6533b831fe1ef96bd1298f68
RESEARCH PRODUCT
Using Temporal Texture for Content-Based Video Retrieval
Edoardo ArdizzoneMarco La CasciaAlessandro Caprasubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryNode (networking)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVariation (game tree)Star (graph theory)CBIR texture analysisTexture (geology)Language and LinguisticsComputer Science ApplicationsHuman-Computer InteractionAutoregressive modelImage textureComputer visionQuery by ExampleArtificial intelligencebusinessRepresentation (mathematics)computerComputingMethodologies_COMPUTERGRAPHICScomputer.programming_languagedescription
Textures evolving over time are called temporal textures and are very common in everyday life. Examples are the smoke flowing or the wavy water of a river. The idea explored in this paper is that image features based on temporal texture could allow a better performance of current content-based video retrieval systems that are mainly based on static characteristics of representative frames, like color and texture. To this aim we analyze the spatio-temporal nature of texture and its application in content-based access to video databases. In particular, we represent temporal texture using the spatio-temporal autoregressive (STAR) model and a variation of self-organizing maps (SOM) where each node is an autoregressive model. These representation schemes have been implemented in a query by example framework to analyze the weaknesses and the strengths of the different approaches. Preliminary experimental results are reported.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2000-06-01 | Journal of Visual Languages & Computing |