{"id":"https://openalex.org/W4402572463","doi":"https://doi.org/10.1109/newcas58973.2024.10666331","title":"High-Rate. Compact In-Sensor Denoising for Active Stereo Vision Towards Embedded Depth Sensing","display_name":"High-Rate. Compact In-Sensor Denoising for Active Stereo Vision Towards Embedded Depth Sensing","publication_year":2024,"publication_date":"2024-06-16","ids":{"openalex":"https://openalex.org/W4402572463","doi":"https://doi.org/10.1109/newcas58973.2024.10666331"},"language":"en","primary_location":{"id":"doi:10.1109/newcas58973.2024.10666331","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/newcas58973.2024.10666331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 22nd IEEE Interregional NEWCAS Conference (NEWCAS)","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/A5037588129","display_name":"Pouya Houshmand","orcid":"https://orcid.org/0000-0003-2935-8842"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Pouya Houshmand","raw_affiliation_strings":["ESAT-MICAS, KU Leuven,Leuven,Belgium"],"affiliations":[{"raw_affiliation_string":"ESAT-MICAS, KU Leuven,Leuven,Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050699819","display_name":"Jean-S\u00e9bastien Staelens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jean-Sebastien Staelens","raw_affiliation_strings":["Voxelsensors,Bruxelles,Belgium"],"affiliations":[{"raw_affiliation_string":"Voxelsensors,Bruxelles,Belgium","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028814183","display_name":"Ward Van Der Tempel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ward Van der Tempel","raw_affiliation_strings":["Voxelsensors,Bruxelles,Belgium"],"affiliations":[{"raw_affiliation_string":"Voxelsensors,Bruxelles,Belgium","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012150553","display_name":"Marian Verhelst","orcid":"https://orcid.org/0000-0003-3495-9263"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Marian Verhelst","raw_affiliation_strings":["ESAT-MICAS, KU Leuven,Leuven,Belgium"],"affiliations":[{"raw_affiliation_string":"ESAT-MICAS, KU Leuven,Leuven,Belgium","institution_ids":["https://openalex.org/I99464096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037588129"],"corresponding_institution_ids":["https://openalex.org/I99464096"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13155421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"11","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.989300012588501,"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":0.989300012588501,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9671000242233276,"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/computer-vision","display_name":"Computer vision","score":0.6470767855644226},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6437998414039612},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5776503086090088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5771611928939819},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.5596256852149963},{"id":"https://openalex.org/keywords/image-sensor","display_name":"Image sensor","score":0.4236086905002594}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6470767855644226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6437998414039612},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5776503086090088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5771611928939819},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.5596256852149963},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.4236086905002594}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/newcas58973.2024.10666331","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/newcas58973.2024.10666331","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 22nd IEEE Interregional NEWCAS Conference (NEWCAS)","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/752416","is_oa":false,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/752416","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"22nd IEEE Interregional NEWCAS Conference (NEWCAS), CANADA, Sherbrooke, 16-19 June 2024","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1492510670","https://openalex.org/W1980081806","https://openalex.org/W2244851982","https://openalex.org/W2292286909","https://openalex.org/W2782061689","https://openalex.org/W2782660655","https://openalex.org/W2790853419","https://openalex.org/W2921126577","https://openalex.org/W3013851562","https://openalex.org/W3108071383","https://openalex.org/W3132942233","https://openalex.org/W3134833667","https://openalex.org/W3136617232","https://openalex.org/W3204766074","https://openalex.org/W4205817027","https://openalex.org/W4220916359","https://openalex.org/W4249932213","https://openalex.org/W4283801280","https://openalex.org/W4313572055","https://openalex.org/W4318827279","https://openalex.org/W4360862185","https://openalex.org/W4385192490","https://openalex.org/W4385801513","https://openalex.org/W6606171110","https://openalex.org/W6810726929"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Depth":[0],"sensing":[1,68,143],"systems":[2,144],"based":[3,62],"on":[4,145],"active":[5,83],"stereo":[6],"vision":[7],"and":[8,15,40,51,95,102,124,155],"SPAD-based":[9],"sensors":[10],"promise":[11],"high":[12,92],"resolution,":[13],"accuracy":[14,43],"throughput,":[16],"but":[17],"their":[18],"real-world":[19],"deployment":[20],"is":[21,136],"hindered":[22],"by":[23,29],"the":[24,30,36,46,74,78,82,121,133,146,149],"amount":[25],"of":[26,77,81,100],"noise":[27,38,105],"captured":[28],"highly":[31],"sensitive":[32],"pixels.":[33],"To":[34],"reduce":[35],"detected":[37,79],"-":[39,44],"thus":[41,119],"maximize":[42],"under":[45],"tight":[47,116],"sensor":[48],"power":[49,123],"consumption":[50],"MIPI":[52],"bandwidth":[53],"constraints,":[54],"we":[55],"propose":[56],"a":[57,91,97,115,137],"hardware-efficient,":[58],"embedded,":[59],"neural":[60],"network":[61],"denoising":[63],"processing":[64],"system":[65],"for":[66,140],"depth":[67,142],"via":[69],"dot":[70],"scanning.":[71],"It":[72],"exploits":[73],"spatio-temporal":[75],"correlations":[76],"trajectory":[80],"light":[84],"to":[85],"accurately":[86],"track":[87],"rapid":[88],"changes,":[89],"at":[90],"frame":[93],"rate":[94],"across":[96],"wide":[98],"range":[99],"indoor":[101],"outdoor":[103,141],"background":[104],"levels.":[106],"All":[107],"required":[108],"computations":[109],"are":[110],"fully":[111],"done":[112],"in-sensor,":[113],"within":[114],"area":[117],"budget,":[118],"avoiding":[120],"major":[122],"latency":[125],"overheads":[126],"from":[127],"off-sensor":[128],"computation.":[129],"We":[130],"demonstrate":[131],"that":[132],"presented":[134],"approach":[135],"valid":[138],"solution":[139],"edge,":[147],"allowing":[148],"tracking":[150],"with":[151],">8dB":[152],"input":[153],"SNR":[154],"sub-nJ/px":[156],"energy":[157],"consumptions":[158],"while":[159],"requiring":[160],"\u00b1100":[161],"gates/px.":[162]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
