ANMS: Asynchronous Non-Maximum Suppression in Event Stream

ANMS: Asynchronous Non-Maximum Suppression in Event Stream | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ANMS: Asynchronous Non-Maximum Suppression in Event Stream Qianang Zhou, Junlin Xiong, Youfu Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3355531/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Non-Maximum Suppression (NMS) is an essential post-processing algorithm that is widely used in frame-based tasks. However, executing NMS in asynchronous event streams results in frequent discontinuities and high computational complexity, which limits the performance of asynchronous event-based algorithms, such as corner event detection. To address this issue, this paper proposes a general-purpose Asynchronous NMS pipeline (ANMS) and applies it to corner event detection. The proposed pipeline extracts fine feature streams from the output of original detectors and automatically adjusts the strength of suppression to accommodate varying motion speeds. The ANMS operates with a latency of less than 0.2ms on most detectors, without affecting real-time detection. To test ANMS comprehensively, a scoring method was designed for detectors without corner scores, and a simulated sequence was created to supplement the real dataset. Evaluation on the public dataset indicates that ANMS improves the performance of popular detectors with negligible latency. Additionally, the pipeline is a natural extension of NMS, and is applicable to other asynchronous scoring tasks for event cameras. The C++ implementation of ANMS-based detectors has been rreleased here: https://github.com/ZhouQianang/ANMS. Event Camera Asynchronous Signal Processing Visual Tracking Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 13 Aug, 2024 Reviewers invited by journal 21 Sep, 2023 Submission checks completed at journal 19 Sep, 2023 Editor assigned by journal 19 Sep, 2023 First submitted to journal 14 Sep, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3355531","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":234705481,"identity":"995056bc-5803-41e2-bb78-66b52712f3d8","order_by":0,"name":"Qianang Zhou","email":"","orcid":"","institution":"University of Science and technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qianang","middleName":"","lastName":"Zhou","suffix":""},{"id":234705482,"identity":"bef4036b-00dc-455c-a1b1-88250dba2637","order_by":1,"name":"Junlin Xiong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYDACZiBm/PdfDolLjBYGNmZjKIsYLQwQLYkNRGsxOM587OEXHrb0DefPH/zAUGGd2MB+9gBeLZLNbOnGMhI8uRtuJDNLMJxJT2zgyUvAq4WfmcdMWsJAAqiFmY2Bse1wYoMEjwEBX4C0JBikG5w/DNTyjwgtIFskPxxISDA4kAzU0kCEFqBf0qQZGw4YzryRbCyRcCzduI0nB78WoHuOSf5sOCDPd/7gww8faqxl+9nP4NcCAsw8MFYCyHcE1QMB4w9iVI2CUTAKRsHIBQB7bDxnAZKxzgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Science and technology of China","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Junlin","middleName":"","lastName":"Xiong","suffix":""},{"id":234705483,"identity":"2fcd9e5b-4773-400c-a0c5-0b737d950fdd","order_by":2,"name":"Youfu Li","email":"","orcid":"","institution":"City University of Hong Kong","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Youfu","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2023-09-14 13:14:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3355531/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3355531/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":43673048,"identity":"9e29d1fd-9212-436f-b20f-5cf406459268","added_by":"auto","created_at":"2023-09-26 05:01:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2039873,"visible":true,"origin":"","legend":"","description":"","filename":"manuscriptLatex.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3355531/v1_covered_57ad1671-f199-4559-bd0c-16aa671e86d9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"ANMS: Asynchronous Non-Maximum Suppression in Event Stream","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"signal-image-and-video-processing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"sivp","sideBox":"Learn more about [Signal, Image and Video Processing](http://link.springer.com/journal/11760)","snPcode":"11760","submissionUrl":"https://submission.nature.com/new-submission/11760/3","title":"Signal, Image and Video Processing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Event Camera, Asynchronous Signal Processing, Visual Tracking","lastPublishedDoi":"10.21203/rs.3.rs-3355531/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3355531/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eNon-Maximum Suppression (NMS) is an essential post-processing algorithm that is widely used in frame-based tasks. 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