{"id":"https://openalex.org/W2126413547","doi":"https://doi.org/10.1007/978-3-642-23123-0_39","title":"Will the Pedestrian Cross? Probabilistic Path Prediction Based on Learned Motion Features","display_name":"Will the Pedestrian Cross? Probabilistic Path Prediction Based on Learned Motion Features","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W2126413547","doi":"https://doi.org/10.1007/978-3-642-23123-0_39","mag":"2126413547"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-23123-0_39","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-23123-0_39","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5013875392","display_name":"Christoph G. Keller","orcid":null},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christoph G. Keller","raw_affiliation_strings":["Image & Pattern Analysis Group, Univ. of Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"Image & Pattern Analysis Group, Univ. of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054075670","display_name":"Christoph Hermes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christoph Hermes","raw_affiliation_strings":["Applied Informatics Group, Univ. of Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Applied Informatics Group, Univ. of Bielefeld, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085298812","display_name":"Dariu M. Gavrila","orcid":"https://orcid.org/0000-0002-1810-4196"},"institutions":[{"id":"https://openalex.org/I887064364","display_name":"University of Amsterdam","ror":"https://ror.org/04dkp9463","country_code":"NL","type":"education","lineage":["https://openalex.org/I887064364"]},{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE","NL"],"is_corresponding":false,"raw_author_name":"Dariu M. Gavrila","raw_affiliation_strings":["Environment Perception, Group Research, Daimler AG, Ulm, Germany","Intelligent Systems Lab, Fac. of Science, Univ. of Amsterdam, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Environment Perception, Group Research, Daimler AG, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"Intelligent Systems Lab, Fac. of Science, Univ. of Amsterdam, The Netherlands","institution_ids":["https://openalex.org/I887064364"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013875392"],"corresponding_institution_ids":["https://openalex.org/I223822909"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":8.7788,"has_fulltext":false,"cited_by_count":61,"citation_normalized_percentile":{"value":0.98685993,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"386","last_page":"395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.7637835741043091},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.7122986316680908},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6436867713928223},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6379374861717224},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.5686343312263489},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5363401770591736},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5329896807670593},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5183557271957397},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5055255889892578},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.492241770029068},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4605964422225952},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44643861055374146},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.43627768754959106},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4280466139316559},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3390108048915863},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21986588835716248},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11073878407478333},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0696675181388855}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.7637835741043091},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.7122986316680908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6436867713928223},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6379374861717224},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.5686343312263489},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5363401770591736},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5329896807670593},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5183557271957397},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5055255889892578},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.492241770029068},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4605964422225952},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44643861055374146},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.43627768754959106},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4280466139316559},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3390108048915863},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21986588835716248},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11073878407478333},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0696675181388855},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1007/978-3-642-23123-0_39","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-23123-0_39","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.247.7616","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.247.7616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.gavrila.net/dagm11_ped_predict.pdf","raw_type":"text"},{"id":"pmh:oai:dare.uva.nl:openaire_cris_publications/54c5c155-6467-496c-8cf0-1c5ade600ee6","is_oa":false,"landing_page_url":"https://handle.uba.uva.nl/personal/pure/en/publications/will-the-pedestrian-cross(54c5c155-6467-496c-8cf0-1c5ade600ee6).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400088","display_name":"UvA-DARE (University of Amsterdam)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887064364","host_organization_name":"University of Amsterdam","host_organization_lineage":["https://openalex.org/I887064364"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Keller, C G, Hermes, C & Gavrila, D M 2011, Will the pedestrian cross? Probabilistic path prediction based on learned motion features. in R Mester & M Felsberg (eds), Pattern Recognition : 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31-September 2 2011: proceedings. Lecture Notes in Computer Science, vol. 6835, Heidelberg, pp. 386-395. https://doi.org/10.1007/978-3-642-23123-0_39","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:uvapub:oai:dare.uva.nl:publications/54c5c155-6467-496c-8cf0-1c5ade600ee6","is_oa":false,"landing_page_url":"https://dare.uva.nl/personal/pure/en/publications/will-the-pedestrian-cross(54c5c155-6467-496c-8cf0-1c5ade600ee6).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Pattern Recognition: 33rd DAGM Symposium, Frankfurt/Main, Germany, August 31-September 2 2011: proceedings, 386 - 395","raw_type":"info:eu-repo/semantics/conferencepaper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6200000047683716,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1531532259","https://openalex.org/W1532653240","https://openalex.org/W1980985548","https://openalex.org/W1992884181","https://openalex.org/W1996097451","https://openalex.org/W2058340587","https://openalex.org/W2067191022","https://openalex.org/W2098813977","https://openalex.org/W2099913338","https://openalex.org/W2107775979","https://openalex.org/W2109432061","https://openalex.org/W2117248802","https://openalex.org/W2121511604","https://openalex.org/W2127786330","https://openalex.org/W2128769005","https://openalex.org/W2135142117","https://openalex.org/W2139479830","https://openalex.org/W2155268664","https://openalex.org/W2161969291","https://openalex.org/W2502277634","https://openalex.org/W2502896360"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W4297270893","https://openalex.org/W2577671007","https://openalex.org/W1591216093","https://openalex.org/W2912100719","https://openalex.org/W2963330455","https://openalex.org/W3091300685","https://openalex.org/W2331280411","https://openalex.org/W2783931899"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}