基于雙曲空間的無監(jiān)督視頻異常檢測(cè)方法

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中圖分類號(hào)：TP391 文獻(xiàn)標(biāo)志碼：A 文章編號(hào)：1001-3695（2025）07-042-2234-07

doi：10.19734/j. issn.1001-3695.2024.08.0371

Abstract：Inthefieldofvideoanomalydetection，anomalouseventsoftendemonstratetemporalcontinuityandsimlarityExisting unsupervised methods typicallysegment videos into multipleclipsandrandomlyselectsubsets for training，disrupting the continuityofanomalouseventsandcausing thelossofcriticalspatiotemporalinformation.AditionallycurrntEuclidean space-basedmethodsencounterlimitationsinembeddngspacedimensionalitymakingitdificulttoefectivelycapturethelatent geometrichierarchyofvideodata.Toaddress these isues，thispaper introducedanovelunsupervisedvideoanomalydetection methodbasedonhyperbolic space.Itdesignedaspatiotemporalfeatureconstruction（STFC）module toextract temporalcorrelationsand featuresimilaritiesamong videosegments，mbedding themintoLorentzandPoincaréballhyperbolicspaces to learnrichervideorepresentationsthatmoreefectivelydistinguishnormalfromabnormal events.Experimentsshowthatthis method achieves AUC scores of 93.26% and 77.55% on the Shanghai Tech and UCF-Crime datasets，respectively，outperforming existingunsupervised video anomalydetectionmethods.Theseresultsconfirmtheadvantageof hyperbolic spaceincapturingthelatentgeometrichierarchyofvideodataandhighlightitspotential inenhancinganomalydetectioncapabilities.

KeyWords：unsupervised；video anomaly detection；Lorentz hyperbolicspace；Poincaréballhyperbolic space

0 引言

隨著國(guó)家公共安全意識(shí)的不斷增強(qiáng)，監(jiān)控?cái)z像頭在街道、十字路口、銀行和購(gòu)物中心等公共場(chǎng)所的使用日益普及，旨在提高整體的公共安全水平。（剩余17085字）