{"id":"https://openalex.org/W2800970297","doi":"https://doi.org/10.1117/12.2310117","title":"Compressed normalized block difference for object tracking","display_name":"Compressed normalized block difference for object tracking","publication_year":2018,"publication_date":"2018-04-13","ids":{"openalex":"https://openalex.org/W2800970297","doi":"https://doi.org/10.1117/12.2310117","mag":"2800970297"},"language":"en","primary_location":{"id":"doi:10.1117/12.2310117","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2310117","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Tenth International Conference on Machine Vision (ICMV 2017)","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/A5016810352","display_name":"Dengzhuo Zhang","orcid":"https://orcid.org/0000-0002-2874-1092"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dengzhuo Zhang","raw_affiliation_strings":["Yunnan Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Yunnan Univ. (China)","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034124944","display_name":"Donglan Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donglan Cai","raw_affiliation_strings":["Yunnan Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Yunnan Univ. (China)","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085807713","display_name":"Hao Zhou","orcid":"https://orcid.org/0000-0002-9256-6022"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhou","raw_affiliation_strings":["Yunnan Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Yunnan Univ. (China)","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101821738","display_name":"Lan Ge","orcid":"https://orcid.org/0000-0001-8692-3225"},"institutions":[{"id":"https://openalex.org/I4210159876","display_name":"Institute of Physics","ror":"https://ror.org/05cvf7v30","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210159876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Lan","raw_affiliation_strings":["Kunming Institute of Physics (China)"],"affiliations":[{"raw_affiliation_string":"Kunming Institute of Physics (China)","institution_ids":["https://openalex.org/I4210159876"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076074964","display_name":"Yun Gao","orcid":"https://orcid.org/0000-0002-9637-5119"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]},{"id":"https://openalex.org/I4210159876","display_name":"Institute of Physics","ror":"https://ror.org/05cvf7v30","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210159876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun GAO","raw_affiliation_strings":["Kunming Institute of Physics (China)","Yunnan Univ. (China)"],"affiliations":[{"raw_affiliation_string":"Kunming Institute of Physics (China)","institution_ids":["https://openalex.org/I4210159876"]},{"raw_affiliation_string":"Yunnan Univ. (China)","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016810352"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04459076,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"82","last_page":"82"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9988999962806702,"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":0.9980999827384949,"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/feature","display_name":"Feature (linguistics)","score":0.716079592704773},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7080609798431396},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6554098725318909},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6379700899124146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6325734853744507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6133826375007629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5779434442520142},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5300901532173157},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.49910593032836914},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40637898445129395},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.322896808385849},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3224976658821106}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.716079592704773},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7080609798431396},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6554098725318909},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6379700899124146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6325734853744507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6133826375007629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5779434442520142},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5300901532173157},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.49910593032836914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40637898445129395},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.322896808385849},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3224976658821106},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2310117","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2310117","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Tenth International Conference on Machine Vision (ICMV 2017)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W161114242","https://openalex.org/W1120312422","https://openalex.org/W2016790919","https://openalex.org/W2024657922","https://openalex.org/W2109579504","https://openalex.org/W2118345389","https://openalex.org/W2129131372","https://openalex.org/W2129638195","https://openalex.org/W2129812935","https://openalex.org/W2147533695","https://openalex.org/W2158592639","https://openalex.org/W2165037244","https://openalex.org/W2247274765","https://openalex.org/W2280226538","https://openalex.org/W2343187456","https://openalex.org/W6606595081","https://openalex.org/W6677356763","https://openalex.org/W6681780711","https://openalex.org/W6684332838","https://openalex.org/W6695416801"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W4300044672","https://openalex.org/W2810730439","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W2465351041","https://openalex.org/W1976264255"],"abstract_inverted_index":{"Feature":[0],"extraction":[1],"is":[2,40],"very":[3],"important":[4],"for":[5,16],"robust":[6],"and":[7,31,151],"real-time":[8,17],"tracking.":[9],"Compressive":[10],"sensing":[11,101],"provided":[12],"a":[13,46,61,68,93],"technical":[14],"support":[15],"feature":[18,52,66,72,87,97,130],"extraction.":[19],"However,":[20],"all":[21],"existing":[22],"compressive":[23,100],"tracking":[24],"were":[25],"based":[26,98,127,141],"on":[27,99,119,128,142],"compressed":[28,48,143],"Haar-like":[29,144],"feature,":[30,145],"how":[32],"to":[33,82],"compress":[34],"many":[35],"more":[36],"excellent":[37],"high-dimensional":[38],"features":[39],"worth":[41],"researching.":[42],"In":[43],"this":[44],"paper,":[45],"novel":[47],"normalized":[49,63,69,94],"block":[50,70,95],"difference":[51,65,71,96],"(CNBD)":[53],"was":[54],"proposed.":[55],"For":[56],"resisting":[57],"noise":[58],"effectively":[59],"in":[60,76,146],"highdimensional":[62],"pixel":[64],"(NPD),":[67],"extends":[73],"two":[74,83],"pixels":[75],"the":[77,104,110,125],"original":[78],"formula":[79],"of":[80,116,148],"NPD":[81],"blocks.":[84],"A":[85],"CNBD":[86,129],"can":[88,131],"be":[89],"obtained":[90],"by":[91],"compressing":[92],"theory,":[102],"with":[103],"sparse":[105],"random":[106],"Gaussian":[107],"matrix":[108],"as":[109],"measurement":[111],"matrix.":[112],"The":[113],"comparative":[114],"experiments":[115],"7":[117],"trackers":[118],"20":[120],"challenging":[121],"sequences":[122],"showed":[123],"that":[124],"tracker":[126,140],"perform":[132],"better":[133],"than":[134,138],"other":[135],"trackers,":[136],"especially":[137],"FCT":[139],"terms":[147],"AUC,":[149],"SR":[150],"Precision.":[152]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
