{"id":"https://openalex.org/W2189613666","doi":"https://doi.org/10.1109/mmsp.2015.7340869","title":"Graph spectral motion segmentation based on motion vanishing point analysis","display_name":"Graph spectral motion segmentation based on motion vanishing point analysis","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2189613666","doi":"https://doi.org/10.1109/mmsp.2015.7340869","mag":"2189613666"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp.2015.7340869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2015.7340869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","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/A5016854114","display_name":"Dong Tian","orcid":"https://orcid.org/0000-0002-2310-0974"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dong Tian","raw_affiliation_strings":["Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047382767","display_name":"Jiun-Yu Kao","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiun-Yu Kao","raw_affiliation_strings":["Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA","Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I1174212"]},{"raw_affiliation_string":"Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101648073","display_name":"Hassan Mansour","orcid":"https://orcid.org/0000-0002-1667-9885"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hassan Mansour","raw_affiliation_strings":["Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049841606","display_name":"Anthony Vetro","orcid":"https://orcid.org/0000-0002-8194-573X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anthony Vetro","raw_affiliation_strings":["Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electronic Research Labs (MERL), Cambridge, MA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5016854114"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3744,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.69535521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994999766349792,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994999766349792,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9919999837875366,"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":0.9843000173568726,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.793152928352356},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7556390762329102},{"id":"https://openalex.org/keywords/motion-field","display_name":"Motion field","score":0.703711748123169},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6744604110717773},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.6040030121803284},{"id":"https://openalex.org/keywords/quarter-pixel-motion","display_name":"Quarter-pixel motion","score":0.5689112544059753},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5486928224563599},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.48443105816841125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4730105698108673},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.46710601449012756},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4555943012237549},{"id":"https://openalex.org/keywords/structure-from-motion","display_name":"Structure from motion","score":0.45112743973731995},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4481564462184906},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.44262051582336426},{"id":"https://openalex.org/keywords/motion-analysis","display_name":"Motion analysis","score":0.4231157898902893},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.39541617035865784},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3801994323730469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3635442852973938}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.793152928352356},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7556390762329102},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.703711748123169},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6744604110717773},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.6040030121803284},{"id":"https://openalex.org/C174493125","wikidata":"https://www.wikidata.org/wiki/Q1073461","display_name":"Quarter-pixel motion","level":3,"score":0.5689112544059753},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5486928224563599},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.48443105816841125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4730105698108673},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.46710601449012756},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4555943012237549},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.45112743973731995},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4481564462184906},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.44262051582336426},{"id":"https://openalex.org/C2777036941","wikidata":"https://www.wikidata.org/wiki/Q6917771","display_name":"Motion analysis","level":2,"score":0.4231157898902893},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.39541617035865784},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3801994323730469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3635442852973938},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mmsp.2015.7340869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2015.7340869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.725.1127","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.725.1127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.merl.com/publications/docs/TR2015-122.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1520481592","https://openalex.org/W1913356549","https://openalex.org/W1966809113","https://openalex.org/W1974192600","https://openalex.org/W1977556410","https://openalex.org/W1993962865","https://openalex.org/W2012184117","https://openalex.org/W2049612634","https://openalex.org/W2052311585","https://openalex.org/W2101491865","https://openalex.org/W2146395539","https://openalex.org/W2160888640","https://openalex.org/W2162616721","https://openalex.org/W2165874743","https://openalex.org/W2294312563","https://openalex.org/W6684578312"],"related_works":["https://openalex.org/W1501297619","https://openalex.org/W2120943489","https://openalex.org/W1484667368","https://openalex.org/W2026674073","https://openalex.org/W1978569796","https://openalex.org/W2012241496","https://openalex.org/W4232311089","https://openalex.org/W2010464357","https://openalex.org/W4211095474","https://openalex.org/W3145278978"],"abstract_inverted_index":{"Motion":[0],"segmentation":[1,34,92,99],"relies":[2],"on":[3,50,100],"identifying":[4],"coherent":[5],"relationships":[6],"between":[7,110],"image":[8,77,81,101],"pixels":[9],"that":[10,36,86],"are":[11],"associated":[12,78],"with":[13,79,103],"motion":[14,33,39,47,51,69,74,91,108],"vectors.":[15],"However,":[16],"perspective":[17,105],"differences":[18],"can":[19],"often":[20],"deteriorate":[21],"the":[22,38,68,73,80,87],"performance":[23],"of":[24,41],"conventional":[25],"techniques.":[26],"In":[27],"this":[28],"paper,":[29],"we":[30],"develop":[31],"a":[32,42,62],"scheme":[35],"utilizes":[37],"map":[40],"single":[43],"frame":[44],"to":[45],"identify":[46],"representations":[48],"based":[49],"vanishing":[52,75],"points.":[53],"Segmentation":[54],"is":[55,65],"achieved":[56],"using":[57,67,107],"graph":[58,64,89],"spectral":[59,90],"clustering":[60],"where":[61],"novel":[63],"constructed":[66],"representation":[70],"distances":[71],"in":[72],"point":[76],"pixels.":[82],"Experimental":[83],"results":[84],"show":[85],"proposed":[88],"algorithm":[93],"outperforms":[94],"state-of-the-art":[95],"methods":[96],"for":[97],"dense":[98],"sequences":[102],"strong":[104],"effects":[106],"vectors":[109],"only":[111],"two":[112],"images.":[113]},"counts_by_year":[{"year":2016,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
