{"id":"https://openalex.org/W7130580666","doi":"https://doi.org/10.1109/apccas67402.2025.11377388","title":"Energy-Efficient Surveillance via Event-Driven ROI Detection with DVS-CIS Fusion","display_name":"Energy-Efficient Surveillance via Event-Driven ROI Detection with DVS-CIS Fusion","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W7130580666","doi":"https://doi.org/10.1109/apccas67402.2025.11377388"},"language":null,"primary_location":{"id":"doi:10.1109/apccas67402.2025.11377388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apccas67402.2025.11377388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","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/A5072544388","display_name":"Mincheol Cha","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Mincheol Cha","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113296003","display_name":"Keehyuk Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Keehyuk Lee","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088587799","display_name":"Soosung Kim","orcid":"https://orcid.org/0009-0002-4430-7752"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soosung Kim","raw_affiliation_strings":["Neuro Reality Vision Corp.,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Neuro Reality Vision Corp.,South Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110936759","display_name":"Hyunsurk Ryu","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunsurk Ryu","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014900695","display_name":"Xuan Truong Nguyen","orcid":"https://orcid.org/0000-0002-7527-6971"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Xuan Truong Nguyen","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126442465","display_name":"Hyuk-Jae Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuk-Jae Lee","raw_affiliation_strings":["Seoul National University,Department of Electrical and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seoul National University,Department of Electrical and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57534471,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.738099992275238,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.738099992275238,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.11789999902248383,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10036","display_name":"Advanced Neural Network Applications","score":0.044599998742341995,"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/object-detection","display_name":"Object detection","score":0.5630999803543091},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5127999782562256},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.4875999987125397},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.4778999984264374},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.47380000352859497},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44449999928474426},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4106000065803528},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41040000319480896},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6833000183105469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6488999724388123},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5694000124931335},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5630999803543091},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5127999782562256},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.4875999987125397},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.4778999984264374},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.47380000352859497},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44449999928474426},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4205000102519989},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4106000065803528},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.39890000224113464},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.3416999876499176},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.2953999936580658},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2678999900817871},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2653999924659729},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.25839999318122864},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2563999891281128}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apccas67402.2025.11377388","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apccas67402.2025.11377388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9065765142440796,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2016574277","https://openalex.org/W2138787968","https://openalex.org/W2144187604","https://openalex.org/W2172654076","https://openalex.org/W2512653618","https://openalex.org/W2594491944","https://openalex.org/W2902709485","https://openalex.org/W3090440982","https://openalex.org/W3200691027","https://openalex.org/W4385338963","https://openalex.org/W4399121711","https://openalex.org/W4408862768","https://openalex.org/W4411725612","https://openalex.org/W4411725643","https://openalex.org/W4411726552"],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"presents":[2],"an":[3,138],"ultra-low-power":[4],"surveillance":[5],"system":[6,121],"that":[7,71],"fuses":[8],"Dynamic":[9],"Vision":[10],"Sensors":[11,20],"(DVS)":[12],"[5],":[13],"[11],":[14],"[14],":[15],"[15]":[16],"and":[17,30,75,98],"CMOS":[18],"Image":[19],"(CIS)":[21],"for":[22,40],"real-time":[23,135],"object":[24],"detection.":[25],"DVS":[26,91],"offer":[27],"ultra-low":[28],"latency":[29],"high":[31],"dynamic":[32],"range":[33],"with":[34,116,137],"minimal":[35],"energy,":[36],"making":[37],"them":[38],"ideal":[39],"efficient":[41],"visual":[42],"processing":[43,80],"[7],":[44],"[9].":[45],"However,":[46],"conventional":[47],"always-on":[48],"systems":[49],"waste":[50],"energy":[51,127],"on":[52,112],"redundant":[53],"deep":[54],"neural":[55,79],"network":[56],"(DNN)":[57],"inference.":[58],"To":[59],"address":[60],"this,":[61],"we":[62],"propose":[63],"a":[64,78,95,113,117,123,130],"DVS-based":[65],"Region-of-":[66],"Interest":[67],"(ROI)":[68],"detection":[69],"algorithm":[70,89],"identifies":[72],"motion-triggered":[73],"regions":[74],"selectively":[76],"activates":[77],"unit":[81],"(NPU)":[82],"only":[83],"when":[84],"meaningful":[85],"activity":[86],"occurs.":[87],"The":[88],"models":[90],"event":[92],"distributions":[93],"using":[94,101],"probabilistic":[96],"framework":[97],"extracts":[99],"ROI":[100],"Kadane's":[102],"maximum":[103],"sub":[104],"array":[105],"algorithm,":[106],"enabling":[107],"linear-time":[108],"inference":[109,140],"triggering.":[110],"Implemented":[111],"dual-FPGA":[114],"platform":[115],"YOLOv3-Tiny":[118],"NPU,":[119],"the":[120],"achieves":[122],"31.5%":[124],"reduction":[125],"in":[126],"consumption":[128],"over":[129],"24-hour":[131],"deployment":[132],"while":[133],"maintaining":[134],"performance":[136],"I8ms":[139],"latency.":[141]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-20T00:00:00"}
