{"id":"https://openalex.org/W1595484319","doi":"https://doi.org/10.1109/mva.2015.7153103","title":"Annotation driven MAP search space estimation for sliding-window based person detection","display_name":"Annotation driven MAP search space estimation for sliding-window based person detection","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1595484319","doi":"https://doi.org/10.1109/mva.2015.7153103","mag":"1595484319"},"language":"en","primary_location":{"id":"doi:10.1109/mva.2015.7153103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mva.2015.7153103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 14th IAPR International Conference on Machine Vision Applications (MVA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://publica.fraunhofer.de/documents/N-347652.html","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003385886","display_name":"Stefan Becker","orcid":"https://orcid.org/0000-0001-7367-2519"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Stefan Becker","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032146064","display_name":"Wolfgang H\u00fcbner","orcid":"https://orcid.org/0000-0001-5634-6324"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Hubner","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany","institution_ids":["https://openalex.org/I4210111500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000041406","display_name":"Michael Arens","orcid":"https://orcid.org/0000-0002-7857-0332"},"institutions":[{"id":"https://openalex.org/I4210111500","display_name":"Fraunhofer Institute of Optronics, System Technologies and Image Exploitation","ror":"https://ror.org/01zx97922","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210111500","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Arens","raw_affiliation_strings":["Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany"],"affiliations":[{"raw_affiliation_string":"Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany","institution_ids":["https://openalex.org/I4210111500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003385886"],"corresponding_institution_ids":["https://openalex.org/I4210111500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0358112,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"430","last_page":"434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9958000183105469,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.8344765901565552},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.6843874454498291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6505661010742188},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.5434146523475647},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4907899796962738},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47729432582855225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.475232869386673},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.45475542545318604},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.452913761138916},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4332984983921051},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.41667309403419495},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4102197289466858},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3791823983192444},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3483268618583679},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23643946647644043},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.16448643803596497},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13957026600837708},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.12307682633399963}],"concepts":[{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.8344765901565552},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.6843874454498291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6505661010742188},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.5434146523475647},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4907899796962738},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47729432582855225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.475232869386673},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.45475542545318604},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.452913761138916},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4332984983921051},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.41667309403419495},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4102197289466858},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3791823983192444},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3483268618583679},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23643946647644043},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.16448643803596497},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13957026600837708},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.12307682633399963},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/mva.2015.7153103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mva.2015.7153103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 14th IAPR International Conference on Machine Vision Applications (MVA)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-347652","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-347652.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/388595","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/388595","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:fraunhofer.de:N-347652","is_oa":true,"landing_page_url":"http://publica.fraunhofer.de/documents/N-347652.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IOSB","raw_type":"Conference Paper"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W626667024","https://openalex.org/W1573096183","https://openalex.org/W1600255690","https://openalex.org/W1972683771","https://openalex.org/W1988520084","https://openalex.org/W2031454541","https://openalex.org/W2044313232","https://openalex.org/W2077513643","https://openalex.org/W2098792943","https://openalex.org/W2104446196","https://openalex.org/W2113201641","https://openalex.org/W2131323740","https://openalex.org/W2139479830","https://openalex.org/W2146352414","https://openalex.org/W2161969291","https://openalex.org/W2168356304","https://openalex.org/W2974222084","https://openalex.org/W4249099346","https://openalex.org/W6675396308","https://openalex.org/W6680831728"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2109115373","https://openalex.org/W2183246718","https://openalex.org/W2099261052","https://openalex.org/W2390901981","https://openalex.org/W2608226141","https://openalex.org/W2352028961","https://openalex.org/W2124097254","https://openalex.org/W3014558862","https://openalex.org/W3026806648"],"abstract_inverted_index":{"A":[0],"common":[1],"method":[2],"for":[3,126],"performing":[4],"multi-scale":[5],"person":[6,26,72],"detection":[7,115,131],"is":[8,22,40,108],"a":[9,19,62,64,75,90],"sliding":[10,30,104],"window":[11,15,31,105],"classification.":[12],"For":[13],"every":[14],"location":[16],"and":[17,94,133],"scale":[18],"binary":[20],"classification":[21],"done.":[23],"Many":[24],"state-of-the-art":[25],"detectors":[27],"follow":[28],"this":[29,35],"paradigm.":[32],"Not":[33],"only":[34,70],"exhaustive":[36],"search":[37,58,120],"space":[38,121],"strategy":[39,107],"computationally":[41],"expensive,":[42],"it":[43],"usually":[44],"produces":[45],"large":[46],"number":[47],"of":[48,74,86],"false":[49],"positives.":[50],"In":[51],"order":[52],"to":[53,100],"estimate":[54],"an":[55],"optimal":[56],"reduced":[57],"space,":[59],"we":[60],"derive":[61],"maximum":[63],"posteriori":[65],"probability":[66],"(MAP)":[67],"solution":[68,80],"given":[69],"the":[71,82,101,118,128],"annotations":[73],"dataset.":[76],"The":[77,97],"proposed":[78],"MAP":[79,119],"considers":[81],"naturally":[83],"height":[84],"distribution":[85],"persons,":[87],"deviations":[88],"from":[89],"flat":[91],"world":[92],"assumption,":[93],"annotation":[95],"uncertainty.":[96],"effectiveness":[98],"compared":[99],"traditional":[102],"uniform":[103],"selection":[106],"shown":[109],"on":[110],"different":[111],"realistic":[112],"monocular":[113],"pedestrian":[114],"datasets.":[116],"Moreover":[117],"estimation":[122],"provides":[123],"design":[124],"parameters":[125],"modeling":[127],"tradeoff":[129],"between":[130],"performance":[132],"runtime":[134],"constraints.":[135]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
