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- W157386987 abstract "Computer vision applications are often confronted by the need to differentiate between objects and their shadows. A number of shadow detection algorithms have beenproposed in literature, based on physical, geometrical, and other heuristic techniques.While most of these existing approaches are dependent on the scene environments andobject types, the ones that are not, are classified as superior to others conceptuallyand in terms of accuracy. Despite these efforts, the design of a generic, accurate,simple, and efficient shadow detection algorithm still remains an open problem. Inthis thesis, based on a physically-derived hypothesis for shadow identification, novel,multi-domain shadow detection algorithms are proposed and tested in the spatial andtransform domains.A novel Affine Shadow Test Hypothesis has been proposed, derived, and validatedacross multiple environments. Based on that, several new shadow detection algorithmshave been proposed and modelled for short-duration video sequences, wherea background frame is available as a reliable reference, and for long duration videosequences, where the use of a dedicated background frame is unreliable. Finally, additionalalgorithms have been proposed to detect shadows in still images, where theuse of a separate background frame is not possible. In this approach, the authorshows that the proposed algorithms are capable of detecting cast, and self shadowssimultaneously.All proposed algorithms have been modelled, and tested to detect shadows in thespatial (pixel) and transform (frequency) domains and are compared against state-of-art approaches, using popular test and novel videos, covering a wide range oftest conditions. It is shown that the proposed algorithms outperform most existingmethods and effectively detect different types of shadows under various lighting andenvironmental conditions." @default.
- W157386987 created "2016-06-24" @default.
- W157386987 creator A5012305702 @default.
- W157386987 date "2006-01-01" @default.
- W157386987 modified "2023-09-22" @default.
- W157386987 title "Cast shadow modelling and detection" @default.
- W157386987 hasPublicationYear "2006" @default.
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