{"id":"https://openalex.org/W2565859913","doi":"https://doi.org/10.1145/3009977.3010071","title":"Crowd motion analysis for group detection","display_name":"Crowd motion analysis for group detection","publication_year":2016,"publication_date":"2016-12-18","ids":{"openalex":"https://openalex.org/W2565859913","doi":"https://doi.org/10.1145/3009977.3010071","mag":"2565859913"},"language":"en","primary_location":{"id":"doi:10.1145/3009977.3010071","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3009977.3010071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing","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/A5025512806","display_name":"Neha Bhargava","orcid":null},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Neha Bhargava","raw_affiliation_strings":["Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016405213","display_name":"Subhasis Chaudhuri","orcid":"https://orcid.org/0000-0002-1680-0016"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subhasis Chaudhuri","raw_affiliation_strings":["Indian Institute of Technology Bombay, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Bombay, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025512806"],"corresponding_institution_ids":["https://openalex.org/I162827531"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18988443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9990000128746033,"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":0.7146918177604675},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.6579793691635132},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.6376286149024963},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5415388345718384},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5224910378456116},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.504974901676178},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4635656774044037},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4451168179512024},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.43309688568115234},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4191983640193939},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35595962405204773},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3458080589771271},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17869487404823303}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7146918177604675},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.6579793691635132},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.6376286149024963},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5415388345718384},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5224910378456116},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.504974901676178},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4635656774044037},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4451168179512024},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.43309688568115234},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4191983640193939},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35595962405204773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3458080589771271},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17869487404823303},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3009977.3010071","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3009977.3010071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W31178829","https://openalex.org/W47624021","https://openalex.org/W166089218","https://openalex.org/W1886885333","https://openalex.org/W1981276685","https://openalex.org/W1999915399","https://openalex.org/W2005614539","https://openalex.org/W2009238858","https://openalex.org/W2011128100","https://openalex.org/W2033403400","https://openalex.org/W2036721747","https://openalex.org/W2039430607","https://openalex.org/W2042015300","https://openalex.org/W2047617665","https://openalex.org/W2065994824","https://openalex.org/W2079023123","https://openalex.org/W2105269163","https://openalex.org/W2107887685","https://openalex.org/W2127852267","https://openalex.org/W2153990517","https://openalex.org/W2165874743","https://openalex.org/W2167052694","https://openalex.org/W2990138404","https://openalex.org/W3105265400"],"related_works":["https://openalex.org/W2393022482","https://openalex.org/W2377346130","https://openalex.org/W2361092061","https://openalex.org/W2319775965","https://openalex.org/W2357314690","https://openalex.org/W2191886813","https://openalex.org/W1986317414","https://openalex.org/W2163394011","https://openalex.org/W2795976185","https://openalex.org/W2353606679"],"abstract_inverted_index":{"Understanding":[0],"crowd":[1,39],"dynamics":[2,23],"is":[3,51,110],"an":[4,91],"interesting":[5],"problem":[6],"in":[7,85],"computer":[8],"vision":[9],"owing":[10],"to":[11,20,69],"its":[12],"various":[13],"applications.":[14],"We":[15,88],"propose":[16,90],"a":[17,46,54,75,113,120],"dynamical":[18],"system":[19],"model":[21,31,50,68],"the":[22,28,33,38,41,67,72,79,86,98,101,105],"of":[24,27,37,74,100,104,123],"collective":[25],"motion":[26],"crowd.":[29],"The":[30,49,63,107],"learns":[32],"spatio-temporal":[34],"interaction":[35,102],"pattern":[36],"from":[40],"track":[42],"data":[43],"captured":[44],"over":[45,128],"time":[47],"period.":[48],"trained":[52],"under":[53],"least":[55],"square":[56],"formulation":[57],"with":[58],"spatial":[59,64],"and":[60,78],"temporal":[61,80,83],"constraints.":[62],"constraint":[65,81],"allows":[66],"consider":[70],"only":[71],"neighbors":[73],"particular":[76],"agent":[77],"enforces":[82],"smoothness":[84],"model.":[87,106],"also":[89],"effective":[92],"group":[93,108,125],"detection":[94,109,126],"algorithm":[95,127],"that":[96],"utilizes":[97],"eigenvectors":[99],"matrix":[103],"cast":[111],"as":[112],"spectral":[114],"clustering":[115],"problem.":[116],"Extensive":[117],"experimentation":[118],"demonstrates":[119],"superlative":[121],"performance":[122],"our":[124],"state-of-the-art":[129],"methods.":[130]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}