Matches in SemOpenAlex for { <https://semopenalex.org/work/W3201726334> ?p ?o ?g. }
- W3201726334 endingPage "634" @default.
- W3201726334 startingPage "623" @default.
- W3201726334 abstract "(Discriminative) Correlation Filter has been successfully applied to visual tracking and has advanced the field significantly in recent years. Correlation filter-based trackers consider visual tracking as a problem of matching the feature template of the object and candidate regions in the detection sample, in which correlation filter provides the means to calculate the similarities. In contrast, convolution filter is usually used for blurring, sharpening, embossing, edge detection, etc. in image processing. On the surface, correlation filter and convolution filter are usually used for different purposes. In this paper, however, we prove, for the first time, that correlation filter and convolution filter are equivalent in the sense that their minimum mean-square errors (MMSEs) in visual tracking are equal, under the condition that the optimal solutions exist and the ideal filter response is Gaussian and centrosymmetric. This result gives researchers the freedom to choose correlation or convolution in formulating their trackers. It also suggests that the explanation of the ideal response in terms of similarities is not essential." @default.
- W3201726334 created "2021-10-11" @default.
- W3201726334 creator A5029265672 @default.
- W3201726334 creator A5031943397 @default.
- W3201726334 creator A5082243302 @default.
- W3201726334 creator A5085914001 @default.
- W3201726334 date "2021-01-01" @default.
- W3201726334 modified "2023-09-23" @default.
- W3201726334 title "Equivalence of Correlation Filter and Convolution Filter in Visual Tracking" @default.
- W3201726334 cites W161114242 @default.
- W3201726334 cites W1964846093 @default.
- W3201726334 cites W1966382073 @default.
- W3201726334 cites W2044986361 @default.
- W3201726334 cites W2099736636 @default.
- W3201726334 cites W2149829493 @default.
- W3201726334 cites W2154889144 @default.
- W3201726334 cites W2191054309 @default.
- W3201726334 cites W2214352687 @default.
- W3201726334 cites W2273403121 @default.
- W3201726334 cites W2341818270 @default.
- W3201726334 cites W2518013266 @default.
- W3201726334 cites W2557641257 @default.
- W3201726334 cites W2558899534 @default.
- W3201726334 cites W2569436968 @default.
- W3201726334 cites W2591753034 @default.
- W3201726334 cites W2599547527 @default.
- W3201726334 cites W2681067697 @default.
- W3201726334 cites W2799058067 @default.
- W3201726334 cites W2884367402 @default.
- W3201726334 cites W2921580843 @default.
- W3201726334 cites W2947059957 @default.
- W3201726334 cites W2963227409 @default.
- W3201726334 cites W2963534981 @default.
- W3201726334 cites W2964069521 @default.
- W3201726334 cites W2964071664 @default.
- W3201726334 cites W2987346479 @default.
- W3201726334 cites W2989688045 @default.
- W3201726334 cites W3035211844 @default.
- W3201726334 cites W3035453691 @default.
- W3201726334 cites W3035466700 @default.
- W3201726334 cites W3035571898 @default.
- W3201726334 cites W3089861793 @default.
- W3201726334 cites W3091131369 @default.
- W3201726334 cites W3095366650 @default.
- W3201726334 cites W3100321043 @default.
- W3201726334 cites W3102624093 @default.
- W3201726334 cites W3108235634 @default.
- W3201726334 cites W3112404983 @default.
- W3201726334 cites W3131925909 @default.
- W3201726334 cites W3132084862 @default.
- W3201726334 cites W3172553658 @default.
- W3201726334 cites W4226162296 @default.
- W3201726334 cites W657953742 @default.
- W3201726334 doi "https://doi.org/10.1007/978-3-030-87361-5_51" @default.
- W3201726334 hasPublicationYear "2021" @default.
- W3201726334 type Work @default.
- W3201726334 sameAs 3201726334 @default.
- W3201726334 citedByCount "0" @default.
- W3201726334 crossrefType "book-chapter" @default.
- W3201726334 hasAuthorship W3201726334A5029265672 @default.
- W3201726334 hasAuthorship W3201726334A5031943397 @default.
- W3201726334 hasAuthorship W3201726334A5082243302 @default.
- W3201726334 hasAuthorship W3201726334A5085914001 @default.
- W3201726334 hasBestOaLocation W32017263342 @default.
- W3201726334 hasConcept C106131492 @default.
- W3201726334 hasConcept C117220453 @default.
- W3201726334 hasConcept C154945302 @default.
- W3201726334 hasConcept C15744967 @default.
- W3201726334 hasConcept C19417346 @default.
- W3201726334 hasConcept C202444582 @default.
- W3201726334 hasConcept C2524010 @default.
- W3201726334 hasConcept C2775936607 @default.
- W3201726334 hasConcept C2780069185 @default.
- W3201726334 hasConcept C31972630 @default.
- W3201726334 hasConcept C33923547 @default.
- W3201726334 hasConcept C41008148 @default.
- W3201726334 hasConcept C45347329 @default.
- W3201726334 hasConcept C50644808 @default.
- W3201726334 hasConceptScore W3201726334C106131492 @default.
- W3201726334 hasConceptScore W3201726334C117220453 @default.
- W3201726334 hasConceptScore W3201726334C154945302 @default.
- W3201726334 hasConceptScore W3201726334C15744967 @default.
- W3201726334 hasConceptScore W3201726334C19417346 @default.
- W3201726334 hasConceptScore W3201726334C202444582 @default.
- W3201726334 hasConceptScore W3201726334C2524010 @default.
- W3201726334 hasConceptScore W3201726334C2775936607 @default.
- W3201726334 hasConceptScore W3201726334C2780069185 @default.
- W3201726334 hasConceptScore W3201726334C31972630 @default.
- W3201726334 hasConceptScore W3201726334C33923547 @default.
- W3201726334 hasConceptScore W3201726334C41008148 @default.
- W3201726334 hasConceptScore W3201726334C45347329 @default.
- W3201726334 hasConceptScore W3201726334C50644808 @default.
- W3201726334 hasLocation W32017263341 @default.
- W3201726334 hasLocation W32017263342 @default.
- W3201726334 hasOpenAccess W3201726334 @default.
- W3201726334 hasPrimaryLocation W32017263341 @default.
- W3201726334 hasRelatedWork W1497101000 @default.
- W3201726334 hasRelatedWork W1543936162 @default.