{"id":"https://openalex.org/W2084719016","doi":"https://doi.org/10.1109/icce-tw.2014.6904056","title":"Image parsing with automatic detection of symmetrical parts and its application on human activity recognition","display_name":"Image parsing with automatic detection of symmetrical parts and its application on human activity recognition","publication_year":2014,"publication_date":"2014-05-01","ids":{"openalex":"https://openalex.org/W2084719016","doi":"https://doi.org/10.1109/icce-tw.2014.6904056","mag":"2084719016"},"language":"en","primary_location":{"id":"doi:10.1109/icce-tw.2014.6904056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-tw.2014.6904056","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 Consumer Electronics - Taiwan","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/A5011402983","display_name":"De-Kai Huang","orcid":null},"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":true,"raw_author_name":"De-Kai Huang","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011881193","display_name":"Tzu-Hao Hsu","orcid":null},"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":"Tzu-Hao Hsu","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027628644","display_name":"Po\u2010Yen Lee","orcid":"https://orcid.org/0000-0002-1825-0003"},"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":"Po-Yen Lee","raw_affiliation_strings":["School of Automation, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101839507","display_name":"Shyi\u2010Chyi Cheng","orcid":"https://orcid.org/0000-0003-4752-0460"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shyi-Chyi Cheng","raw_affiliation_strings":["Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5011402983"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14072687,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"197","last_page":"198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9983999729156494,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.8015362024307251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7840453386306763},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7796928882598877},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.5774972438812256},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5723607540130615},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.5413285493850708},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5319768786430359},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5171093940734863},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.506609320640564},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.48513588309288025},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4690577983856201},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43198734521865845},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.4158184826374054},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36693352460861206},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09538814425468445}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015362024307251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7840453386306763},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7796928882598877},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.5774972438812256},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5723607540130615},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.5413285493850708},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5319768786430359},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5171093940734863},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.506609320640564},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.48513588309288025},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4690577983856201},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43198734521865845},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.4158184826374054},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36693352460861206},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09538814425468445},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-tw.2014.6904056","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-tw.2014.6904056","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 Consumer Electronics - Taiwan","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W1995444699","https://openalex.org/W2015262814","https://openalex.org/W2025508903","https://openalex.org/W2168356304","https://openalex.org/W2170432751","https://openalex.org/W3152330821"],"related_works":["https://openalex.org/W2030098947","https://openalex.org/W1974777989","https://openalex.org/W2003466055","https://openalex.org/W2363834444","https://openalex.org/W2070077862","https://openalex.org/W2765199790","https://openalex.org/W2164944168","https://openalex.org/W2326760703","https://openalex.org/W262984167","https://openalex.org/W2372868647"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"present":[4],"a":[5,102],"variant":[6],"of":[7,43,53,68,134],"Hough":[8,31],"voting":[9,32],"for":[10],"detecting":[11],"and":[12,48,75,94,115,137],"parsing":[13,22,55,116],"image":[14],"objects":[15,74],"into":[16],"their":[17,76],"constituent":[18],"symmetrical":[19,38],"parts.":[20],"The":[21,51,98],"algorithm,":[23],"given":[24],"an":[25,41,58],"input":[26],"image,":[27],"first":[28],"uses":[29],"the":[30,36,54,66,72,85,112,122],"scheme":[33],"to":[34,83,92],"detect":[35],"salient":[37],"parts":[39,77],"by":[40],"integrating":[42],"color":[44],"segmentation,":[45],"depth":[46],"coherence,":[47],"motion":[49],"grouping.":[50],"output":[52],"algorithm":[56],"is":[57,62],"object":[59,86,113],"graph":[60],"which":[61,89],"further":[63],"denoised":[64],"with":[65],"optimization":[67],"dominant":[69],"sets.":[70],"Subsequently,":[71],"detected":[73],"are":[78,90,107],"tracked":[79],"across":[80],"video":[81],"frames":[82],"capture":[84],"part":[87],"movements":[88],"used":[91],"learn":[93],"classify":[95],"human":[96],"activities.":[97],"proposed":[99,123],"approach":[100],"has":[101],"significant":[103],"advantage:":[104],"no":[105],"models":[106],"learned":[108],"in":[109,111,132],"advance":[110],"detection":[114,135],"algorithm.":[117],"Experimental":[118],"results":[119],"show":[120],"that":[121],"method":[124],"gives":[125],"good":[126],"performance":[127],"on":[128],"publicly":[129],"available":[130],"datasets":[131],"terms":[133],"accuracy":[136],"recognition":[138],"rate.":[139]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
