{"id":"https://openalex.org/W4416955818","doi":"https://doi.org/10.1145/3769102.3774381","title":"Poster: \"Semantic-Guided Skip Sampling and Soft Edge Compression for Real-Time Edge-Based Traffic Video Analytics\"","display_name":"Poster: \"Semantic-Guided Skip Sampling and Soft Edge Compression for Real-Time Edge-Based Traffic Video Analytics\"","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4416955818","doi":"https://doi.org/10.1145/3769102.3774381"},"language":null,"primary_location":{"id":"doi:10.1145/3769102.3774381","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769102.3774381","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM/IEEE Symposium on Edge Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3769102.3774381","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072563140","display_name":"Dexiong Pan","orcid":"https://orcid.org/0000-0003-3037-8912"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Deng Pan","raw_affiliation_strings":["George Washington University, Washington, USA"],"affiliations":[{"raw_affiliation_string":"George Washington University, Washington, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020963730","display_name":"Timothy Wood","orcid":"https://orcid.org/0000-0002-6728-4197"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy Wood","raw_affiliation_strings":["George Washington University, Washington, USA"],"affiliations":[{"raw_affiliation_string":"George Washington University, Washington, USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018088886","display_name":"Samer H. Hamdar","orcid":"https://orcid.org/0000-0001-6896-367X"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samer Hamdar","raw_affiliation_strings":["George Washington University, Washington, USA"],"affiliations":[{"raw_affiliation_string":"George Washington University, Washington, USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072563140"],"corresponding_institution_ids":["https://openalex.org/I193531525"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40799367,"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":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.22349999845027924,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.22349999845027924,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.12039999663829803,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.07720000296831131,"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/data-compression","display_name":"Data compression","score":0.5806000232696533},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5681999921798706},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5062000155448914},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.45840001106262207},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.42899999022483826},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4237000048160553},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4207000136375427},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.397599995136261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7350999712944031},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5963000059127808},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5806000232696533},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5681999921798706},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5062000155448914},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.45840001106262207},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4207000136375427},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.3767000138759613},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3528999984264374},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.30329999327659607},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2768000066280365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26660001277923584},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.26409998536109924},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2578999996185303}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3769102.3774381","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769102.3774381","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM/IEEE Symposium on Edge Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3769102.3774381","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769102.3774381","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM/IEEE Symposium on Edge Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2963098024","https://openalex.org/W4292230951","https://openalex.org/W4402469109"],"related_works":[],"abstract_inverted_index":{"Edge-based":[0],"traffic":[1,31,79],"monitoring":[2],"is":[3],"an":[4,64],"important":[5],"component":[6],"in":[7,34,44],"building":[8],"smart":[9],"transportation":[10],"infrastructure":[11],"that":[12,39],"understands":[13],"the":[14,21],"flow":[15],"of":[16],"vehicles":[17],"and":[18,29,49],"pedestrians.":[19],"Yet":[20],"necessary":[22],"multi-modal":[23],"data":[24,37],"including":[25],"video,":[26],"in-vehicle":[27],"sensors,":[28],"embedded":[30],"monitors":[32],"result":[33],"large-scale":[35],"continuous":[36],"streams":[38],"are":[40],"difficult":[41],"to":[42,53,55,76],"process":[43],"real-time":[45],"on":[46,82],"edge":[47,84],"devices":[48],"would":[50],"be":[51],"wasteful":[52],"send":[54],"a":[56],"distant":[57],"cloud.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62],"propose":[63],"integrated":[65],"framework":[66],"combining":[67],"semantically-guided":[68],"skip":[69],"sampling":[70],"with":[71],"soft":[72],"edge-based":[73],"neural":[74],"compression":[75],"enable":[77],"efficient":[78],"video":[80],"analytics":[81],"resource-constrained":[83],"devices.":[85]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-03T00:00:00"}