computer-science","display_name":"Computer science","score":0.7957799434661865},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6689902544021606},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6643854975700378},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6584670543670654},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.5581917762756348},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.556248664855957},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5485060214996338},{"id":"https://openalex.org/keywords/mobile-phone","display_name":"Mobile phone","score":0.5190601944923401},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5069959163665771},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.4654463231563568},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3960200548171997},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24299505352973938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7957799434661865},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6689902544021606},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6643854975700378},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6584670543670654},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.5581917762756348},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.556248664855957},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5485060214996338},{"id":"https://openalex.org/C2777421447","wikidata":"https://www.wikidata.org/wiki/Q17517","display_name":"Mobile phone","level":2,"score":0.5190601944923401},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5069959163665771},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.4654463231563568},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3960200548171997},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24299505352973938},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmew.2014.6890530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2014.6890530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.46000000834465027}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334924","display_name":"Program for New Century Excellent Talents in University","ror":"https://ror.org/01mv9t934"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1785730614","https://openalex.org/W1974235253","https://openalex.org/W2011800695","https://openalex.org/W2034110104","https://openalex.org/W2036709663","https://openalex.org/W2049633694","https://openalex.org/W2052575788","https://openalex.org/W2071598318","https://openalex.org/W2083277843","https://openalex.org/W2093164524","https://openalex.org/W2104095591","https://openalex.org/W2113201962","https://openalex.org/W2117081927","https://openalex.org/W2121189958","https://openalex.org/W2124351162","https://openalex.org/W2125637308","https://openalex.org/W2163360863","https://openalex.org/W2167064216","https://openalex.org/W2169551590","https://openalex.org/W2294819727","https://openalex.org/W2798247327","https://openalex.org/W2998023265","https://openalex.org/W3129711340","https://openalex.org/W3211330693","https://openalex.org/W6638212498","https://openalex.org/W6684913354","https://openalex.org/W6772576394"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W2055202857","https://openalex.org/W4205800335","https://openalex.org/W2371519352","https://openalex.org/W2386644571","https://openalex.org/W2372421320","https://openalex.org/W2901890255"],"abstract_inverted_index":{"With":[0],"rapid":[1],"development":[2],"of":[3,64,143,151],"mobile":[4,10,36,140,178],"technology":[5],"and":[6,27,82,111,149,166],"digital":[7],"image":[8,13,32,66,93],"processing,":[9],"applications":[11],"involving":[12],"segmentation":[14,33,109,133],"are":[15,75],"emerging":[16],"in":[17,87],"many":[18],"fields.":[19],"In":[20,103],"this":[21,104],"paper,":[22],"we":[23,106],"propose":[24],"an":[25,138],"effective":[26],"easy-to-use":[28],"algorithm":[29,154],"for":[30,59,92,101],"interactive":[31],"(IIS)":[34],"on":[35,176],"phones":[37],"through":[38],"integrating":[39],"a":[40,56,123,177],"Bayesian":[41,57],"Classifier":[42],"into":[43],"the":[44,50,61,65,79,84,88,108,113,126,131,152,158,163,167,173],"Random":[45],"Walk":[46],"optimizer.":[47],"We":[48,135],"exploit":[49],"user":[51,114,117],"input":[52],"information":[53],"to":[54,69,77,121,129],"train":[55],"classifier":[58],"determining":[60],"posterior":[62],"probabilities":[63,74],"pixels":[67,86],"belonging":[68],"foreground":[70],"or":[71],"background.":[72],"These":[73],"used":[76],"calculate":[78],"edge":[80],"weights":[81],"label":[83],"seed":[85],"random":[89],"walk":[90],"optimizer":[91],"segmentation.":[94],"The":[95,116,147],"resultant":[96],"method":[97],"is":[98,118,155],"called":[99],"BCRW":[100,145],"short.":[102],"way":[105],"improve":[107],"accuracy":[110],"alleviate":[112],"burden.":[115],"only":[119],"required":[120],"draw":[122],"rectangle":[124],"bounding":[125],"interested":[127],"object":[128],"get":[130],"high-quality":[132],"result.":[134],"further":[136],"design":[137],"efficient":[139],"phone":[141],"version":[142],"our":[144],"algorithm.":[146],"effectiveness":[148],"efficiency":[150],"proposed":[153],"confirmed":[156],"by":[157],"comparative":[159],"experimental":[160,174],"results":[161,175],"with":[162],"Grab":[164],"Cut":[165],"PIBS":[168],"algorithms,":[169],"as":[170,172],"well":[171],"phone.":[179]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
