{"id":"https://openalex.org/W2294696353","doi":"https://doi.org/10.1145/2822013.2822024","title":"Deep signatures for indexing and retrieval in large motion databases","display_name":"Deep signatures for indexing and retrieval in large motion databases","publication_year":2015,"publication_date":"2015-11-03","ids":{"openalex":"https://openalex.org/W2294696353","doi":"https://doi.org/10.1145/2822013.2822024","mag":"2294696353"},"language":"en","primary_location":{"id":"doi:10.1145/2822013.2822024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2822013.2822024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games","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/A5101479917","display_name":"Yingying Wang","orcid":"https://orcid.org/0000-0003-3293-0790"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yingying Wang","raw_affiliation_strings":[""],"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013628099","display_name":"Michael Neff","orcid":"https://orcid.org/0000-0003-0226-2808"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Neff","raw_affiliation_strings":[""],"affiliations":[{"raw_affiliation_string":"","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101479917"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7026,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.93486492,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T12290","display_name":"Human Motion and Animation","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10812","display_name":"Human Pose and Action Recognition","score":0.9986000061035156,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9984999895095825,"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":0.8127012848854065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6943312287330627},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.6689045429229736},{"id":"https://openalex.org/keywords/byte","display_name":"Byte","score":0.6290048956871033},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.603339672088623},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.5887870788574219},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5859630107879639},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.571736216545105},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.448019415140152},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44508007168769836},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.43248608708381653},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4303479492664337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07966265082359314}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8127012848854065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6943312287330627},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6689045429229736},{"id":"https://openalex.org/C43364308","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Byte","level":2,"score":0.6290048956871033},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.603339672088623},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.5887870788574219},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5859630107879639},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.571736216545105},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.448019415140152},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44508007168769836},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.43248608708381653},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4303479492664337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07966265082359314},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2822013.2822024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2822013.2822024","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W54274230","https://openalex.org/W189596042","https://openalex.org/W1489548117","https://openalex.org/W1541742946","https://openalex.org/W1826372865","https://openalex.org/W1982905909","https://openalex.org/W1988608780","https://openalex.org/W1993882792","https://openalex.org/W2007943216","https://openalex.org/W2023775764","https://openalex.org/W2028605775","https://openalex.org/W2029903115","https://openalex.org/W2100495367","https://openalex.org/W2109349805","https://openalex.org/W2115096495","https://openalex.org/W2118560764","https://openalex.org/W2125113755","https://openalex.org/W2133835838","https://openalex.org/W2136922672","https://openalex.org/W2139658427","https://openalex.org/W2145038566","https://openalex.org/W2150111138","https://openalex.org/W2163605009","https://openalex.org/W2165870892","https://openalex.org/W2184188583","https://openalex.org/W2186775481","https://openalex.org/W2557865186","https://openalex.org/W2560674852"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"Data-driven":[0],"motion":[1,13,42,71,82,96,104,149,173],"research":[2],"requires":[3],"effective":[4],"tools":[5],"to":[6,23,88,118],"compress,":[7],"index,":[8],"retrieve":[9],"and":[10,106,146,151,162],"reconstruct":[11],"captured":[12],"data.":[14],"In":[15],"this":[16],"paper,":[17],"we":[18],"present":[19],"a":[20,28,35,65,70,90,95,109,131,137,169],"novel":[21],"method":[22],"perform":[24],"these":[25],"tasks":[26],"using":[27,139],"deep":[29,33,62,158],"learning":[30],"architecture.":[31],"Our":[32],"autoencoder,":[34],"form":[36],"of":[37,58,69,94,123],"artificial":[38],"neural":[39],"network,":[40],"encodes":[41],"segments":[43,174],"into":[44],"\"deep":[45,132],"signatures\".":[46],"This":[47],"signature":[48,63,159],"is":[49,64,127,135,160],"formed":[50],"by":[51,129],"concatenating":[52],"signatures":[53],"for":[54,103],"functionally":[55],"different":[56],"parts":[57],"the":[59,157],"body.":[60],"The":[61],"highly":[66],"condensed":[67],"representation":[68,93],"segment,":[72],"requiring":[73],"only":[74],"20":[75],"bytes,":[76],"yet":[77],"still":[78],"encoding":[79],"high":[80],"level":[81],"features.":[83],"It":[84],"can":[85,99,175],"be":[86,100,176],"used":[87,102],"produce":[89],"very":[91,110],"compact":[92],"database":[97],"that":[98,134,155],"effectively":[101],"indexing":[105],"retrieval,":[107],"with":[108,165,181],"small":[111],"memory":[112],"footprint.":[113],"Database":[114],"searches":[115],"are":[116],"reduced":[117],"low":[119],"cost":[120],"binary":[121],"comparisons":[122],"signatures.":[124],"Motion":[125],"reconstruction":[126],"achieved":[128],"fixing":[130],"signature\"":[133],"missing":[136],"section":[138],"Gibbs":[140],"Sampling.":[141],"We":[142],"tested":[143],"both":[144],"manually":[145],"automatically":[147],"segmented":[148],"databases":[150],"our":[152],"experiments":[153],"show":[154],"extracting":[156],"fast":[161],"scales":[163],"well":[164],"large":[166],"databases.":[167],"Given":[168],"query":[170],"motion,":[171],"similar":[172],"retrieved":[177],"at":[178],"interactive":[179],"speed":[180],"excellent":[182],"match":[183],"quality.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}