{"id":"https://openalex.org/W2565250676","doi":"https://doi.org/10.1109/iros.2016.7759724","title":"A triangle histogram for object classification by tactile sensing","display_name":"A triangle histogram for object classification by tactile sensing","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2565250676","doi":"https://doi.org/10.1109/iros.2016.7759724","mag":"2565250676"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2016.7759724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5079568748","display_name":"Mabel M. Zhang","orcid":"https://orcid.org/0000-0002-5130-1183"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mabel M. Zhang","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047853405","display_name":"Monroe Kennedy","orcid":"https://orcid.org/0000-0002-4567-0409"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Monroe D. Kennedy","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042002060","display_name":"M. Ani Hsieh","orcid":"https://orcid.org/0000-0003-2186-9074"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Ani Hsieh","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050660826","display_name":"Kostas Daniilidis","orcid":"https://orcid.org/0000-0003-0498-0758"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kostas Daniilidis","raw_affiliation_strings":["GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"GRASP Laboratory, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5079568748"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":null,"apc_paid":null,"fwci":2.0317,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.86071608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4931","last_page":"4938"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10914","display_name":"Tactile and Sensory Interactions","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.998199999332428,"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/T10789","display_name":"Interactive and Immersive Displays","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.8096335530281067},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7713865041732788},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7708479166030884},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6602262854576111},{"id":"https://openalex.org/keywords/tactile-sensor","display_name":"Tactile sensor","score":0.6218490600585938},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5982542037963867},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5666460394859314},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.5375174880027771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4853922128677368},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.48055580258369446},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4579095244407654},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.4368263781070709},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43394774198532104},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4259713292121887},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.252010315656662},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.13825109601020813},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.133856862783432}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8096335530281067},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7713865041732788},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7708479166030884},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6602262854576111},{"id":"https://openalex.org/C46722567","wikidata":"https://www.wikidata.org/wiki/Q7674139","display_name":"Tactile sensor","level":3,"score":0.6218490600585938},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5982542037963867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5666460394859314},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.5375174880027771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4853922128677368},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.48055580258369446},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4579095244407654},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.4368263781070709},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43394774198532104},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4259713292121887},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.252010315656662},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.13825109601020813},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.133856862783432},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2016.7759724","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2016.7759724","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1993302780","https://openalex.org/W2000795044","https://openalex.org/W2012224615","https://openalex.org/W2014886722","https://openalex.org/W2017801178","https://openalex.org/W2021683594","https://openalex.org/W2031060683","https://openalex.org/W2041388347","https://openalex.org/W2042599225","https://openalex.org/W2052390545","https://openalex.org/W2061734820","https://openalex.org/W2064990398","https://openalex.org/W2082669075","https://openalex.org/W2084200723","https://openalex.org/W2093725709","https://openalex.org/W2106828303","https://openalex.org/W2109081464","https://openalex.org/W2112714380","https://openalex.org/W2119104235","https://openalex.org/W2131341196","https://openalex.org/W2138351865","https://openalex.org/W2138648596","https://openalex.org/W2152864241","https://openalex.org/W2167359739","https://openalex.org/W2180140657","https://openalex.org/W2295332248","https://openalex.org/W2296434941","https://openalex.org/W2515115737","https://openalex.org/W2570268714","https://openalex.org/W2887302987","https://openalex.org/W3145100414","https://openalex.org/W4232810638","https://openalex.org/W6726073876"],"related_works":["https://openalex.org/W2131341196","https://openalex.org/W2138648596","https://openalex.org/W2115846099","https://openalex.org/W1581953684","https://openalex.org/W2914333633","https://openalex.org/W2561871937","https://openalex.org/W2003931843","https://openalex.org/W968840149","https://openalex.org/W3133047889","https://openalex.org/W3180220476","https://openalex.org/W2781193762","https://openalex.org/W2023722365","https://openalex.org/W3154650674","https://openalex.org/W2338631224","https://openalex.org/W3204162010","https://openalex.org/W2798462325","https://openalex.org/W2993006212","https://openalex.org/W2998633559","https://openalex.org/W3003964240","https://openalex.org/W2909130473"],"abstract_inverted_index":{"We":[0,31],"present":[1],"a":[2,66,82,88,110,130],"new":[3],"descriptor":[4,119],"for":[5],"tactile":[6,94,131],"3D":[7],"object":[8,14,29,76,124],"classification.":[9],"It":[10],"is":[11],"invariant":[12],"to":[13,18,43,120],"movement":[15],"and":[16,60],"simple":[17],"construct,":[19],"using":[20,87,126],"only":[21],"the":[22,28,58,63,75,100,115,118],"relative":[23],"geometry":[24],"of":[25,35,55,84,99,117],"points":[26],"on":[27],"surface.":[30],"demonstrate":[32],"successful":[33],"classification":[34,103],"185":[36],"objects":[37],"in":[38,48],"10":[39],"categories,":[40],"at":[41,57,62,107],"sparse":[42,93],"dense":[44],"surface":[45],"sampling":[46,98],"rate":[47],"point":[49],"cloud":[50],"simulation,":[51,68],"with":[52,92],"an":[53],"accuracy":[54],"77.5%":[56],"sparsest":[59],"90.1%":[61],"densest.":[64],"In":[65],"physics-based":[67],"we":[69,113],"show":[70,114],"that":[71],"contact":[72],"clouds":[73],"resembling":[74],"shape":[77],"can":[78],"be":[79],"obtained":[80],"by":[81,129],"series":[83],"gripper":[85],"closures":[86],"robotic":[89],"hand":[90],"equipped":[91],"arrays.":[95],"Despite":[96],"sparser":[97],"object's":[101],"surface,":[102],"still":[104],"performs":[105],"well,":[106],"74.7%.":[108],"On":[109],"real":[111],"robot,":[112],"ability":[116],"discriminate":[121],"among":[122],"different":[123],"instances,":[125],"data":[127],"collected":[128],"hand.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
